UNIVERSITY OF CINCINNATI

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1 UNIVERSITY OF CINCINNATI Date: October 17, 2006 I, Gregory S. Johnson, hereby submit this work as part of the requirements for the degree of: Doctor of Philosophy (PhD) in: Philosophy It is entitled: On the Relationship between Psychology and Neurobiology: Levels in the Cognitive and Biological Sciences This work and its defense approved by: Chair: Professor Thomas Polger Professor Robert Richardson Professor John Bickle Professor Jenefer Robinson

2 On the Relationship between Psychology and Neurobiology: Levels in the Cognitive and Biological Sciences A dissertation submitted to the Division of Research and Advanced Studies of the University of Cincinnati in partial fulfillment of the requirements for the degree of DOCTORATE OF PHILOSOPHY (Ph.D.) in the Department of Philosophy of the College of Arts and Sciences 2007 by Gregory S. Johnson B.A., Georgetown University, 1995 Committee Chair: Thomas W. Polger

3 3 Abstract In this dissertation I offer an account of the relationship between psychology and neurobiology. I do this in terms of two types of levels, levels of organization and levels of explanation. A hierarchy of levels of organization orders the entities and activities that are found in nature. Alternatively, the different ways of describing those things that we find in nature are placed at levels of explanation. The thesis of my dissertation is that these two types of levels need to be used together in order to understand the relationship between psychology and neurobiology. Neurobiological entities are located at the appropriate levels of organization. The descriptions offered in cognitive psychology of the capacities that humans have are located at a level of explanation above the neurobiological levels of organization. Selecting the correct levels of organization entails identifying the types of entities and the types of activities that are able to carry out psychological capacities. Based upon this requirement the appropriate levels of organization are the level where neurons and their activities occur and the level where macromolecules and their activities are found. The activities at these two levels of organization carry out the psychological capacities that are described by cognitive psychology at a higher level of explanation. In the first part of the dissertation (chaps.1 2) I develop and defend a hierarchy of levels of organization that is based upon Wimsatt s account of levels of organization. In the second part of the dissertation (chaps. 3 4) I use Marr s account of levels of explanation as the basis for my analysis of levels of explanation. I argue that the type of description that is offered in cognitive psychology is the type that belongs at Marr s highest level of explanation. In the final part of the dissertation (chaps. 5 6) I combine these two different hierarchies, levels of organization and

4 4 levels of explanation, into a two-dimensional framework. This entails locating the lowest level of explanation at one, or in this case two, of the levels of organization. Therefore, the hierarchy of levels of explanation is composed of different kinds of descriptions of the entities and activities that are found at the neuronal and macromolecular levels of organization.

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6 6 Acknowledgments This dissertation, and my graduate studies more generally, have been greatly aided by the generous help of my advisor, Tom Polger, to whom I would like to extend sincere thanks for all of his efforts. Thanks are also due to the other members of my dissertation committee, John Bickle, Bob Richardson, and Jenefer Robinson. I would also like to thank the other faculty and staff of the University of Cincinnati philosophy department for providing a helpful and enjoyable environment while I was a graduate student. I am also grateful for the financial support provided by the Charles Phelps Taft Research Center for one year while I worked on this dissertation.

7 Contents List of Figures and Tables 9 Introduction 11 1 Levels of Organization Wimsatt s account of levels of organization Interaction versus composition Levels of organization The cell network level of organization The sub-cellular level of organization The chemical level of organization Higher levels Objections 47 2 A Critique of Churchland Churchland s analysis of levels Churchland s hierarchy of levels of organization The cell network level of organization Synopsis of Churchland s ten levels Brain areas 89 3 Levels of Explanation Marr s account of levels of explanation An example from Marr The computational theory Representation and algorithm Neural implementation Marr s middle level Classical computational models Connectionist models Biologically realistic models Marr s middle level Models of Cognitive Appraisals and the Level of the Computational Theory Background for the models Appraisal theories Constraints 124

8 4.1.3 Initial evidence for the appraisal process Models of the appraisal capacity Roseman Methodologies Scherer Process models of the appraisals A review of Marr s middle level A process model of the appraisals Critique A Two Dimensional Model of Levels Levels of explanation and levels of organization The hierarchy of levels of explanation Levels of organization Determining the appropriate levels of organization The organism level of organization Brain areas The cell network level of organization The sub-cellular level of organization The chemical level of organization Critiques of Lycan and Craver Lycan Lycan s commitment to homunclular functionalism Lycan s commitment to the continuity of levels of nature A critique of Lycan s account Kim Craver Craver s account of mechanistic levels The mechanistic level Spatial memory Decomposition Concluding Remarks 216 References 219

9 9 List of Figures and Tables Figure 1.1 Wimsatt s levels of organization 17 Figure 1.2 The cell network level of organization 26 Figure 1.3 Modulation of single cell responses 28 Figure 1.4 Neural circuit in the visual cortex 29 Figure 1.5 Spiny stellate cell 32 Figure 1.6 Monocularly deprived axons 35 Figure 1.7 Intracellular cascade 36 Figure 1.8 Removal of synapses 39 Figure 1.9 Calmodulin and calmodulin-dependent protein kinase II 41 Figure 1.10 Thymine and adenine 42 Figure 2.1 Brain areas for song production in canaries 92 Figure 3.1 Motion used for identifying shapes 102 Figure 3.2 The aperture problem 103 Figure 3.3 Time derivative of the zero-crossing 105 Figure 3.4 Neural implementation of edge detection 106 Figure 3.5 Neural implementation of motion detection 106 Figure 3.6 ACT-R program 110 Figure 3.7 Connectionist network 113 Figure 3.8 A node in a connectionist network 113 Figure 3.9 Compartmental model of a pyramidal cell 114 Figure 3.10 Compartmental model represented as electrical circuits 114 Figure 3.11 Model of neurons in the piriform cortex 116 Figure 4.1 Skin conductance levels from Speisman et al (1964) 129 Figure 4.2 Skin conductance levels from Lazarus and Alfert (1964) 131 Figure 4.3 Roseman s model of cognitive appraisals 132 Figure 4.4 Scherer s process model of the cognitive appraisals 153 Figure 4.5 Roseman s (2001) model of the cognitive appraisals 159 Figure 4.6 Scherer s model of the cognitive appraisals 160 Figure 5.1 Levels of organization and levels of explanation 164 Figure 5.2 Levels of organization and levels of explanation 171

10 10 Figure 5.3 Microstimulated feeding motion 177 Figure 5.4 Entities interacting at three levels of organization 182 Figure 6.1 Lycan s levels of nature 192 Figure 6.2 Levels of organization and levels of explanation 192 Figure 6.3 Lycan s decomposition of a face recognizer 195 Figure 6.4 Levels of a key 199 Figure 6.5 Craver s mechanistic levels 207 Figure 6.6 The relationship between mechanistic levels 213 Figure 6.7 The molecular process for long-term potentiation 214 Table 1.1 Levels of organization based upon composition 21 Table 1.2 Churchland s hierarchies of levels of organization 57 Table 2.2 Synopsis of Churchland s ten levels of organization 88 Table 4.1 Marr s levels of explanation and the psychological sciences 121 Table 4.2 Scherer s stimulus evaluation checks 142

11 11 Introduction This dissertation provides an account of the relationship between psychology and neurobiology. I concentrate on cognitive psychology and those capacities that are recognized as psychological capacities: memory, language use and comprehension, emotion, vision, and so on. Given these psychological capacities, which can be and often are described in the language of cognitive psychology, the issue is how to explain the relationship between these types of descriptions and the neurobiology that carries out the capacities. My answer is provided using levels as the framework. Therefore, one task is to establish the idea that more than one type of level is required in order to accurately describe the relationship between psychology and neurobiology. The two required types of levels are levels of organization and levels of explanation. Only employing one type of level, which gives us a single hierarchy of levels, is not sufficient for providing the correct picture of this relationship. Before saying more about my account I will briefly describe different ways in which levels are used. As Churchland and Sejnowki (1988) point out, the three main ways of talking about levels are as levels of organization, levels of explanation, and levels of processing. Only levels of organization and levels of explanation concern this project, but I will briefly lay out all three so that we are clear on the different ways of using the term levels. The term levels is probably most commonly used to refer to levels of organization. When identifying a level of organization one is generally trying to identify a particular playing field (i.e., a level) and the different entities that occupy it. Having a relatively clear idea of what entities are at a particular level of organization, and not at some other level, then suggests what sort of composition and causal relations might exist between different entities. It is expected that

12 12 entities at one level of organization will causally interact only with entities at the same level of organization, and not with entities at higher or lower levels of organization. With regard to composition, it is expected that entities at a lower level will compose the entities at higher levels. For example, humans are at one level of organization and they causally interact with other humans, other animals, and artifacts of the appropriate size. At a lower level are the organs that compose humans, which causally interact with each other, but not with other humans. A second way that levels are sometimes used is as levels of explanation (this same use is sometimes referred to as levels of description or levels of analysis). Churchland and Sejnowski say of this type of levels, Levels of analysis concern the conceptual division of a phenomenon in terms of different classes of questions that can be asked about it (1988:741). The basic idea is that these types of levels provide a way of ordering different kinds of descriptions of the same phenomenon. And third, although levels of processing do not concern this project, I will discuss what is meant by the term in order to distinguish it from the other ways of talking about levels. Levels of processing are a series of points or stages within a complex, but fairly linear procedure or process. Levels are demarcated by either or both: (1) their temporal placement within the process so levels will line up with respect to the order in which they occur in the process; or (2) levels are demarcated by their relative simplicity or complexity with respect to the final stage of the process so simple levels precede more complex ones and the phenomena at the more complex levels are (in some sense) built up from the phenomena at the simpler levels. A unique feature of levels of processing is that, unlike levels of organization (or levels of explanation), there are causal interactions between the different levels of processing.

13 13 Returning to my project, using levels of organization and levels of explanation together yields a more complex picture than is found in accounts that only employ a single hierarchy of levels. The benefit is that levels of organization give us the resources to order the entities and activities that we find in nature, while levels of explanation provide a method of ordering the different ways that we have of describing those things that we find in nature. If only a single hierarchy is used, then this distinction is not possible. But when both of these types of levels are used it generates a two-dimensional space of levels. And as a project in the philosophy of psychology one defense of this two-dimensional framework is that it provides a useful way of investigating the relationship between psychology and neurobiology. The framework also yields a particular account of the relationship between psychology and neurobiology. A large part of the work in this dissertation is spent developing the details of this account. But in general arriving at the answer only requires following through on the commitments entailed in employing levels of organization and levels of explanation. The answer that is generated is that descriptions that are offered in cognitive psychology of the capacities that humans have are abstract descriptions of the activity that occurs at the cellular level of organization and the molecular level of organization. 1 Before turning to the outline of this dissertation I want to emphasize that this is a project in the philosophy of psychology. The issues that I address are focused on a particular question concerning the phenomena that are understood as psychological capacities, namely, their relationship to neurobiological entities and activities. I am not, in this dissertation, addressing the 1 I do not actually use these terms: cellular level of organization and molecular level of organization, because I want to create some space between the levels that I use in this project and the way those terms are used for the branch of neuroscience (i.e., cellular and molecular neuroscience). I use instead the terms cell network level of organization and sub-cellular level of organization. But for the moment cellular level and molecular level are sufficient to indicate what I mean.

14 14 issue of reductionism or of eliminativism, although what is done here may have an application to those problems. Outline of the project In the first chapter I review Wimsatt s account of levels of organization. He suggests that levels of organization can be characterized in terms of entities interacting in regular and predictable ways with each other. Adopting his analysis I construct a hierarchy of the levels of organization that fall within the scope of the brain. In chapter two I look at a hierarchy of levels of organization that is offered by Churchland (1986). Critiquing her account also provides the opportunity to further explain some of aspects of the hierarchy that I offered in chapter one. In the third chapter I lay out Marr s account of levels of explanation, and discuss the three levels that he suggests are required in order to completely explain an information processing task. In this chapter I also look at some other types of explanations (symbolic modeling, connectionist modeling, and biologically realistic modeling) that, broadly speaking fall within the scope of his middle level of explanation. Then in chapter four I examine some models that have been offered in cognitive psychology to explain the early part of the emotion process. The purpose of looking at these models is to demonstrate that the format of these types of explanations is what Marr characterized as his highest level of explanation. Recognizing that these models are the type of description that is offered at a particular level of explanation allows us to place psychological descriptions of capacities or at least one example of such into a hierarchy of levels of explanation. In chapter five I offer the account in which levels of organization and levels of explanation are combined to form the two dimensional model. This model illustrates that

15 15 psychological descriptions of capacities are a certain, abstract way of describing the activity that occurs among neurons (at one level of organization), and among macromolecules (at another level of organization). In the final chapter I contrast my account with the accounts offered by William Lycan (1981, 1987) and by Carl Craver (2002). This is an opportunity to demonstrate some of the problems that arise when one attempts to explain psychological capacities with only a single hierarchy of levels.

16 Chapter Levels of Organization In this chapter I offer an account of the different levels of organization that fall within the scope of the brain. I begin by reviewing Wimsatt s (1976) analysis of levels of organization. Using this as the starting point, I develop a hierarchy of levels by applying Wimsatt s analysis to several examples of different types of activities that are found in the brain. The hierarchy of levels of organization that is developed here is one important part of the account of the relationship between psychology and neurobiology that I will lay out in chapter five. 1.1 Wimsatt s account of levels of organization Wimsatt begins by suggesting that the best way in which to understand levels of organization is by using size (1976: 237 8). Larger entities are at higher levels of organization and smaller entities are at lower levels of organization. Even if size alone cannot be used as the sole variable that determines what levels of organization are, it is a good indicator of the level of organization at which an entity belongs. As Wimsatt points out in a footnote, one reason why size is a useful guide is because forces act differently on entities of different sizes, or only act upon entities of a certain size. He explains this by saying, Different forces can have different ranges either because their force laws vary with different powers of the radius or because in our world some with the same exponent in their force laws are cancelled out at close ranges (electrostatic forces), while others (gravitation) are not (1976: 237, n12).

17 Chapter 1 17 If the entities in the world are delineated on the basis of size, we find that entities appear to be found at (roughly) certain sizes (1976: 240 1, figure 1.1). 1 But more important than size alone as an indicator of levels of organization is size as an indicator of a regularity and predictability of interactions (1976: 238) among the entities at each size. If the entities at certain sizes do have regular and predictable interactions then this regularity and predictability of interactions suggests that size is a relevant variable for establishing an ordered set of levels. Figure 1.1. Wimsatt s diagram of different possible plots for size versus regularity and predictability of interactions. The suggestion, which is made in the top plot, is that the regularity and predictability of interactions (on the y-axis) will be high for some sizes and low for others. The slightly less regular plot on the bottom ( Our World? ) suggests that the regularity and predictability of interactions are quite high for smaller sizes (i.e., the first few peaks) and becomes progressively flatter as size increases, although still retaining dips and rises. From Wimsatt (1976: 240). 1 His groups of entities, in increasing size, are: the atomic, the molecular, the macro-molecular, the unicellular, smaller metazoan, larger metazoan, and the socio-cultural ecological.

18 Chapter 1 18 However, we do not know initially that the interactions of the entities are going to be equally regular and predictable for each of the groups of entities of a particular size, or even that size is the reason that there is any regularity or predictability at all. In order to determine why these groups indicate that there will be regular and predictable interactions, Wimsatt suggests that there have to be certain conditions in place that generate the regular and predictable interactions. For example, natural selection, or the pressure from natural selection, is one of these conditions. Given change over time on an evolutionary time scale, what counts as an entity will change. At one point single cells were the most highly evolved biological entity, at a later point multicellular organisms were, and at a still later point metazoan organisms were. In this case there is a condition, pressure from natural selection, that causes organisms to find loci of predictability and regularity, that is, places where their existence is relatively stable with respect to finding food and not being food themselves. 2 This locus of predictability and regularity e.g., the space occupied by metazoan organisms can then be taken to constitute a level of organization. On the other hand, errant changes in size that make it more difficult for an organism or a group of organisms to find food or avoid predators would make those organisms interactions less predictable and regular. In addition to the conditions created by natural selection, other conditions generate other loci of predictability and regularity. As Wimsatt says, Atomic nuclei and molecules constitute two other levels of organization and foci of regularity. They are so because they are the most probable states of matter under certain ranges of conditions (1976: 239). At this point in his argument Wimsatt is motivating the idea that there are conditions in the world which have a tendency (a high probability) of generating regularity. These places 2 As Wimsatt notes, this is an oversimplification (1976: 238).

19 Chapter 1 19 where regularity and predictability are found can then be characterized as levels of organization. So, when a level of organization is understood as a local maximum of predictability and regularity what is being said is that entities have congregated at some particular size because it is there that they have a predictable and regular environment. With this much laid out, Wimsatt proposes to shift the perspective from considering levels of organization as abstract spaces where regularity and predictability are found, to considering levels of organization as a feature of the entities that fill up that space. Now the idea is that a level of organization is a result of entities interacting in stable ways with each other. The gain, in addition to being parsimonious, is that it makes causation (i.e., these interactions) a feature that defines levels of organization rather than a consequence of it (1976: ). That is, the interactions give rise to a level of organization and not the other way around; a level of organization is not a place where interactions are able to occur. To make the shift from thinking of levels as some place in an abstract space to a feature of entities interacting Wimsatt introduces the idea that: organisms are an important feature of the environment of many of the other organisms that they interact with. The presence or absence of an organism may have a strong effect on the predictability and regularity of the environment for another organism, and thus, of how close the latter is to a level of organization the dependence of what constitutes stable states on what else is around is found at all levels of organization (1976: 239). The point that Wimsatt is introducing is that entities causally interacting (and the extent that they are dependent on their interactions) gives rise to a level of organization. In addition to the dependence that entities have on other entities that they interact with, another aspect of this analysis is that it includes the notion of context or environment, since this bears on how entities may interact.

20 Chapter 1 20 Therefore, entities interacting in relatively stable and predictable ways are, or give rise to, a level of organization. Consequently, a level of organization is not some sort of abstract plane which is occupied by a particular set of entities, which because they are on this particular level are able to interact with each other. And so, a correct application of Wimsatt s notion of levels of organization is to say that a series of entities interacting in a stable manner is a level of organization. It then follows that it is incorrect to say that entities occupy a level of organization, as if the level of organization would be there even if there were not entities to occupy it. 3 One important feature of Wimsatt s analysis is that composition is not part of the analysis itself, although it is obviously relevant for many of the uses that we might have when levels of organization are employed (and he does discuss it, 1976: 243). However, I am going to follow Wimsatt and treat composition as a secondary or derivative characteristic of levels of organization. The primary characteristic of a level of organization is entities stably interacting with each other. 1.2 Interaction versus compostion Stepping back from Wimsatt s analysis for a moment, I want to consider an alternative way of defining levels of organization. Listed in the table below is one intuitive way that a partial hierarchy of levels of organization in the brain might be laid out. I am not going to endorse this as a hierarchy of levels of organization, but it might be helpful to contrast this list with Wimsatt s analysis of levels of organization. 3 I agree with Wimsatt s analysis, however, my project of illustrating a two dimensional space of levels is going to lead me to sometimes speak in the looser (incorrect) way.

21 Chapter 1 21 brain diencephalon (telencephalon, brainstem) thalamus, hypothalamus (cortex, hippocampus, amygdale, midbrain, pons, medulla) lateral geniculate nucleus, medial geniculate nucleus, ventral posterior nucleus, etc. cortical layers neurons morphological features of the neuron (eg. dendrites, axons, cell body) (macro)molecules (ion channels, receptors, enzymes, etc.) etc. Table 1.1. A hierarchy of levels of organization based upon composition. This hierarchy is based foremost on composition, and so, for instance, the thalamus is above all of the nuclei (i.e., groups of neurons their cell bodies) that compose it. Looking at one of these nuclei, if we follow the lateral geniculate nucleus (LGN) down this hierarchy, then below it are the six layers of neurons that compose it. The neurons that compose each of the six layers are found at the next level down: magnocellular neurons compose layers one and two, parvocellular neurons compose layers three through six. And at the level below that are the morphological features of neurons. A hierarchy of levels that is constructed in this way using composition as the defining feature does not capture Wimsatt s idea that a level of organization is a feature of stable interactions among entities. In some places on the composition hierarchy, for instance, at the level of neurons, there are interactions that can be tracked and are relatively stable and predictable (that is, the interactions among the neurons). However, at other places on the composition hierarchy there are entities that do not participate in any specific interactions. For instance, I think it is stretching matters, or a case of speaking loosely, to say that the thalamus interacts with the cortex, and even more so to say that the diencephalon interacts with the telencephalon.

22 Chapter 1 22 So the first conclusion to draw, which I believe is uncontroversial, is that a hierarchy of levels based foremost on interaction among entities (that is, Wimsatt s formulation) is not going to be the same as a hierarchy of levels based foremost on composition. I will have more to say about this in what follows. For the time being I just want to be clear that since interaction and composition are obviously different relations, when they are used to construct hierarchies of levels the hierarchies are not going to be the same. The question that follows from this is why choose interactions among entities, as I am, instead of composition as the defining feature of levels of organization? The answer is that we have to start with an idea of why we are interested in levels of organization. For this project the interest is in investigating the relationship between psychology and neurobiology. Therefore, we need to have a notion of levels of organization that is at least not inconsistent with what we think a psychological description might look like. The type of psychological descriptions that I am interested in are of psychological kinds such as language, memory, vision, and the one that I will focus my discussion of psychological description on in chapter four: emotion. The only point I want to make right now concerning these psychological kinds is that they are processes, meaning that we understand them as being temporally extended and usually including the transformation of an input into an output. 4 As a consequence it is reasonable to expect that these sorts of psychological processes are carried out, or realized, biologically by an operation or mechanism of some sort. Thus, with respect to how we want to think about levels of organization, we can use as a starting point the idea that a psychological process is going to be carried out biologically by a series of interactions among entities. Conversely, insofar as hierarchies based upon composition only identify entities 4 I will have more to say about psychological processes in chapters three and four.

23 Chapter 1 23 and says nothing about interactions (of which in some cases there may not be any), it is not a very useful tool for attempting to identify how processes are carried out. A second, related, reason to employ levels based upon the interactions among entities is that if we look at even a minimal amount of evidence from neurobiology it shows us that these processes are in fact extended over some spatial distance (e.g., the process of vision extends from the retina to the temporal lobe of the cortex). So if we want to be able to describe psychological kinds at a particular level of organization, then we need a notion of levels of organization that can accommodate a spatially and temporally extended process. Levels of organization that are based on the stable interactions among entities are able to do this rather straightforwardly insofar as each subsequent interaction increases the distance over which the process is carried out. If, however, levels of organization are based upon composition, they are unable to offer this type of explanation because they do not identify interactions. To be clear, I am not saying that levels based on composition have no utility. They are useful, I presume, for projects such as tracking developmental changes in the brain or investigating comparative neuroanatomy. They just are less useful when the starting point is investigating a process, either psychological or otherwise. 5 In the next few sections I am going to sketch out the levels of organization that are found in the brain when stable interactions among entities are used as the criterion to identify levels. I am going to focus on identifying stable interactions among entities, and distinguishing the entities that participate in stable interactions from entities that do not. I should note that I am going to leave aside identifying the conditions that give rise to those stable interactions. Simply 5 An example of the type of non-psychological process that I have in mind is, for instance, the process that regulates balance. This begins in the inner ear and includes cells in the brainstem, cerebellum, and spinal cord.

24 Chapter 1 24 identifying the interactions will be the criterion that I am going to use here. I will illustrate these levels of organization by appealing to some examples. I am going to begin with what I am calling the cell network level of organization and what this looks like in the primary visual cortex (V1). This will be the starting point for determining the levels of organization that we might say, fall within the scope of the brain. Dropping down a level I have another example, also in V1 of the sub-cellular level of organization. In addition to these two levels of organization there are of course lower levels, some of which may fall within the boundaries of neurobiology. And at the end of this chapter I will also consider a set of entities, brain areas, in order to determine whether they constitute a level above the cell network level. 1.3 Levels of organization The cell network level of organization I will begin with the cell network level of organization. 6 Using Wimsatt s criteria, what makes this a level of organization are the relatively stable interactions that occur between neurons. These are primarily the transmission of impulses from one neuron to another that either excite or inhibit the receiving neuron. 7 Excitatory transmissions cause, or increase the probability, that the receiving neuron will generate an action potential and thus transmit an inhibitory or excitatory 6 I could perhaps have called this the cell or cellular level of organization, but I want to: (1) Start with a clean slate and avoid confusing what I mean with the way that the term is used to refer to a branch of neuroscience (i.e., cellular [and molecular] neuroscience); and (2) Stress that at the level of organization where cells are found we are not always considering one or two cells, although we might be. Even very local interactions have to be understood as occurring within a larger population of interacting neurons (and vice versa). 7 Although I think that it is fair to say that these are considered by most who are interested in cognitive neurobiology (of one sort or another) as the main types of interactions, I am leaving out other types of cells found in the brain, glial and schwann cells, and their interactions, which do not to have a direct role in signal transmission.

25 Chapter 1 25 signal on to another neuron. The inhibitory transmissions increase the probability that the receiving neuron will not transmit a signal to another neuron. In order to transmit an excitatory signal to another neuron the first neuron releases one of the excitatory neurotransmitters (e.g., glutamate, acetylcholine, aspartate) from a presynaptic terminal on its axon into the space between presynaptic terminal and postsynaptic site on the receiving cell (usually on a dendrite of the receiving cell). The release of excitatory neurotransmitter has the effect of shifting the polarity of the postsynaptic membrane towards a threshold point. If the threshold is reached, then the neuron will fire an action potential that moves down that neuron s axon thus allowing this neuron to excite or inhibit other neurons. Generally a number of different presynaptic neurons must release neurotransmitter at the same time in order for the postsynaptic cell to reach threshold and generate an action potential, although how many must be active varies with the amount of neurotransmitter that is released by each particular neuron and the membrane resistance of the post-synaptic cell.

26 Chapter 1 26 Figure 1.2. A drawing of the connections between neurons, showing the axons of the presynaptic cell and the dendrites where the contacts are made on the receiving (postsynaptic) cell. From Jody Culham (2005). Figure 1.2 illustrates the general layout of the contacts between neurons, but in reality the numbers of these synaptic contacts on any given neuron are quite large. To take one example, in the primary visual cortex (V1) of macaque monkeys there are, on average, 3900 synapses per neuron, 83% of which are excitatory (Beaulieu et al 1992). Therefore, for any particular neuron in V1 it has (i.e., receives) about 3200 excitatory contacts on its dendrites. Not all of these will be active at the same time, but the potential is there for the neuron to receive input from a large number of sources. Inhibitory transmission is more or less the opposite. An inhibitory neurotransmitter (e.g., GABA, glycine 8 ) is released from the presynaptic terminal of a neuron s axon. This lowers the probability that the receiving cell will be able to reach threshold and generate an action potential. 8 There are many other neurotransmitters than the ones that I have mentioned here, but as excitatory or inhibitory is not exactly the best way to organize them. Dopamine, for instance, can be either excitatory or inhibitory, depending on the type of receptor that it is released onto.

27 Chapter 1 27 Given that these excitatory and inhibitory interactions between neurons are stable and relatively regular this is a level of organization. We can look at a simplified example of these interactions with a model proposed by Jennifer Lund (Lund and Wu 1997, figure 1.4) for the feed-forward disinhibition of pyramidal neurons in the upper layers of the primary visual cortex (V1). This is a model that attempts to explain the effects observed in single cell activity when the neuron s response is modulated by the presentation of stimuli in the region surrounding the neuron s receptive field (Levitt and Lund, 1997). When a stimulus is placed in the neuron s preferred receptive field (i.e., the preferred location, orientation, and direction of motion), it causes a strong response from the neuron. But if the stimulus is placed in the area just outside of this preferred location (the surround) it does not generate any activity in the neuron. However, when the preferred stimulus and the surround stimulus are presented together this amplifies the neuron s response in some cases and suppresses in others (figure 1.3).

28 Chapter 1 28 Figure 1.3. On the left are the responses of two neurons in layer 3 of a monkey s V1 to a moving grating in their receptive field (the y-axis is impulses per second). As that figure shows, cell D s strongest response is to a 180 orientation and a smaller response is generated to the same orientation (0 ) moving in the opposite direction. Cell E responds strongest when the grating is at 45 / 225 and moving in either direction. The two columns of graphs on the right are the responses of the same neurons when the preferred stimulus is paired with the surround stimulus (the surround cycles through all of the orientations, as shown on the x-axis). In the middle column the preferred stimulus is presented in high contrast and on the far right the preferred stimulus is presented at low contrast. In the graphs on the right the bar is the neuron s response without the surround stimulus, the open circles are the neuron s response to only the surround stimulus, and the filled circles are the neuron s response to both the preferred and the surround presented at the same time. From Levitt and Lund (1997: 73). The two columns on the right in figure 1.3 illustrate that when the center and the surround of the stimulus are at the same orientation (the neuron s preferred orientation) the neuron s activity is suppressed. However, when the surround is at a different orientation than the

29 Chapter 1 29 center, the neuron s activity is in some cases higher than it is when the optimal stimulus is presented without the surround. This is to say that the surround is amplifying the neuron s response. And in some cases, the neuron responds differently when the surround is at the same orientation, but the contrast of the center is different. This is pointed out by the arrow in the two graphs on the right for cell D. When the contrast is high the activity of the neuron is amplified and when the contrast is low it is suppressed. Figure 1.4. A diagram of a simplified neural circuit in the primary visual cortex (V1). The numbers on the right indicate the cortical layers, and the subdivisions of these layers. From Lund and Wu (1997: 123). Now we can look at the model that Lund created to explain this data. The diagram in figure 1.4 shows two spiny stellate cells (the circles), one in the upper part of layer 4Cα and one closer to the 4Cα-4Cβ border in V1. These cells receive input from cells in the lateral geniculate nucleus, which are themselves innervated by cells in the retina. The spiny stellate cell in upper layer 4Cα excites a pyramidal cell in layer 4B. This causes the pyramidal cell to excite a

30 Chapter 1 30 columnar cell, which then releases the inhibitory neurotransmitter GABA onto a chandelier cell in layer 3B. When the chandelier cell is inhibited it no longer, or to a lesser extent, inhibits the pyramidal cell that it projects to. So by virtue of the columnar cell inhibiting the chandelier cell the pyramidal cell is no longer inhibited (i.e., the pyramidal cell is now disinhibited). One possible purpose for these columnar cells is, as Lund and Wu say, to act as inhibitory controllers of the chandelier neurons, ensuring that local pyramidal neurons are released from their inhibition under appropriate conditions, e.g., when the column is active (1997: 124). If we look at the other activity in this column, the spiny stellate cell in the middle of layer 4C of the diagram is exciting that same pyramidal cell in layer 3B. This pyramidal cell is no longer receiving inhibitory input from the chandelier cell and is receiving excitatory input from the spiny stellate cell in 4C. Therefore, it is now able to excite a pyramidal cell in layer 2/3A and the columnar cell in layer 3B. The diagram also includes pyramidal cells in the same layer as the other pyramidal cells but in a different column (to the left). These laterally placed cells are presumed to give rise to the type of activity shown in figure 1.3. The diagram in figure 1.4 is representing the idea that the two pyramidal cells on the left and those on the right all respond to the same orientation (let s say a line at this angle: ). The pyramidal cells in the left column are exciting both the pyramidal cell and the chandelier cell in their respective layers. The excitation of the pyramidal cell causes it to fire, but the excitation of the chandelier cell causes the chandelier cell to inhibit the same pyramidal cell. Lund and her colleges (Lund and Wu 1997, Lund et al 1995) suggest that as this input from the pyramidal cell in the left hand column increases the overall effect is the inhibition of the pyramid cell (on the right) via the chandelier cell. That is, when the pyramidal cell in the left

31 Chapter 1 31 column receives strong (or optimal) stimulation the activity of pyramidal cell in the right column is suppressed. But when the pyramidal cell on the left is receiving sub-optimal stimulation (e.g., an orientation that is 45 greater than its optimal orientation), then the response of the pyramidal cell on the right is enhanced. Thus, the pyramidal cells in one column are able to suppress the activity of the pyramid cells in the same layer but a different column. However, this suppression is, graded and the result of how strong the lateral input is (Lund and Wu 1997: 124). Overall this example shows us how a series of neurons interact as inputs that began in the retina are received. This example from Lund, while it has been helpful for discussing excitatory and inhibitory projections, is a simplification of the activity at this level. In this example each cell in the diagram is presumed to represent a number of similar cell types that have similar projection patterns. And all of the projections that the actual neurons in these locations make are shown as one or two projections that represent the general pattern of projections for that population of neurons. In reality the number of connections and hence the number of interactions are often in the thousands for each neuron. To emphasize this point I want to look at an actual spiny stellate cell. In figure 1.5 is a spiny stellate cell with an axon that makes excitatory contacts on cells in layers 5, 4Cα and β, and in layers 2/3 (Yabuta and Callaway 1998). 9 And for the input that this cell receives thousands of contacts are made on its dendrites by neurons in the lateral geniculate nucleus of the thalamus and by other neurons in V1 (Beaulieu et al 1992; Peters et al 1994). 9 This axon has 2545 synaptic terminals (or buotons as they are called in figure 1.2) in layers 5, 4Cα and 4Cβ, and 1066 synaptic terminals in layers 2/3. This spiny stellate is one of the ones Yabuta and Callaway (1998) designate as lower 4Cα with narrow dendrites.

32 Chapter 1 32 Figure 1.5. A spiny stellate cell. From Yabuta and Callaway (1998). Note that the dentritic field is draw separately from the cell body and axonal arbor (the dendritic field is the much smaller clump on the left). The scale bar is 200µm. One might conclude from this description of the spiny stellate cell that a little loss of detail might be beneficial. Possibly, but this is not a question that I am going to address. Rather I want to emphasize that the sort of description that we get from Lund is a very simplified description of the entities and their interactions at this level of organization (although it does give us traction into understanding these interactions). The actual cell network level of organization is the actual causal interactions between the entities at that level. When we switch to talking about the general tendency of one population of neurons to innervate another population of neurons we are, in a certain sense abstracting away from the actual details of what occurs at this level of organization. There are numerous ways that we can speak loosely about what is, or might be, occurring at a level of organization. And the example from Lund is fairly explanatory so we can see that there can be benefits to abstracting away from the details. I will have more to say in later chapters about abstracting away from a particular level of organization. For now I just want to make the point that there is a way of talking that describes the entities and their interactions at a

33 Chapter 1 33 level of organization, and then there is also a looser way of talking that captures the sorts of things that occur at a level of organization but does not completely describe them (as in the example from Lund). Offering a less detailed description of what is occurring at a particular level of organization does not mean that we have introduced another level of organization. We are still dealing with the same level of organization because we are still talking about the same entities and the same activities, just in a different a looser way The sub-cellular level of organization I now want to move down one level to what I am calling the sub-cellular level of organization and again look at activity in V1. The entities at this level are for the most part the large molecules (enzymes, proteins, ion channels, organelles, etc.) that interact with each other within and around neurons. The exemplar that I am going to look at here is ocular dominance plasticity. This is a good example because plasticity, that is, a change to the way that neurons and their activities are organized, is one obvious reason to look at the activity at the sub-cellular level. This is to say that if we observe a significant change at the cell network level, then we are inclined to look to the sub-cellular level and the processes that are occurring there in order to understand what drives the change. There are other reasons to examine the activity at the subcellular level, for instance, we might want a clearer understanding of how excitatory input causes a cell to respond and under what conditions it does. However, plasticity is one good reason to be interested in this level of organization. Starting our explanation at the cell network level, ocular dominance plasticity is the process whereby depriving one eye of input for a period (e.g., by sewing it closed, or having a cataract) causes the cells in V1, which normally are organized into ocular dominance columns, to

34 Chapter 1 34 shift to responding predominantly to the non-deprived (open) eye. Ocular dominance columns do not exist at birth. In the monkey for instance, at birth the axons that enter layer 4C from the LGN branch over a large area and there is little or no segregation between the inputs from each eye (Hubel and Wiesel 1977: 51). During early development the axon branches become smaller, more focused, and organize into the ocular dominance columns. It also appears that these geniculate-cortical axonal branches become denser in this narrower area that they occupy. However, if one eye is deprived of stimulation during the critical period after birth the axons entering V1 (in layer 4C) that serve the deprived eye become greatly reduced while the axons serving the non-deprived eye expand. 10 Deprivation is effective in causing these changes in as little as a week. The result is that the cells in V1 respond predominantly to the eye that was not deprived. Whereas if the deprivation had not occurred the columnar organization would have developed, the deprivation causes almost all of the cells in V1 to become innervated by the nondeprived eye (and, consequently, the deprived eye to lose almost all of the cortical territory that it would have innervated in V1). This change this plasticity is therefore a result of how stimulation of the eyes is manipulated. 10 This plasticity occurs, under the right conditions, during a window, the critical period, between birth and puberty. The length of this critical period differs among species. In the human it lasts until age seven (Berardi et al, 2000). In the monkey it is competed twelve weeks after birth (Berardi et al, 2000). In the cat it does not begin until the eyes open two weeks after birth, and extends past week ten (Antonini and Stryker, 1993b: 3549). And in mice it lasts until the mouse is about 32 days old (Gordon and Stryker, 1996). The length of time that one eye must be occluded for the full ocular dominance shift to occur likewise differs among species, and is relative to the length of the critical period.

35 Chapter 1 35 Figure 1.6. The figure on the left shows axons, deprived and non-deprived, from kittens that had one eye deprived for one week beginning at five weeks after birth. 'ND' are axons serving the non-deprived eye, 'D' are axons serving the deprived eye. The figure on the right shows axons from kittens that had one eye sewn shut from before eye opening to age 39 days. Note that the non-deprived axons in the long-term monocular deprivation have branches that are dense, widespread, and not restricted to 0.4 mm columns. From Antonini and Stryker (1993a: 1819). The figure above shows the axons of cells in the LGN that innervate cells in layer 4C of V1. The dramatic changes in these genticulate-cortical axon branches in layer 4C are the end result of this plasticity. Prior to the changes that occur in layer 4C are the loss of the spines that form on the dendrites (and are sites of synaptic contact) in other layers. The loss of dendritic spines on the pyramidal cells in layers 2/3 (Mataga et al, 2004) and 5 (Oray et al, 2004) of V1 is the first change in this form of plasticity, occurring after brief (2 4 days) monocular deprivation during the critical period in mice. So the basic outline of this plasticity process is: first there is a change in visual experience, this then causes changes in the synaptic connections outside of layer 4C (i.e., the loss of spines), which in turn drives significant changes to the axons that enter V1 (in 4C).

36 Chapter 1 36 In the rest of this section I will review some of the sub-cellular activities that lead to the spine loss outside of layer 4C. The beginning of this process, from calcium influx to gene expression is sketched out in the figure below. extracellular Ca 2+ influx NMDA receptor calmodulin CaMKII cytoplasm nucleus CREB CRE gene expression Figure 1.7. A sketch of the intracellular cascade that begins with calcium ions entering the cell and eventually leads to gene expression. CaMKII: Calcium-calmodulin kinase II. When a pre-synaptic neuron releases the neurotransmitter glutamate it binds to receptors in the post-synaptic membrane. This allows positively charged sodium ions (Na + ) to enter the cell. If enough Na + enters (if there is a strong enough depolarization) the Mg 2+ ion that is blocking the NMDA receptor is removed. Removal of the magnesium blockade allows an influx of Ca 2+ through the NMDA receptor (Taha and Stryker 2005a: 104). 11 The influx of Ca 2+ then begins intercellular processing The first important component in ocular dominance plasticity, once the stimulation the eyes receive is altered, is the disruption of the balance between inhibitory and excitatory activity. This inhibitory input is not merely a (direct) consequence of the altered sensory input (from the eyes) to V1. It also seems to be a feature of the critical period during which plasticity can occur. However, it is not entirely clear what the exact balance is between excitatory and inhibitory input that is required for ocular dominance plasticity. The inhibitory neurotransmitter γ-aminobutyric acid (GABA) provides the inhibitory input. And the GABA A receptors containing the α1 subunit, which are found on the soma of pyramidal cells where

37 Chapter 1 37 The influx of calcium allows calcium-calmodulin kinase II (CaMKII), a protein which has been shown to be important for this form of plasticity, to become active (Taha and Stryker, 2005b; Gordon et al, 1996; and Taha et al, 2002). 13 Once a sufficient amount of calcium enters the neuron it can bind to the protein calmodulin, thereby changing the conformation of this protein. The Ca 2+ /calmodulin complex then binds to CaMKII, activating the CaMKII. Once activated CaMKII can autophosphorylate, which allows it to remain in its active state once the calcium influx has ended. 14 The active CaMKII can then phosphorylate the protein cyclic AMP response element binding protein (CREB, [Pham et al, 1999]). 15 synapses are made with large basket cells, also appear to have a role here. The basic idea is that the correct balance of excitatory and inhibitory activity allows plasticity to proceed. When mice are genetically manipulated so that they produce significantly less of the inhibitory neurotransmitter GABA (GAD65 KO mice glutamic acid decarboxylase 65-kD is one of two enzymes that synthesizes the neurotransmitter GABA) these mice fail to exhibit this ocular dominance shift after one eye is occluded. 12 Experiments by Roberts et al (1998), demonstrated that the NMDA receptor is involved in ocular dominance plasticity. She and her colleagues demonstrated this by using antisense oligonucleotides to reduce expression of the NMDAR1 subunit of the NMDA receptor (an antisense oligodeoxynucleotide is an engineered string of nucleotides that when injected binds to a particular sequence of a strand of DNA, which then effectively silences the gene). This technique blocks the NMDA receptor activity, without disrupting general visual activity, and it prevents ocular dominance plasticity. 13 Other enzymes, notably protein kinase A (PKA) (Beaver et al, 2001), and extracellular signal-regulated kinase (ERK) (Di Cristo et al, 2001) have also been shown to have a role in ocular dominance plasticity. This suggests that there may be several, perhaps interrelated or overlapping, intracellular cascades that contribute to ocular dominance plasticity. 14 That the autophosphorylation of αcamkii is critical for rapid ocular dominance plasticity was shown by Sharif Taha and Michael Stryker (2002). They genetically modified mice so that the amino acid alanine was substituted for threonine (at position 286), which makes αcamkii unable to autophosphorylate. In mice with this genetic modification ocular dominance was significantly impaired as compared to wild-type mice. This study was followed by another (Taha and Stryker, 2005b) testing the effects of longer periods of monocular deprivation (10-26 days) on mice in which αcamkii could not autophosphorylate. They found that there was plasticity in these mice (indistinguishable from wild-type), perhaps driven by αcamkii activity that was dependent on Ca 2+ /calmodulin, or another kinase-dependent cascade (Taha and Stryker, 2005b: 16441). 15 That CaMKII is necessary for ocular dominance seems clear, but its exact role is less clear. Stryker (Taha and Stryker 2005a) and Hensch (2004, 2005) both suggest that it is part of the cascade that begins with calcium influx and leads to CREB activation. CaMKII s role in CREB activation is however,

38 Chapter 1 38 CREB is a transcription factor that binds to the camp response element (CRE) sequence of DNA, and so if it is activated it promotes the synthesis (transcription) of RNA from a strand of DNA (Nestler and Greengard, 1999: 490 2). 16 Once active CREB regulates the expression of numerous genes (i.e., different genes that all contain the CRE sequence for CREB to bind to), one of which is brain-derived neurotrophic factor (BDNF [Pham et al 1999]). BDNF has been shown, in vitro, to stimulate the expression of tissue plasminogen activator (i.e., the expression of tpa mrna), as well as its release from neurons into the extracellular space (Fiumelli et al 1999). Tissue plasminogen activator (tpa) is a protease that when released from a cell causes the conversion of plaminogen into plasmin. Plasmin is an enzyme that participates in proteolysis, the breakdown of proteins. Although, it is not known if in this particular process tpa is directly participating in the proteolysis, or if its role is to catalyze the plasminogen (Berardi et al, 2004: 906). 17 Mataga et al (2004) suggest the process that is illustrated in the figure below, as the way somewhat complicated. CaMKII can, like CaMKIV (and PKA and ERK), phosphorylate CREB on serine 133, making CREB active. However, CaMKII also phosphorylates CREB on serine 142, which appears to disactivate CREB (Sun et al 1994). But as a reminder, I am here only trying to illustrate the sort of entities and their activity that are found at the sub-cellular level. 16 CREB has been shown to be required for ocular dominance plasticity by Tony Pham and his colleagues (Pham et al, 1999) who found that it is upregulated in mice that are monocularly deprived, but not in mice that are binocularly deprived or in mice that do not experience deprivation. And in another study Mower et al (2002) were able to suppress CREB activity in ferrets using a virus that caused a dominant negative form of CREB (which could not become active) to be expressed in V1. This manipulation prevented ocular dominance from occurring. 17 Returning to the cell-network level, Mataga et al (2004) imaged the dendrites of pyramidal cells in layers 2/3 of V1, which had been labeled with lipophilic dye, and found that the number of protrusions increased steadily during development (from 9 days after birth eyes still closed, to 66 days old adult) in normal (wt) mice. Monocular deprivation for four days during the critical period significantly reduced the number of protrusions as compared to non-deprived mice of the same age (and monocular deprivation of adult mice showed no effect on the number of protrusions).

39 Chapter 1 39 in which the monocular deprivation induced release of tpa causes the degeneration and eventual removal of the spines from pyramidal cells. Figure 1.8. In all three diagrams the presynaptic terminal is the shape at the top of the diagram and the dendritic spine is below it. See text for further explanation. From Mataga et al (2004). The area around the synapse (outside the cells) is composed of an extracellular matrix of proteins, as well as cell adhesion proteins that attach to the presynaptic terminal and the postsynaptic dendritic spine. The tpa (or plasmin) in the area of the synapse (the pac-man shapes) breaks down some of the proteins that compose the extracellular matrix (laminin and phophacan these are represented by the gray background that is fading from A to B to C), and the neuronal cell adhesion molecules (yellow bars). This begins the process of spine loss. These extracellular events may then be followed by signaling from the soma of the postsynaptic cell (e.g., by serum-inducible kinase, SNK) that causes spine removal.

40 Chapter 1 40 In contrast to this activity that is downstream of the deprived eye, the extracellular matrix around the synapses that are driven by the non-deprived eye are not affected, although they are also exposed to tpa. One reason for this may be that tpa is inhibited by one or both of two protease inhibitors: neuroserpin and nexin-1 (the green triangles in the figure), which are released at active synapses along with tpa. Another possibility is that adhesion molecules that are not sensitive to tpa: N-cadherin and β-catenin (green bars), protect the active synapses from the tpa activity. This tpa activity the breakdown of the extracellular matrix occurs in layers 2/3 of V1. It is not known how this activity connects with the changes that occur in layer 4. And I have not talked at all about the positive changes that occur during this shift in ocular dominance. This is also not well understood, although it is presumed that BDNF has a role in driving the growth of new axonal branches that serve the non-deprived eye (Hensch 2005, Taha and Stryker 2005a). This is a summary account of some of the entities that are found at the sub-cellular level of organization and the activities that they participate in during the occurrence of this type of plasticity. Although I have given somewhat more detail about tpa and its activities, even that was less than a complete description of the entities and their behavior at this level. For instance, obviously tpa are not little pac men chomping their way through protein in the intracellular matrix. A more detailed picture of the entities and their activity would look more like what is shown in the diagram below illustrating calmodulin binding to the regulatory domain of the alpha subunit of calcium/calmodulin-dependent protein kinase II (αcamkii). This binding relieves the autoinhibition of that subunit of the CaMKII, which in turn sets in motion a series of event that make the CaMKII active and hence able to phosphorylate the proteins that it targets.

41 Chapter 1 41 Figure 1.9. From Vetter and Leclerc (2003: 406). This is one way of representing macro-molecules. The ribbon shapes represent the secondary structure of these proteins. The blue ribbon is calmodulin (the yellow spheres are the calcium ions), and the red ribbon is the calmodulin binding site of the α form of the CaMKII. The point is to be clear about the range of ways of talking about what is occurring at the level of organization. It is often the case that these activities are discussed not in the context of a discussion of levels of organization, but in the context of trying to understand an extended process that is incompletely understood. Hence, it is not always important to be explicit about how calmodulin binds to CaMKII (which is well understood) or whether tpa acts directly on the extracellular matrix molecules or via plasminogen activation (which is not yet known, so being explicit is not an option). Nevertheless, as I said in the previous section, whether we are being explicit about them or not, the actual activities remain the same and an explicit description of them is what constitutes a description of a level of organization. All other talk is a looser, although perhaps still informative, description of the activity at the particular level of organization.

42 Chapter The chemical level of organization One level of organization that is below the sub-cellular level is what can be called the chemical (or biophysical) level of organization. At this level the entities are atoms (chemical elements) and their interactions are such things as: the chemical bonds that form between atoms whether these are covalent bonds or the weaker ion-ion, hydrogen, or dipole-dipole bonds; non-bonding interactions between atoms, and the interactions between atoms and the solvent that they are in (van Holde et al 1998: 10 11, 95 8). One question, however, is whether there is a level between this chemical level and the sub-cellular level. The obvious candidate for an intermediate level would, I believe, be a level occupied by entities such as amino acids, sugars, and lipids. These are entities and they do have interactions. However, the issue here is whether these interactions are actually different in type than the interactions at the lower, chemical, level. An example that can help to address this issue is shown in the figure below. H H C C H C C O N H H N N H C C N C C N N C C N O Thymine Adenine Figure Adapted from van Holde et al (1998: 55). Except for the hydrogen bonds that are represented as dotted lines, the different types of bonds are not represented. The filled circles are where the nitrogen atoms bond to the deoxyribose.

43 Chapter 1 43 Illustrated here are two of the bases, thymine and adenine, that compose deoxyribonucleic acid (DNA). Now there certainly is a way of talking where we say that these two bases interact, that is, they bind together. I am not interested in critiquing that way of talking. All that I want to clarify, for the purposes of constructing a hierarchy of levels of organization, is whether or not there is one interaction that the bases have and a different interaction that atoms have. It seems to me that there is only one type of interaction here. And furthermore that type of interaction, the bonds that form between atoms, occurs at this chemical level of organization. 18 Therefore, the consequence of this is that although these bases, amino acids, sugars, and so on are entities, because they do not have unique interactions they do not have their own level of organization when levels of organization are based upon interactions among entities Higher levels The three levels of organization that I have just discussed, the cell network level, subcellular level, and the chemical level qualify in a straightforward way as levels of organization. The entities are identifiable and the interactions that these entities have with each other are, if not 18 One other possibility is that although the same term, bonding, is being used when talking about amino acids and when talking about atoms the term has a somewhat different meaning in each case. I am not sure and I am going to put this possibility aside. 19 One objection here may be that the difference in strength between hydrogen bonds and covalent bonds indicates that they are should be at different levels. After all the strength of the interactions here are markedly different. I prefer to think that both of these interactions (hydrogen bonds and covalent bonds) occur at the same level of organization. They are just different interactions that occur at the same level. And this type of objection I address in the last section of this chapter. On this particular point however, I will say that although hydrogen bonds and covalent bonds differ in their strength, each is not a type of interaction that occurs between different sorts of entities. There are differences, but it is not the case (for instance) that we can look at one type of bond as occurring between atoms and the other type as occurring between amino acids, which is the important point for this section.

44 Chapter 1 44 easy to discover, still easy to describe once they have been determined. I am not convinced that there are higher levels within the brain (i.e., below the level of the whole brain) that have these features. If we look at some of the entities that have been mentioned while discussing the early part of the visual process we have: the lateral geniculate nucleus, the primary visual cortex (V1), V2, and so on. We might intuitively think that these entities these brain areas constitute a level. However, when we look at these entities, it is difficult to say what sorts of interactions they participate in, which of course is required if we are to establish that this is a level of organization. If we take the LGN and V1, the two structures do not touch each other, and merely saying that they are connected by axons is not an option since axons occur at the cell network level of organization. The most plausible suggestion that can be made here, I think, is that they interact by way of axon tracks or axon bundles. That is, structures like the optic track or optic radiations, which are bundles of axons that all have their cell bodies in the same place (in this case in the retina, and in the LGN) and that all terminate in the same general place. In order to make this move I think that there has to be at least some minimal justification for understanding these axon bundles as different than just the axons that are found at the cell network level of organization. One justification is that, at least in some cases, an axon track is a visible entity. The optic nerve for instance can be seen with the naked eye (when the brain is removed from the skull). And presumably there is at least an intuitive desire to call something that we can see and touch, and distinguish from other things an entity. So this is perhaps one reason to say that the optic radiations are what connect the lateral geniculate nucleus and primary visual cortex. But, on the

45 Chapter 1 45 face of it all that introducing optic radiations does is give us another entity. What sort of interactions these entities have is another question that still has not been answered. 20 So, it is still not clear how we might describe, at this brain areas level, the interactions that are supposed to occur between the LGN and V1. As a contrast we can look at a magnocellular neuron in the lateral geniculate nucleus that sends its axon into V1 where it synapses on spiny stellate cells that are in layer 4Cα. This magnocellular neuron interacts with the spiny stellate cells by way of an excitatory impulse, which under the right conditions will contribute to the spiny stellate cells generating an action potential and themselves exciting other neurons. In this case we have the type of activity that neurons engage in: generating action potentials, and we have a description of the interactions between neurons that drive this type of activity: multiple neurons concurrently releasing excitatory neurotransmitter onto the spiny stellate cell can drive that cell to threshold such that it will generate the action potential. In the case of the interaction between the LGN and V1 it is not obvious that we can describe the interactions in as straightforward a manner. We could say that there are additive effects of these neurons in the LGN exciting cells in V1, however, it does not really seem to be the case that the effects are exactly what we would call additive. 21 In the case of this vision example when we are looking at the activity of neurons and their interactions (at the cell network 20 It can be noted that in this discussion I am not pressing Wimsatt s criteria very hard i.e., the issue is not one of where the most significant interactions are found, or where the most regular interactions are found. Rather it is more simply just a question of whether there are any interactions among these brain areas at all. 21 Recall that in the discussion of the cell-network level of organization I pointed out that there are looser ways of talking about what is occurring at a level of organization, namely describing the tendency for cells in one area to transmit to cells in another area. This is in contrast to an actual description of the activity at this level of organization which is of the specific entities and their activities. This looser way of talking about what is occurring at the cell-network level of organization is not a higher level of organization. To move to the higher level of organization we need different entities.

46 Chapter 1 46 level) we can investigate the processing of orientation, motion, color and so on. However, when we move to talking about brain areas, if we merely add up the activity of the neurons, then we lose the focus on the perception of these different features. Possibly we could say something such as: there is a flow of visual information from the lateral geniculate nucleus to V1, but it is not clear what this visual information is. It is wrong to say that the visual scene (out in the world) is simply encoded as a whole and transferred from the LGN to V1. But when we are more specific about what sort of information is being transferred, then we are again talking about the activities that occur at the cell network level not among brain areas. Therefore, I am taking the position that brain areas do not constitute a level of organization. I will however, investigate this at more length in the next chapter with some of the cases that Patricia Churchland (1986) offers. The difficulty that there is in putting together support for this brain areas level of organization suggests, rather convincingly, that there are not any levels of organization that are even higher, but below the level of the whole brain, for example, a level where brain lobes interact. As a reminder this entire discussion is about levels of organization where a level is occupied by particular entities interacting in predictable ways. Levels based on something else, for instance composition, give us a way of ordering higher level entities such as the thalamus or the occipital lobe of the cortex. But when focusing on levels of organization in the way that Wimsatt defines level of organization these sorts of entities (thalamus, occipital lobe of the cortex, etc.) do not have a place they may very well be used to reference where some interaction is occurring or where some entity is located, but they are not themselves entities that participate in the sorts of interactions that constitute a level of organization.

47 Chapter 1 47 In the next section I will consider some objections, but first I want to reiterate where we stand. I have suggested that there are three levels of organization that fall within the scope of the brain: the cell network level, the sub-cellular level, and the chemical level. There is no way, which I know of, to prove that there are only these three levels of organization within the scope of the brain. All that can be done is to examine other potential candidates. This I have done for brain areas and I will look at more cases in the next chapter. 1.4 Objections Now that I have discussed the different levels of organization that fall within the scope of neurobiology I want to address a few potential objections to the idea that a level of organization is identified by stable and regular interactions and to the hierarchy that I have developed. I take these entities and their activities to be real, in the sense that they exist in nature and I do not take myself to be imposing an artificial organizational scheme on them. However, I also recognize that when trying to organize them there may be gray areas, as well as areas where some may disagree about how to conceive of a particular type of interaction or what counts as an entity. Although I said that I am taking a (more or less) realist stance with respect to these levels of organization, my aim here is not to organize the furniture of nature. Rather, it is to set up a scheme that can be useful for thinking about how psychology and neurobiology are related. To that end, the hierarchy of levels of organization that I have offered is laid out for that purpose and so ultimately it is just meant to be a useful tool for getting some traction into that relationship. There are however, three issues that I want to address (1) First, how do we know when some interaction should be explained at one level rather than another? For instance, the excitatory interactions between neurons, and the subsequent

48 Chapter 1 48 generation of an action potential can be described at the cell network level, but a series of interactions that occur at the sub-cellular level of organization can explain the same events. 22 However, while it seems clear that the event can be understood at both levels, there do seem to be reasons to select one level over another. To back up a bit, when establishing levels of organization there are two ways in which we can proceed. We can look at the entities that are studied by neurobiology and then determine if each class of entities participates in specific interactions. When we do this we find that neurons participate in specific interactions, as do the macromolecules that are found in the brain. Brain areas, however, although they are entities, do not participate in specific interactions. Conversely, we can proceed by looking for the interactions first. For instance we can look at the process by which ocular dominance plasticity occurs, or a process such as the one Lund describes in V1. If we are successful these two approaches should coincide, and we will have identified some specific levels of organization. Returning to the question of how to decide the level at which an interaction should be described, these two cases indicate that the problem is solved for us if we just allow the descriptions of the entities and the interactions to, in a sense, take their natural course. Or more specifically, if we just follow the way in which the scientists describe these interactions, then the level at which an interaction should be described is answered for us. Therefore, in the case of the excitatory interactions, when we find that there are times when we want to describe excitatory 22 For instance, at the sub-cellular level the generation of the action potential is explained as the binding of the neurotransmitter to receptors in the membrane of the postsynaptic neuron. This either directly or indirectly causes ion channels to open, allowing positively charged ions that the channel is selective for to enter. This influx of positively charged ions spreads down the dendrite to the base of the axon where there are voltage gated channels. When the voltage gated channels are opened this is usually sufficient to drive the membrane potential to threshold. This at the cell network level is the generation of an action potential.

49 Chapter 1 49 interactions among neurons (as Lund does), then we utilize the cell network level. On the other hand, if we want more detail concerning how the interactions occur, then the activity at the subcellular level must be investigated. The gain in choosing the lower level is a more complete understanding of what the event in this case excitatory transmission entails. The cost, however, in choosing the lower level is the added complexity of grasping a large series of these events (excitatory transmissions) and the downstream effects that a large number of excitatory transmissions will have. A second answer expands upon this. In a case like the example that I used from Lund of the different responses of a neuron to only slightly different stimuli, there is a clear sense in which this activity is tracked more easily at the cell network level and not at the sub-cellular level. And not only is it tracked more easily there, but there is no gain in our understanding of the case by investigating the activity at the sub-cellular level rather than at the cell-network level (so far as I know). Given that it is most easily tracked at the cell-network level and there is no advantage to investigating the activities at the sub-cellular level, this makes the cell network level the natural level at which to explain these activities. And likewise for other levels; it seems reasonable to say that as long as we are not losing any (needed) content in the description of an activity, then the level at which the activity is most easily described should be the one that should be selected. 23 (2) A second issue is that there do appear to be some genuinely gray areas. We saw one of these in the section on the sub-cellular level, namely the interaction between calcium ions and the protein calmodulin. I would normally take these two entities to be at different levels of 23 Note that this discussion about the level at which an activity should be described, is not the same as the discussion concerning the status of brain areas and whether or not they occupy a level at all.

50 Chapter 1 50 organization, but in a straightforward way of talking about them they do appear to interact: calcium binds to calmodulin, thus changing the calmodulin s conformation. The case could perhaps be manipulated so that it would fit better with my notion of levels of organization. For example, we might say something like this: when calmodulin s environment changes from a free Ca 2+ concentration of ~10 7 moles to a concentration of ~10 5 moles the calmodulin becomes active (Cates et al 2002). 24 This is a legitimate way of talking about the activities of calmodulin. However, it seems more straightforward just to say that calcium ions and calmodulin do interact and this particular case does not fit as neatly into a level of organization as most other cases. (3) The last issue that I want to address concerns what might be called the breadth of a level of organization. As I have said a level of organization is defined by interactions among entities, but it is important to understand that a level of organization includes all of the entities of that type, whether they directly interact or not. The interactions among neurons in the lateral geniculate nucleus and the primary visual cortex (V1), acceptably, constitute a single level since they interact and have a role in the visual process. However, as we increase the breadth of the interactions that we are looking at, for example, from neuronal activity dedicated to vision to neuronal activity dedicated to memory or emotion, we remain at the same level of organization. Dividing up the behavior of neurons into activities dedicated to what we consider different capacities is not an issue that directly pertains to establishing the levels of organization themselves. Rather this is an issue for scientists engaged in investigating those processes. 24 This is basically the way in which Cates et al do describe it in one place: Eukaryotic intracellular resting levels of free Ca 2+ are maintained at a concentration of ~10-7 M via membrane-bound Ca 2+ -ATP pumps. Ca 2+ influx responses increase the cytosolic Ca 2+ concentration to ~10-5 M as a result of a specific signal stimulus, as in neuron stimulation of muscle cells or hormonal stimulation of a cell through the binding of specific receptors. Regulatory Ca 2+ -binding proteins that direct physiological processes through Ca 2+ -induced conformational changes have been designed by nature such that their Ca 2+ affinity is sufficient to bind Ca 2+ during an influx, but not at resting levels (2002: 1133).

51 Chapter 1 51 Determining what counts as a level of organization only concerns identifying regular and predictable interactions among entities. An objection that might be made here is that a level of organization should be limited to a restricted series of interactions. The force of this objection comes from the idea that the sorts of interactions that are occurring do distinguish one capacity from another (and sub-capacities from each another). The interactions between entities engaged in one process are going to be more regular (or cohere more strongly) than interactions between different processes. 25 So the objection is that there are some interactions that are very significant and very regular. And since we distinguish between different processes based upon the strength of these interactions, we should therefore distinguish levels of organization in the same way. In response to this objection I, first, want to say that we have to think of interaction in general terms. With levels of organization what we want to identify are types of interactions and types of activities that are consistently found among certain kinds of entities. 26 Once we have done this we have identified a level of organization. In instances where we cannot identify interactions, for example between brain areas, we do not have a level of organization. In the cases where we have identified a level of organization, then we (subsequently) make more 25 For example, M cells in the LGN more commonly synapse on (and excite) cells in layer 4Cα, than on cells in other layers, or cells in one ocular dominance column have stronger interactions with neurons in the LGN driven by one eye rather than the other. 26 The conditions are probably easier to talk about at the level of individuals. At this level we might find a case such as: mother-child interactions are generally going to be more regular than father-child interactions. Although the strength of the interactions here might be significantly different there are general background conditions that help us identify a level of organization that includes the mother, father, and the child (as well as all other individuals). These background conditions might be specified as something like: humans have the sort of visual system that is useful for identifying other entities over a specific range (i.e., not too small or too large), and humans have the sort of skeletal and muscular composition to physically interact with other entities over a specific range of sizes.

52 Chapter 1 52 distinctions, essentially distinguishing different types of processes from each other (e.g., memory and vision, or different aspects of the visual process from each other). These distinctions will be made based on the interactions that are found, but since the level of organization has already been established, the distinctions between different capacities are made at the same level. Making these distinctions is a significant task, but not one that affects the status of a level of organization. Furthermore, when we look at what Wimsatt says he seems to me to waver on this point. The way in which he generates his account of levels of organization does not seem to suggest that levels of organization are restricted sets of interactions. Recall that he begins with size as the initial indicator of levels. Although this is not his final answer, at this point in this argument all entities of roughly the same size are at the same level, and there is no restriction on the breadth of the level. From there he develops the idea that entities are found at those sizes because they are the places of greatest regularity and predictability (1976: 239). That is to say, there are conditions that make those sizes the most likely ones. The conditions that are in place are what generate the levels of organization. But the levels of organization that he has determined based upon size have not changed or at least they have not changed radically. From this I take it that a level of organization is generated by the background conditions that are in place and which at least in part insure the stability of the interactions. And whatever further conditions make some interactions stronger or more regular are subsequent and do not affect the status of the level of organization. On this line of thought Wimsatt agrees with the broad view of levels of organization that I am using.

53 Chapter 1 53 On the other hand Wimsatt does say after he has introduced his account: In picking out a level of organization (which we generally do by naming a few characteristic entities and interrelations) we are doing so on the basis of something like a gestalt a recognition that these entities and these relations hang together more strongly with one another (in terms of frequency and density of connection) than they do with other units and relations (1976: 242). This passage seems to suggest that a restricted series of interactions will constitute a level of organization. A set of entities that appear to participate in a cohesive series of interactions constitute a level and entities that do not directly participate in this series of interactions are not at this level. However, I am not going to debate the point about whether or not this should be Wimsatt s position. I think that it is possible that he does agree with my position. But in any case the alternative raises some problems, which is why I think it is not the correct position to hold. The consequence of thinking that a level of organization is constituted by a restricted set of interactions is that interactions that extend beyond that series will not be part of the same level of organization. This leaves us with two options. We can say that there are interactions between levels, or we can say that each of these restricted series of interactions constitutes an entity at a higher level and at that higher level these entities interact. We can look at these options with a simple example: a 1 interacts with a 2, a 2 interacts with a 3, and a 3 interacts with a 4. And let us say that the interactions between a 1 and a 2, and between a 3 and a 4 are both extremely regular, while the interactions between a 2 and a 3 are somewhat less regular. We can represent this scenario as such: a 1 a 2 a 3 a 4 The first option, interaction between levels, will lead us to say that the interaction between a 1 and a 2 constitute one level of organization, and the interaction between a 3 and a 4

54 Chapter 1 54 constitute another level of organization. We will then have interactions between levels when we want to talk about the interactions between a 2 and a 3. This option is not very appealing because what we are looking for from a series of levels of organization is a way of ordering levels hierarchically. When we add interactions between levels then we are adding another dimension to our task a dimension that we were looking to avoid. Of course regardless of whether we consider this an interaction between levels or not we are interested in the interaction. The question is whether or not the issue should be cast in terms of an interaction that occurs at a level, or an interaction that occurs between levels. It seems reasonable to reduce the complexity of how we conceptualize levels of organization and say that a 1, a 2, a 3, and a 4 are all at the same level of organization. Then we can address the particular interactions between a 1, a 2, a 3, and a 4 separately. The second option, suggesting that each of these restricted series of interactions constitutes a higher level entity, presents us with this picture of levels (where the boxes represent entities): level 2: a 1 & a 2 interacts with a 3 & a 4 level 1: a 1 interacts with a 2 The consequence of this picture is that the interaction between a 2 and a 3, which was considered relatively weak at level 1, is the interaction that occurs between the entities at level 2. It seems odd to me that what is considered a relatively weak interaction at one level would be, at a higher level, the interaction that establishes the level of organization. However, the main issue that this example highlights is that the type of interaction between the entities at level 2 is the same type of interaction that occurs at level 1; it is just slightly less regular than the other interactions at

55 Chapter 1 55 level It seems that if we are focused on interactions as the defining feature of a level of organization, then we are not justified in introducing a higher level based on this type of scenario, but rather ought to say that a 1, a 2, a 3, and a 4 are all at the same level of organization. All of this having been said, although it is the case that some interactions are going to be more regular than others, I am using a more general standard of interaction to identify a level of organization, namely, the types of interactions, whether that is the interactions that neurons have, the interactions that proteins and enzymes have, or the interactions that atoms have. These types of regular and stable interactions identify a level of organization, not the specific interactions which will naturally vary from case to case. 27 This also raises a related issue. In the example that I used to illustrate the activities that occur at the sub-cellular level, ocular dominance plasticity, the entities participate in a series of interactions that is fairly stable, but we are not tempted to say that they collectively are an entity at a higher level.

56 Chapter A Critique of Churchland In the previous chapter I laid out three levels of organization that fall within the scope of the brain: the cell network level, the sub-cellular level and the chemical level. In this chapter I contrast my hierarchy of levels of organization with one that is offered by Patricia Churchland (1986; see also Churchland and Sejnowski 1988, 1990). The structure of this chapter is a critique of each of the levels in Churchland s hierarchy. Doing this also provides the opportunity to examine a number of different phenomena that have been studied by neurobiologists and to look at how they are handled by my hierarchy of levels of organization. 2.1 Churchland s analysis of levels In this section I discuss three issues that concern Churchland s analysis: (1) how she determines what the levels are, (2) the role that empirical data has when establishing a hierarchy of levels, and (3) some concerns that can be raised about having too many levels in the hierarchy. Churchland has, in different places, suggested the hierarchies of levels that are listed in table 2.1. And in her book Neurophilosophy she offers a number of scientific studies that she takes to be exemplars of different levels of organization (1986: ). This chapter focuses on these different neurobiological investigations. I have chosen to look at them rather carefully because it is a straightforward and fairly tractable set of examples that illustrate the hierarchies that are listed in table 2.1.

57 Chapter 2 57 Churchland (1986: 359) Churchland and Sejnowski Churchland and Sejnowski first approximation second approximation (1988: 742) (1990: 369) CNS CNS behavior systems brain maps circuit metamodules maps brain systems cell assembly modules layers brains subsystems synapse networks circuit cell neurons neurons single cell membrane synapses membrane molecules biochemical Table 2.1. Different hierarchies of levels of organization proposed by Churchland. Although Churchland refers to the hierarchies in table 2.1 as levels of organization, she does not offer much analysis of what levels of organization are, and, as the chart above demonstrates, she has at different times indicated that different levels of organization fall within the scope of the brain. One of the techniques that she uses for establishing a hierarchy of levels of organization is identifying important structures that can be ordered based upon their size (1986: 359; Churchland and Sejnowski 1988: 742; Churchland and Sejnowski 1992: 19). For instance, in the list on the far right in table 2.1, the cell membrane is one type of structure, the single cell is a structure found one level above that, the cell assembly is a structure one level above that, and so on. But this is not the only way in which she identifies levels of organization. An alternative is as she says, another preliminary and related way to demarcate a level is to characterize it in terms of the research methods used (1986: 359). Regarding the first option (i.e., structure), this is similar, if not the same as, using composition as the defining feature of levels of organization. The problem that I found in chapter one with using composition instead of interaction as the defining feature of levels of organization is that every structure that can be identified does not participate in a process; that is, every structure does not have a specific interaction with other structures (or entities). In any case, some

58 Chapter 2 58 of Churchland s examples in this chapter will provide opportunities to examine problems with thinking of levels of organization primarily in terms of structure. With respect to the second option: looking at research methods, this, in practice, might be a reasonable way to identify levels of organization. If different methods happen to focus on different levels of organization, then this heuristic works. However, if different techniques are used to investigate the same entities and their activities (or vice versa), then research methods are an imperfect indicator of the level of organization. This is also an issue that I will be able to elaborate upon in this chapter when looking at Churchland s examples. Another aspect of Churchland s view of levels of organization is that talking about what counts as a level of organization and how different levels of organization should be divided up is an empirical matter. She writes, How many levels there are, and how they should be described, is not something to be decided in advance of empirical theory. Pretheoretically, we have only rough and ready and eminently revisable hunches about what constitutes a level of organization (1986: 359). To a certain extent I agree with the sentiment that she expresses here. Levels of organization are a way of categorizing nature, and so the inquiries into nature that are made by science should be carefully noted. And I relied upon empirical work when constructing my own hierarchy of levels of organization in chapter one. However, there are a number of reasons why we should expect that an account of levels of organization requires stepping back from the empirical data for the purpose of offering a meta-analysis. One straightforward reason is that there are different uses of the term levels that are not related. 1 Also, as I said in chapter one, there are at least two different 1 Besides levels of organization, there are also levels of explanation (Marr 1982), which I will discuss in the next chapter. Levels of processing also seems to me to be a way of using levels that is distinct from organization and explanation. Then there are also variants of these, or these same ones used by different

59 Chapter 2 59 ways that a hierarchy of levels of organization can be constructed (using interaction and using composition). But besides these reasons, which are relatively easy to specify, there are more general worries about relying too heavily on empirical studies when constructing a hierarchy of levels of organization: the wide range of techniques used in the brain sciences, the enormous number of empirical studies done every year, the tendency for researchers to work at more than one level, and the continuously developing picture about how the brain works. For example, there could be a case where a researcher is looking for some indication that an entity has certain features (say the conditions under which a neuron will respond), but he is using tools with poor resolution. Because the researcher is not able to look very closely at the feature being studied (maybe he is only able to record the activity of a large number of neurons) there is a tendency to think that his efforts are pitched at a rather high level. However, the exact same feature the conditions under which a neuron will respond could be looked at (maybe several years later) with more precise tools and a clearer idea of which specific cells might respond under the given conditions. And although the research methods and what Churchland calls the grain of these two studies are certainly different, the level of organization that they are investigating is the same, that is, the entities and their activities are the same. Ignorance or vagueness can also be a factor when scientists report on their attempts to try to gain access to entities and the entities interactions. At a given point in time researchers just may not know what it is that they are looking for or where to find it. However, if a level of organization is defined by stable interactions between entities, then vagueness cannot be an names (e.g., Lycan s [1981, 1987] levels of nature is not very thoroughly defined but seems to be more or less like levels of organization).

60 Chapter 2 60 aspect of what determines a level of organization although it may be necessary to accept that it is not entirely clear what level of organization a study is trying to gain access to at a particular point in time. As a consequence we cannot just take different empirical results, order them into a hierarchy of levels, and expect that hierarchy to reflect anything precise about nature. Precision is necessary, although difficult, because of the larger issue that levels of organization fit into, namely the relationship between psychology and neurobiology. 2 Therefore, while I agree with Churchland that it is important to have empirical work in mind when giving an account of levels of organization, I do not think that giving an account of levels of organization can succeed by taking reports of empirical results and ordering them according to some intuitive standard such as grain. 3 The problem with working in this manner is that it ignores the need for a specification of what a level of organization is (which I get from Wimsatt). Even if one disagrees Wimsatt s analysis, it is important to have some sort of analysis of levels to work with so that the application of a level is consistent. With this in place a hierarchy of levels of organization can be constructed based upon the results of investigations into nature (or some segment of it, e.g., the brain). And lastly, I want to address a wider problem that I see: the tendency to seek a hierarchy composed of many levels. If it is the case that there have to be many levels, then fine. However, I disagree with the idea that there are as many levels of organization as Churchland supposes. 2 Churchland takes it that this relationship is a reductive one, which she suspects can be accomplished on a bridge-law model (1986: 294). 3 The grain of the study cannot indicate the level of organization unless there is a constant relationship between the two (the grain and the level). If there is not a constant relationship then it is necessary that one is an imperfect indicator of the other.

61 Chapter 2 61 There seem to me to be several motivations that might lead one Churchland in this case, but a similar issue arises with William Lycan and Carl Craver, which I will discuss in chapter six to suggest that there are more levels that fall within the scope of the brain than there actually are. One is an attempt to try to make levels amenable to everything that science does, that is, to use levels to provide a framework that highlights everything that science accomplishes or takes to be important. For instance, Hubel and Wiesel s (1962) demonstration that there are ocular dominance columns in V1 is important, but in the hierarchy of levels of organization that I laid out in chapter one ocular dominance columns are not entities that occupy a level of organization. Rather they are just a feature that arises from the location and connectivity of particular neurons. The reason that my hierarchy does not highlight them is because ocular dominance columns are not entities that have interactions with other entities. But regardless of why, the larger point is that hierarchies of levels do not have to explain everything that science does. There is nothing built into the idea of levels that suggests that they do or should have this purpose. A second possible reason why there is a tendency to construct a hierarchy with many levels is to provide a defense against a possible (or an easy) reduction of the mental or the psychological to the neurobiological. 4 Although, as John Bickle says, Churchland is hardly an enemy of reductionism (2006: 413), it does seem to be the case that the more levels there are that fall within the scope of the brain the less clear it becomes how a reduction would be accomplished. On this point Churchland and Sejnowski say, Moreover, it should be emphasized that the explanation of high level cognitive phenomena will not be achieved directly in terms of phenomena at the lowest level of nervous-system organization, such as synapses and individual neurons. Rather, the explanation will refer to 4 Bickle (2006) discusses this issue.

62 Chapter 2 62 properties at higher structural levels, such as networks or systems. Functional properties of networks and systems will be explained by reference to properties at the next level down, and so on (1990: 351). These are just possible motivations that one might have for constructing a hierarchy with numerous levels. They may apply to different authors to differing degrees or not at all. I am going to set them aside and focus on the hierarchy that Churchland offers. Churchland (1986) cites fourteen articles and arranges them at ten different levels of organization. However, I will take the position that there are only the levels of organization that I laid out previously: (1) the sub-cellular, and (2) the cell network; I will also start with a level for (3) brain areas as a first step in reducing Churchland s list, as well as an additional, higher, level to accommodate a few of the examples she offers: (4) the behavior of individuals. Looking at Churchland s ten levels of organization through the scope of these four levels I think that it is possible to narrow her list significantly. That is, these four levels are sufficient to account for all the phenomena that she organizes into ten levels. 2.2 Churchland s hierarchy of levels of organization Level 1 Churchland focuses on the mechanism for habituation in Aplysia as an illustration of her lowest level. This is from a review by Hawkins and Kandel (1984) in which they describe the cellular pathways in Aplysia that control some defensive behaviors. They explain habituation, a simple type of learning, as the inactivation of the Ca 2+ channels at the axon terminal of the sensory neuron when the sensory neuron is repeatedly presented with a weak stimulus. This causes less Ca 2+ to enter the presynaptic cell, which causes less neurotransmitter to be released onto the

63 Chapter 2 63 motor neuron. A good place to start is by placing this process at the sub-cellular level of organization. Level 2 Churchland uses a study that examines the effects of high frequency stimulation to the axons that synapse on pyramidal cells in the hippocampus to illustrate her second level (Lee et al 1980). This is an early investigation into what the relevant changes might be that give rise to long term potentiation: the increased amplitude of the postsynaptic potentials in a neuron following high (repetitive) activity. The high frequency stimulation did cause long term potentiation in these pyramidal cells in the CA1 region of the hippocampus, and Lee and his colleagues also found that there were some structural changes to the areas where these fibers synapse with the pyramidal cells. In some cases, there were changes in (1) the size of the spines that were postsynaptic sites, (2) where the post synaptic sites were (on dendritic shafts or dendritic spines), and (3) the size of the postsynaptic density proteins on the interior membrane of the postsynaptic cell, which in an electron micrograph show up as a dark area on the membrane. 5 As I said earlier Churchland takes structure to be a feature that defines a level of organization, and in this study we get a report of structural changes in particular changes in the location of the synapse and the size of the spines that were post synaptic sites. And, as is shown in table 2.1, Churchland has synapse as a level of organization. Since this study by Lee et al 5 More specifically, the relevant (positive) results were (1) there were significantly more synapses onto dendritic shafts in the group that received the high frequency stimulation (potentiated group) both as measured by number per 100 µm 2, and as a ratio of synapses onto dendritic shafts versus synapses onto dendritic spines; and (2) there was significantly less variation (standard deviation/mean) and skewedness in size of the post synaptic density, dendritic spine neck width, and dendritic spine area in the potentiated group. The authors conclude, It appears then that repetitive stimulation reduced the variability of spine measurements and decreased the skewedness of their distribution (1980: 255).

64 Chapter 2 64 concerns synapses, I will take this as an example of work at what she calls the level of the synapse, a level that is determined primarily in terms of structure. There are at least two problems that I see with the idea of a level of the synapse. First, the synapse has very narrow boundaries. A synapse is just the presynaptic terminal (the part of the presynaptic cell where neurotransmitter is released), the postsynaptic site (the part of the postsynaptic cell where that neurotransmitter binds), and the space in between the terminal and the postsynaptic site. A lot of activity occurs in this area, but there are interactions that begin in this area and then move beyond it, for example, down the dendrite towards the cell body. It seems counterintuitive to say that merely by moving outside the boundaries of the synapse that we have switched levels of organization. Insofar as the same sorts of activities are occurring (e.g., interactions between macromolecules), and in some cases the very same activities are occurring (e.g., the transport of proteins from the postsynaptic site to the cell body), I do not see the justification for changing levels when activity moves beyond the boundaries of the synapse. A second problem is that synapse, because it only identifies an area and not an activity, seems to be describable at what we might otherwise consider different levels. To take my cell network level of organization, a description of what occurs at a synapse can be given: the axon of a pyramidal cell in the CA3 region of the hippocampus has a synapse on the dendritic spine of a pyramidal cell in the CA1 region, (and the excitation of the pyramidal cell that occurs here causes an excitatory postsynaptic potential). If, however, Hawkins and Kandel had extended their account of habituation to include the postsynaptic site they would have given a description of the activity that occurs at a synapse at the sub-cellular level. And in fact we could go down to lower levels as long as we limited ourselves to the area within the defined boundaries. Without being explicit about what sorts of activities we are interested in, it is not clear how to limit the

65 Chapter 2 65 description of a synapse to one level. But when we do define the sorts of activities that we are interested in, then the first problem reoccurs the boundaries of the synapse impose a seemingly artificial limit on how extended that activity can be (i.e., how far it can go while remaining at the same level). As an alternative to Churchland s level of the synapse we can look at this study in light of the levels that I laid out in chapter one. To do this we have to move beyond thinking only about structure, and so the question becomes: Is this study examining activity that is occurring at the cell network or the sub-cellular level of organization? The activity here is the high frequency stimulation, which was meant to mimic action potentials in these neurons. And this activity the consistent electrical stimulation causes changes to the postsynaptic site of the pyramidal cells. The dendritic spines become less varied in their size and some new connections developed. Adding this much clarifies the issue, but it is still not enough to determine the level at which this study belongs. In order to do that we have to supply more information about this case (and insofar as we have to do this, it demonstrates a shortcoming of simply taking a study and trying to place it in a hierarchy of levels). One way to do this is to assume that we are interested in the effects of pyramidal cells in the CA3 region exciting the pyramidal cells in the CA1 region, and further, the consequences that this activity has on subsequent interactions. (That is, we are interested in the effects of LTP.) If these are the issues that we are interested in, then this study suggests an answer: Long-term potentiation causes some changes in the contacts made between neurons, and hence this is activity at the cell network level. 6 Conversely, we can focus on the sub-cellular level and the activities that caused the changes in the sizes of the dendritic spines. Here we would be looking 6 It has to be noted that the results of this study, by themselves, only weakly suggest this conclusion.

66 Chapter 2 66 at the particular intracellular cascade(s) that begin with the binding of the neurotransmitter and lead, eventually, to changes to the cell membrane. It seems to me that the language and theme of the study suggests the first option the cell network level of organization more strongly. The study is not posed in such a way that it is investigating activities at the sub-cellular level, that is, what caused the observed changes. Rather the study is just observing these changes for the first time. That is not to say that this report does not raise questions that can only be answered at the sub-cellular level, but the report itself seems to be focused on activities that occur at the cell-network level of organization. So, what gain is there in choosing my cell network level over Churchland s level of the synapse? The answer, and this is similar to the first problem that I raised earlier, is that using structure, as a defining feature of levels of organization, especially when thinking about psychological processes, is very limiting. In the case of the synapse, there is lots of activity occurring there, but establishing the level not by that activity, but only by this structure (the synapse) seems to make the level arbitrary. If we are attempting to give an account of some process at one level it seems that having a level like the level of the synapse would make this difficult because of the restrictions that this would impose on how far the process could extend (i.e., only to the end of this boundary). To my mind levels of organization should provide a basis for looking at and identifying processes that occur at that level. They should not disrupt the investigation of those processes. I grant that the synapse is an important feature of the biology of the brain. However, this alone does not seem to be a very good criterion for identifying a level of organization.

67 Chapter 2 67 Level 3 Churchland s third level is represented by a study that investigates the effects of training rats on a maze for one month (Greenough et al 1979). Greenough and his colleagues found that in the rats that had been trained on the maze the pyramidal cells in areas V1 and V2 (areas 17, 18, and 18a) had an increased number of dendrites µm from the cell body as compared to control rats. This study describes a change to a morphological region of a neuron, and issues similar to the ones that I just discussed for Churchland s level two arise. Although Churchland does not have a level of dendrites in any of the hierarchies in table 2.1, presumably she considers this study to be at something like the level of dendrites, right above the level of the synapse. The main problem that I raised when discussing Churchland s previous level applies here as well. That is, the boundaries of this structure are narrow and processes that extend beyond these boundaries will no longer be a part of the same level. Therefore, although dendrites are obviously important neurobiological structures, it is not clear what utility a level of dendrites has when investigating neurobiological processes a level of dendrites seems to limit the process that can be investigated, not aid in the investigations. 7 Rather than thinking of dendrites as a level of organization simply because they are an important structure, we can consider the implications of an increase in the number of its dendrites on a neuron. Since dendrites are usually where synapses are made on the postsynaptic cell, an increase in the number of dendrites allows more contacts to be made on a neuron. Therefore, an increase in the number of dendrites that a neuron has allows that neuron to receive more input from other neurons. From this perspective, we are looking at activity that is occurring 7 These criticisms might not be entirely charitable, but I think that some pressure needs to be put on the idea that structure can determine levels of organization.

68 Chapter 2 68 at the cell network level of organization. Of course what causes more dendrites to form would be a question that would be addressed at the sub-cellular level of organization, but this study is not addressing that particular question. Rather it is focusing on the idea that patterns of connectivity change in response to the demands of the environment (such as maze training). Therefore, the appropriate level for what is found in this study seems to be the cell network level. Level 4 An example of the phenomena at Churchland s fourth level are laid out in a paper by Theodore Berger and his colleagues (1980). In this study the cellular activity at three sites in the hippocampus was compared to activity in the nictitating membrane (inner eyelid) in rabbits during the conditioning of an eyeblink response to a tone. Microelectrodes (5 7 µm diameter) placed in areas CA1, CA3, and the dorsal hippocampal granule cell region recorded the activity levels of cells in the hippocampus, and a nylon loop that was sewn into the nictitating membrane measured the response of the eyelid. The rabbits were conditioned to expect an airpuff to the cornea following a tone (85 db, 350 msec tone, followed 250 msec after onset by a 100msec airpuff to the cornea). The activity of the 21 cells in the hippocampus from which recordings were made was found to correlate positively with the response of the nictitating membrane. Also, the amount of time that the activity of the cells in the hippocampus preceded the activity in the nictitating membrane increased from the first block of trials to the last. In the first block of trials on the first day, the activity in the hippocampus preceded the activity in the nictitating membrane by ±13.97 msec, and in the last block of trials on the second (the last) day by ±6.61 msec.

69 Chapter 2 69 What is important here is the response of the cells in the hippocampus and the implication that they have a role with respect to the conditioned activity of the nictitating membrane. This study is demonstrating that there are interactions indirect interactions perhaps between these cells in the hippocampus and neurons that control the nictitating membrane. Since this study focuses on the activity of these cells, and how their activities direct behavior, this is straightforwardly activity at the level of the cell network The cell network level of organization Having concluded that these last three studies, those at Churchland s second, third, and fourth levels, are all investigating the cell network level I want to reiterate a point that I made in chapter one. The cell network level of organization identifies the entities and interactions that are meaningful when they are understood as interactions among neurons. A single dendrite or a single synaptic connection has a role in the interactions between neurons. This role is on the small side, although how small is only relative to how many other interactions we are observing. In any case, the activity that is occurring at a synapse or at a dendrite only makes sense if we understand it as being part of a series of interactions among multiple neurons. For instance, take a dendrite that has on it a certain number of synapses on it. This might be studied in isolation, but we understand the relevance of a dendrite having a certain number of contacts on it because this indicates the type and amount of excitatory or inhibitory transmission that this dendrite, and consequently this neuron, receives. Therefore it is at the cell network level. 8 8 Of course there are times when we will be looking at the activity that occurs within a dendrite (or to the cell membrane). In these cases the activity will be at the sub-cellular level and the dendrite will not be an entity participating in any activity, but rather just a location where the activity is occurring.

70 Chapter 2 70 The next point that I want to make is that looking at a wide range of interactions (or distant interactions) that are occurring among a large number of neurons is at the same level of organization as looking at a small number of more localized interactions. Someone might object that Lee et al (1980) are looking very closely at a cellular network and some distinction should be made in terms of levels of organization between this and larger networks that include thousands of cells and hundreds of thousands of synaptic connections. However, if the entities and interactions remain the same, no matter how many of them there are, then they remain at the same level of organization. In their study Lee et al look at places where inputs are passed from one neuron to another, or to several others. If the move is made to look at the same types of interactions among more neurons, the level of organization does not change; there just is more going on at that same level of organization. A second reply to this objection is that simply based on the number of synaptic contacts that one neuron can make (e.g., the spiny stellate cell that was used as an example in the previous chapter had 2879 synapses on its dendrites and 2545 terminals on its axonal arbors), then the numbers of neurons that are going to interact with each other is quite large. Nevertheless, we might focus on a very small number of cells, say two cells and how they interact, in which case we might choose to look more closely at the interactions. However, we do not want to consider just two neurons as constitutive of a level of organization because then there is a boundary and a series of interactions that extends beyond that boundary forces us to move to a different level of organization. The boundary would, in effect prohibit us from tracking the activities that extend beyond that boundary. And so if we do not insist upon any sort of boundary, then we have to accept that when we talk about cells interacting we may be speaking on the order of thousands of cells or more.

71 Chapter 2 71 A case from a different level of organization might help clarify this. Consider for instance a sociologist at a bus station who is trying to get a general idea of the interactions that occur there (people buying tickets, saying good-bye to friends, waiting for their bus, etc.) versus a second sociologist that is studying the interactions that occur only at the ticket counter. The second sociologist is studying a more specific and localized series of interactions, but both sociologists are studying entities (humans) and their interactions at the same level of organization. Additionally, the sociologist studying the activity at the ticket counter is still working at the same level if he is studying some very narrowly focused and local aspect of the transaction such as the destinations that people are buying tickets for, the size of the bills people are paying with, or the number of people who brush hands with the person who is selling the tickets. The point is that as long as the entities being studied remain the same the individuals and the artifacts they manipulate and the activities are the activities that those individuals are engaged in, then the level of organization remains the same. In this discussion of the cell network level and the level of individuals, I should emphasize that the way I am employing levels of organization accomplishes what we want a level of organization to do: a set of entities and interactions is identified and placed at a level, and this distinguishes them from other entities that they cannot interact with (at least under normal circumstances). This is not to say, however, that levels of organization, by themselves, tells us everything that we want to know about the interactions. For example, we may want to know about the interactions that occur among siblings and compare this to interactions among non-siblings. Presumably, the two types of interactions are generally different, and interesting, but this is a further issue that is investigated by the relevant science after we have established the

72 Chapter 2 72 level of organization. And even though the interactions will be different between the siblings and the non-siblings, this does not mean that there are two levels of organization here. Level 5 Returning to the hierarchy of levels, Churchland uses an article by Walter Freeman, Nonlinear dynamics of paleocortex manifested in the olfactory EEG (1979) to demonstrate what is found at her fifth level. In this paper Freeman describes a model that he developed that represents the behavior of the early part of the olfactory system (from the olfactory receptors to the output of the olfactory bulb). The biophysical states that Freeman is modeling are the bursts of activity, as measured by the electroencephalogram (EEG), that are generated by the mitral and granule cells in the olfactory bulb. This technique, the EEG, uses electrodes that are attached to the scalp (or in some cases implanted in the brain), to measure electrical potentials. The electrical potentials that are measured are post-synaptic potentials, which is the voltage inside the postsynaptic neuron (it is the voltage inside the membrane versus voltage outside when the voltage outside is assigned the value of 0). This value will rise when a postsynaptic cell has received an excitatory input. Measuring the post-synaptic potential is not the same as measuring action potentials, which the EEG is not able to do. 9 Pairs of the electrodes measure differences in electrical potentials and this voltage is amplified and graphed by a polygraph. This method of measuring brain activity can to some extent focus on local activity, but it will be measuring the activity of a very large number of cells (Kingsley 2000: 525 6). 9 Post-synaptic potentials, the voltage change caused by the release of neurotransmitter may contribute to the generation of an action potential (although in some cases it will not), but are not action potentials themselves.

73 Chapter 2 73 Freeman s paper, however, is not directly about the data generated by using EEG. Rather it is a mathematical model that seeks to explain how inputs from the olfactory receptors, which linearly code the inputs they receive (i.e., maintaining the intensity and time values of the stimulus), are transformed into the outputs that the cells in the olfactory bulb produce, which is in bursts of activity. The intuition is that this system is sensitive to the stimuli that it receives, but not so sensitive that it responds strongly to all stimuli. As Freeman notes, The design requirements for sensitivity and stability in a sensory system are clearly antithetical. Most features that enhance sensitivity tend to decrease the margin of stability. But on the one hand the sensitivity of the mammalian olfactory system to a broad variety of odorous substances is legendary, and on the other hand it is normally quite stable, although the conditions in which it can be driven into limit cycle or seizure activity are well known (1979: 34). In order to represent the transformation of input into output Freeman used a set of nonlinear differential equations that operate on several sets of variables representing different entities in the system (e.g., olfactory receptors, periglomerular cells, mitral cells). The material described in this article is a bit of a deviation from Churchland s first four levels. To begin with, Freeman s model of the early part of the olfactory system is not identifying biological entities at all but rather modeling them. 10 To the extent that it models the activity rather than just describes it, I would say that it does not belong directly to any level of organization. How to fit abstract models of biological processes (such as Freeman s) into a hierarchy of levels is a matter that I will deal with in later chapters when I discuss levels of explanation. For the time being matters can be simplified by ignoring the model and focusing on the EEG and what it is measuring, which is what provides the data used to construct the model. 10 This is what I would call a description that can be placed at a particular level of explanation, not a level of organization. I will take up levels of explanation in the next chapter.

74 Chapter 2 74 This seems to be what Churchland has in mind as an exemplar for this level which she describes as, the cell assembly studies in the olfactory bulb by Freeman (1979), which uses an 8 x 8 electrode array and evoked response potentials averaging techniques (1986: 360). So what is it that Churchland is placing at this level? One answer that could be given is: the neurons that have their postsynaptic potentials measured by the EEG, all however many millions of them there are. 11 This answer is, I think, more or less correct, but has to be given with the caveat that the EEG only measures the change in the postsynaptic potential of these cells. If this answer is correct, then these entities and their activities belong at the cell network level, although there is not really any attempt being made to investigate what the specific interactions are between these neurons. All we can really conclude is that there are neurons here that all are generating changes in their postsynaptic potentials. 12 This seems uninteresting as a description of activity at the cell network level, but at the same time it does not, in any obvious way, put pressure on me to conclude that it is a different level. Even if we were thinking in terms of composition instead of interaction as the defining feature of levels of organization, and want to introduce entities that are composed of neurons (e.g., layers of neurons, columns of neurons, brain regions) the EEG does not identify any of these particular assemblies of neurons, it just measures the neurons that are beneath the electrodes. 11 Freeman puts the number of cells that are part of this system at 4 x 10 8 in each hemisphere (in the cat), but the cells that are generating the output that the EEG is measuring is a subset of this. 12 EEG is a useful clinical tool for diagnosing and monitoring epilepsy, sleep disorders, and comas. It is also sometimes used to study cognitive processes, for instance Richard Davidson (2004; Pizzagalli et al 2005) has used EEG to investigate the relative contributions of the right versus the left frontal lobes in emotion processing.

75 Chapter 2 75 These criticisms are directed towards Churchland s placement of this article in her hierarchy. However, it is of interest for its own sake to look briefly at Freeman s project, although I do not have room here to give it a full treatment. Freeman has for some time advocated an approach to understanding goal-directed behaviors that focuses on patterns of activity in the brain, where these patterns of activity are what are measured by the EEG. The reason that it is difficult to find a satisfying level at which to put Freeman s paper is because he has a different notion different than anything Churchland or I might entertain of what the relevant levels are. And he has a very different notion of what exactly it is that occupies the main level of his framework (different at least from everything we have encountered in these first two chapters). He does accept that there is a level where there are neurons. And he agrees that this is a level that is important to investigate, but this is because it is useful for understanding the range of possible states that the individual units that form populations of neurons can have (Freeman 2000: 5). In addition to the level of neurons there is the level of populations of neurons and their behavior, what Freeman calls the mesoscopic level. This is the privileged level at which it can be seen, for example, with the EEG, how the organism responds to the patterns of stimuli that it encounters. Agreeing that Freeman s account may be useful for understanding the neural basis of behavior means adopting a whole new framework with respect to the mind-brain sciences (and it is a framework, not just the use of EEG). His framework cannot simply be inserted into a hierarchy of levels, because the whole point of the framework is to demonstrate that this level what is measured by the EEG is the only relevant one. That Churchland does insert it into a hierarchy of levels suggests that she is not really committed to embracing Freeman s model.

76 Chapter 2 76 Level 6 Churchland offers two examples to illustrate the phenomena at level six, an article by Zola- Morgan and Squire (1984) and one by Nottebohm (1981). The Zola-Morgan and Squire paper is a report of several experiments that they ran with monkeys whose brains had been lesioned. Some of these lesions matched the lesions of (the human) patient H.M. who had his hippocampus and amygdala removed bilaterally. Other lesions (in different monkeys) were used as controls. After being lesioned the monkeys were tested on pattern discrimination, 13 object discrimination, 14 and learned motor skills. 15 Zola-Morgan and Squire found that the monkeys with the hippocampus-amygdala lesions were slightly impaired in visual discrimination tasks, severely impaired in object discrimination tasks, and unimpaired in tasks that tested learning motor skills. Their explanation for the difference in performance on visual discrimination and on object discrimination tasks was that the hippocampus-amygdala lesioned monkeys were able to perform tasks that required skill learning (pattern discrimination) but not tasks that required learning facts about the task such as which stimulus is the rewarded one (i.e., the object discrimination [1984: 1079]). The Nottebohm article is a short review of the work he has done on the neural control of song abilities in canaries. This article touches on several different aspects of Nottebohm s work, including the study of the pathway from the two forebrain nuclei that control song abilities to the 13 The monkeys learned to discriminate from +, and N from W. Each monkey always received a reward for choosing the same pattern, although the placement of the pattern (on the right or on the left) varied trial to trial. 14 The monkeys learned to discriminate objects, e.g., a half peanut shell dyed red or a half peanut shell dyed green. 15 In these two tasks the monkeys learned to manipulate a breadstick through a barrier, and lifting a lifesaver off of a metal rod with 90 bend in it.

77 Chapter 2 77 vocal organ; the dominance of the pathway in the left hemisphere; and the correlation between the size of one of the forebrain nuclei and the size of the canaries song repertoire. Churchland indicates that she is focusing on the seasonal changes in the songster nuclei of the canary brain (1986: 360). Nottebohm s work has revealed that these two forebrain nuclei are 50% and 40% smaller in the fall when the males are silent, than in the spring when the males song abilities are being used most frequently. Nottebohm s hypothesis is that this is a result of the shedding and growing of dendrites (and as a consequence the shedding and then the forming of new synapses), which may be controlled by testosterone levels. The basic theme that these two papers share is the identification of a specific brain area that controls a particular behavior. 16 As I said in the previous chapter I am skeptical that specific functional brain areas can have a level of organization to themselves. However, I will set that worry aside for the moment, and place these studies at the brain areas level of organization. At the end of this chapter I will consider the status of a brain areas level in light of these two articles and the article that Churchland has at level eight. Level 7 Churchland s seventh level is illustrated by Terry Jernigan s (1984) article on several studies that used transmission computed tomography (TCT) to study memory, and a short report of a study by Volpe et al (1983) that used positron emission tomography (PET) to study two subjects suffering from amnesia. 16 However, it can also be pointed out that the hypothesis concerning dendritic growth seems to be at the same level of organization as the work that was done by Greenough et al (1979), which on Churchland s list was down at level three, and which I placed at the cell network level.

78 Chapter 2 78 The first technique, CT scans, use narrow x-rays that are passed through the subject s head and collected by photomultiplier tubes (not photographic film as in normal x-rays). The photomultiplier tube then converts the x-ray signals into electrical signals. After the x-rays have been collected from the full 360 around the subject s head the electrical signals (from the photomultiplier) are used to compose an image of a cross section of the subject s brain (Kingsley 2000: 619). In the one study that Jernigan discusses at length, immediate memory (e.g., digit span), recent memory (e.g., verbal paired associates) and remote memory (recall of information) were measured in behavioral tests, and then the atrophy of tissue at several sites in the brain were measured from the CT scans. 17 Jernigan found that, although some of the measures did correlate (recall was significantly correlated with atrophy at two sites 18 ), none of these correlations were found to be predictive of a specific memory deficit. It has to be admitted that if we are thinking in terms of cutting edge neuroscience this study is a little bit disappointing. Churchland composed this list in the mid-1980s, and the trend since then has been away from using CT for the study of cognitive abilities and towards the use of functional imaging techniques (PET and fmri, which I will discuss below). Moreover, there are good reasons why CT is generally not chosen to study cognitive abilities, which this work by Jernigan demonstrates, namely, it is too coarse of a technique. It can identify atrophy, as well as 17 I.e., atrophy as measured by the vertex sulcal widening, the size of the sylvian and interhemispheric fissures ( frontal and interior temporal cortical atrophy ), and ventricular enlargement (general cortical atrophy). The subjects in this study ranged in age from Atrophy was identified in the vertex sulcal widening, and the size of the sylvian and interhemispheric fissures.

79 Chapter 2 79 tumors, hemorrhages, and infarcts (areas of dead tissue), but it cannot identify activity, or even anatomical detail very well. My initial inclination is just to eliminate this study and this level from the list on the basis that it is not measuring anything we care about with respect to memory. Moreover, this problem demonstrates that we cannot just take a series of empirical studies, order them into a hierarchy, and have a hierarchy of levels of organization. If we do, the hierarchy will clearly be excessive since besides the problem of different studies attempting to access the same entities with different techniques, some studies are not measuring anything (or at least anything meaningful) because of the limits of the technology available. On the other hand, if we want to try to determine the level of organization that this work belongs to I think two directions can reasonably be taken. First there is a similarity between this work and the work that is done by Berger et al (1980) at Churchland s level four. In the research Berger et al were doing they were identifying one part of a particular series of neurons that interacted with each other. Their results suggest that the network includes both the cells they were recording from in a few areas in the hippocampus and the nictitating membrane. Jernigan s work also seems similar to Berger et al s in that she is looking for areas where the lost of neurons by way of atrophy appears to cause behavioral deficits. Berger et al and Jernigan are working at different scales, the former is measuring cellular response with microelectrodes and the latter is measuring gross tissue loss. Nevertheless, there is a sense in which their work is trying to gain access to the same thing where neurons are and what behavioral effects they have. In the former case, the Berger et al study, the focus is positive: investigating neuronal activity that appears to drive behavior. On the other hand, for Jerigan the focus is negative:

80 Chapter 2 80 investigating what is missing when a psychological deficit is present. However, the entities, and I would say activities, are the same (or of the same kind). An objection to the idea that these are both at the same level of organization may be that the Berger et al work is much more specific, or they are much more in touch with the cellular network that they are studying. However, I do not think that a feature of a level of organization can just be lack of specificity, or the particular methodological criteria selected by the researchers who are trying to gain access to a level of organization (or just ignorance on the part of the researchers about where they should be looking). The entities and their interactions that determine the level of organization are there (if it is a level of organization), and if the researcher is trying to find something out about those particular interactions or the entities that participate in those interactions, then that is the level of organization of his or her work. The only other plausible alternative is to put the phenomena that Jernigan is investigating at the level of the whole brain. The argument here would be that the brain gives rise to psychological capacities (of which memory is one) and general damage to the brain, as in the case of atrophy gives rise to deficits in psychological capacities. In this particular case I think there are reasons to avoid this conclusion. Jernigan is aware that this might in fact be all that she is measuring, namely general cortical damage that correlates with general cognitive deficits (1984: 260), and she is trying to control for this by integrating results from numerous studies (and subjects), and by making the measures taken from the brain scans more specific than just the whole brain. For these reasons, I do not think that it is accurate to say that Jernigan is working at the level of the whole brain. When we consider what level of organization her work does belong on, I think it is reasonable to say she is trying to observe the cell network level of organization.

81 Chapter 2 81 In the second study Volpe et al (1983) used positron emission tomography (PET) to scan two patients that were suffering from amnesia. In PET scanning the subject is given (by injection to the bloodstream or inhalation) a small amount of a biological compound that is used by the brain, and which includes a short-lived radioactive isotope. For example, 18 F is used to synthesize 18 F-deoxyglucose. The 18 F-deoxyglucose behaves like deoxyglucose except that it can not be metabolized so it just builds up in neurons. The build up of 18 F-deoxyglucose indicates the neurons that are consuming glucose, which is an indication that they are active. Meanwhile the unstable 18 F decays and emits a positron that eventually collides with an electron, destroying both and creating two gamma rays (photons). The gamma rays are detected by the PET scanner and this information is used to create an image highlighting the area where glucose consumption was occurring (or more precisely where the collision occurred). 19 Although it was a fairly rudimentary investigation (recall that this is from 1983), the study by Volpe et al includes this element of tracking where activity is occurring in the brain at a particular time. And they found that there was a drop in the extraction of oxygen from the blood in the middle temporal lobe (which they found by using the isotope 15 O) in the two patients suffering from amnesia as compared to normal subjects. 20 Before discussing the level at which Volpe s work belongs I want to consider functional magnetic resonance imaging (fmri), another imaging technique that is widely used today in 19 Other radioactive isotopes synthesized into other compounds are also used, for instance 15 O in H 15 2 O (water) and 18 F in 18 F-dihydroxy-phenylalanine, a compound from which dopamine is created (Saper, Iverson, Frackowiak 2000: ). 20 Volpe et al do not report having the subjects perform any task while the scanning was occurring. They do however, compare the measures of two patients suffering from amnesia with five normal subjects.

82 Chapter 2 82 cognitive neuroscience, but which Churchland does not include in her hierarchy of levels (presumably because it was not widely used when she wrote her book [1986]). Magnetic resonance imaging (MRI) measures the nuclear magnetic resonance that atomic nuclei give off after they have been subjected to a brief radiofrequency pulse. Typically it is hydrogen atoms in water that are used for this. The MRI scanner s magnet causes the axis of some of the atomic nuclei to become aligned (along the north-south axis of the magnetic field). The radiofrequency pulse then causes this alignment to shift and the proton(s) of these atoms to spin in phase with each other. When the radiofrequency pulse is over, the nuclei return to their prior state; nuclei shift back, and the proton spinning comes out of phase. This releases energy a radiofrequency pulse (the resonance) which is given off by the atoms, and atoms in different tissue (e.g., in fat, in water, intracellular, extracellular, in the blood, or cerebral spinal fluid) give off differing amounts. This resonance is detected and from it an MRI image is generated (Kinglsey 2000: 622 6; Saper, Iverson, and Frackowiak 2000: ). The MRI technique, like the CT, produces an image of a cross section (a slice) of the brain. The advantage of functional MRI (fmri) over MRI and CT scanning is that it produces an image that locates areas of the brain that are active. It does this by focusing on the protein hemoglobin in the blood supply of the brain. The supply of oxygenated blood to areas of the brain that are active is greater than is necessary, and so the ratio of oxygenated blood (oxyhemoglobin) to deoxygenated blood (deoxyhemoglobin) actually increases in areas of activity. Oxyhemoglobin and deoxyhemoglobin also have different magnetic properties, which means that after the radiofrequency pulse has ended the protons in the oxyhemoglobin stay in phase longer than the protons in the deoxyhemoglobin. Therefore, the areas of the brain that have

83 Chapter 2 83 a higher ratio of oxyhemoglobin also have a stronger MRI signal (Saper, Iverson, and Frackowiak 2000: 370 5). In order to determine which level of organization these two functional imaging techniques, PET and fmri, are investigating we have to consider which level of organization researchers who are using these methods are trying to access. This is different than merely considering the level at which the entities and activities that these techniques are directly measuring belong to. The entities (atomic and sub-atomic particles) and their activities (spinning [fmri] and colliding with other particles [PET]) are at a very low level, a level that we would normally think of as the domain of physics. But researchers studying the brain are not really trying to gain access to this very low level. Rather they are using the activity at this level to infer what the activity is at a higher level. Basically they are trying to infer which neurons are active. 21 This means that these imaging techniques are techniques that are trying to gain access to the cell network level. Nevertheless, we have to keep in mind that this is a fairly crude method of gaining access to neuronal activity (although it has the practical, and ethical, benefit of being non-lethal to the subjects), but as I have said before, the grain of the investigation does not determine the level of organization to which the researchers are trying to gain access. Someone might object at this point and say that these techniques are accessing brain areas. The idea being that because of the grain of the techniques we end up identifying fairly large populations of neurons, and so when we look at the results from a functional imaging study we cannot exactly say which neurons are active (all we know is that a lot of them in a certain 21 And interestingly in order to make this inference they must also infer details about the activity of entities at a level in between, eg., hemoglobin for fmri and glucose or some other compound for PET. And note that inferring which neurons are active is not the same as inferring what those neurons are doing, which if necessary requires a further (perhaps, more difficult) inference.

84 Chapter 2 84 area are active), but we can say (fairly) definitively that a particular brain area (e.g., V1) is active. This is a reasonable objection, but my general resistance to taking brain areas to be a level of organization, plus the fact that we are interested in which neurons are active, makes me wary of accepting that this is an example of the brain areas level. By looking at how these techniques work however, I think we can add to the argument against thinking that there is a level of brain areas. As I said before, interpreting these techniques involves working up to the level where neurons are. For example, in fmri, from the different rates of the dephasing of protons we infer the presence of oxyhemoglobin, and from the presence of oxyhemoglobin we infer the activity (and the oxygen needs) of neurons. To make a claim about a brain area we would have to make a further inference. This would be a simple inference (if it is really an inference at all), since we would basically just be stating an identity: if the neurons in this particular area are active, then this particular brain area is active. This is simple enough, but my worry is that it is so simple that the claim that the brain area is active is an empty claim. There is nothing that the brain area is doing that leads to the inference that the brain area is active except the identity: a collection of neurons in a particular area is a brain area. This then focuses on one of my worries about brain areas in general: if they are an entity, then what do they do? For neurons, we take the fact that oxyhemoglobin is being delivered to neurons, include some facts about the consumption of oxygen, and infer that these neurons are receiving inputs from other neurons (and possibly generating their own action potentials in order to pass a signal on to other neurons). There is no similar sort of claim that can be made about brain areas, because there is nothing that they do except have the property of being composed of neurons.

85 Chapter 2 85 Level 8 Churchland uses an article by Squire and Cohen (1984) reviewing what was, at the time, known about amnesia as an example of what is found at her eighth level. In the article Squire and Cohen discuss: (1) the types of neural damage that are known to cause amnesia (Korsakoff s syndrome, H.M. s surgery, and bilateral electroconvulsive therapy), (2) the specific deficits that these patients display in behavioral experiments, and (3) a review of some work on animal models of amnesia. This article seems to have exactly the same theme as the work at level six, that is, identifying the behavioral function of specific brain areas, or conversely identifying the specific deficit when a particular brain area is damaged. The review article by Squire and Cohen even uses the study by Zola-Morgan and Squire from level six in order to illustrate the animal models that have been developed. This suggests that what Churchland has as levels six and eight are by any standard the same level of organization. Against this suggestion there might be two objections. The first is that removing specific brain areas in monkeys, having them perform some tasks, and then removing their brains to confirm what neural damage they received (level six) is work that seems like it belongs at a different level than studying patients that have acquired amnesia in a variety of ways. 22 However, (1) the hippocampus of a monkey is not at a different level than the hippocampus of a human. And (2) how we look in at particular entities cannot determine the level of organization they occupy. In the animal models the identification of the relevant areas is fairly straightforward, since the researchers made the lesions themselves and then they removed the brain after the experiments to examine the lesions more closely. The relevant brain area in, for instance, 22 The examples for level eight are as follows: HM who had lesion surgery performed in order to control the seizures that he was suffering from; NA, whose damage was sustained by getting a fencing foil up the nose; and Korsakoff syndrome is induced by long term alcohol abuse.

86 Chapter 2 86 patients with Korsakoff syndrome are somewhat harder to identify because the researchers cannot be as straightforward in their investigation, and because this syndrome affects a larger brain area, only part of which is relevant to the amnesia. Nevertheless, the consequence is the same: some particular brain areas control particular behaviors, and therefore this work has to be at the same level of organization as the work Churchland places at level six. Level 9 At level nine in Churchland s hierarchy is a description of the cues that bees use to remember one aspect of a food source, a flower s shape its outline and the pattern of colors on its petals (Gould 1985: 1492). Bees were tested using artificial flowers that had different patterns. The results suggest that bees use the spatial relationships between the different elements in a pattern in order to remember the flower shape. There is not any mention of neurobiology in this article; rather the focus is on the behavior of the bees under different conditions. In this case the conditions are the exposure to artificial flowers with different patterns some of which contained food (sucrose) and some of which did not. By altering the way in which the artificial flowers were presented and measuring the bees behavior Gould was able to make a claim about a capacity that bees have: the ability to remember spatial relationships between the elements of the pattern on a food source. I am going to place Gould s work at the level of individuals, the level where individuals, or more broadly organisms, are the entities and their interactions are with each other and their environment.

87 Chapter 2 87 Level 10 At her highest level Churchland offers two examples, one by Norman (1973) and one by Tulving (1983). The phenomena at this level she describes as, psychological studies of memory capacities and skills of college undergraduates, (1986: 360). It is a little odd that she gives this as the description of this level, but then references two works that are a good deal more than just reports of experiments done with college students, although both psychologists reference empirical data. Since my next two chapters focus on psychology, I am not going to spend much time here examining Norman and Tulving s projects. Insofar as one way to study memory is to take some subjects, ask them some questions, record their answers, and then analyze the data, this level is not any different than the previous one. Both are studying the behavior of animals, bees and humans respectively. As Churchland points out, the former is ethology and the latter is psychology, but this distinction is not one that concerns a hierarchy of levels, at least not in the way she has been constructing them up to here, and certainly not in the way that I understand levels of organization. It should also be mentioned that there is more that can be done within the domain of psychology than just experiments with undergraduates. Descriptions can also be given concerning what a psychological capacity such as memory is exactly, or how it works. These sorts of projects are, for the most part what concern Norman and Tulving. This is no longer, at least straightforwardly a description of behavior, rather it is a description of a capacity that guides behavior. However, for the purposes of reviewing Churchland s list of levels, it is easier to stick with the simpler characterization of psychology as the study of behavior, which is what she seems to have in mind anyway.

88 Chapter Synopsis of Churchland s ten levels With respect to Churchland s ten levels I have argued that there are no more than the four levels that we started with: sub-cellular, cell network, brain areas, and behavior. This conclusion is shown in the table below. sub-cellular: Hawkins and Kandel (1984) [1]. cell network: Lee et al (1980) [2], Greenough et al (1979) [3], Berger et al (1980) [4], Jernigan (1984) [7]. brain areas: Zola-Morgan and Squire (1984) [6], Nottebohm (1981) [6], Squire and Cohen (1984) [8]. individuals: Gould (1985) [9], Norman (1973) [10], Tulving (1983) [10]. Table 2.2. The numbers in square brackets are the levels at which Churchland places each of these studies. Where it was feasible I have tried to critique Churchland s levels by simply inquiring into what is going on at that level. That is, locating redundancies in her hierarchy by just looking closely at what exactly the phenomena are at each of her levels. Where necessary I have extended the critique and discussed reasons why we should use interaction among entities to establish a level of organization. But on the whole I want to insist on the idea that a hierarchy with many levels does not appear to be a successful analysis of the levels that fall within the scope of the brain. I take it that it would not be that interesting to take a list of different levels of organization and point out a couple of problems here and there. However, when we begin with a list of ten levels of organization and are left with only three or four, then I think we have made some progress. First, we have a much simpler and more straightforward way of getting some traction into the problem of how we might think about the relationship between psychology and neurobiology. Instead of following Churchland s suggestion that we have to work through numerous levels and determine how each is related before we can fully address this problem, we

89 Chapter 2 89 can look at the levels of organization that we do have and begin to think about how psychological processes might be carried out by what is found at a few different levels. This is the issue that I will address in chapter five. Second, I have looked at a range of evidence that Churchland has offered and been able to show that it is basically consistent with the hierarchy that I established in chapter one. Hence, this examination of Churchland s list has also been useful as a basis for discussing some aspects of my own hierarchy of levels of organization. In particular, what is found at the cell network level and how those phenomena are investigated, as well as some more problems with thinking that brain areas belong at a level of organization. Regarding brain areas, I have left some of the studies that Churchland used as exemplars of her levels at a brain areas level, and so I will turn to the status of that level now Brain areas In the previous chapter I said that above the cell network level of organization there are entities, for instance, functional brain areas but they do not constitute a level of organization. Now we have some examples from Churchland that can be used in order to revisit the issue of whether or not there is such a thing as a brain areas level of organization. This, in the way that I am conceptualizing level of organization, is a question of whether or not there is a level where interactions among brain areas occur. Since the Zola-Morgan and Squire (1984) and the Squire and Cohen (1984) studies are very similar I will just consider the Zola-Morgan and Squire article. Zola-Morgan and Squire carried out several experiments with monkeys that had select brain areas lesioned. The main deficit that Zola-Morgan and Squire wanted to test was the

90 Chapter 2 90 damage that patient H. M. had sustained, the bilateral removal of the amygdala and hippocampus and how this affects memory. They found that the lesioned monkeys had certain memory deficits that the controls did not (some of which had different lesions and some of which had no lesions). Using the technique of lesioning in order to investigate what behaviors rely on the hippocampus and amygdala does not give us direct information about entities and how they interact. It does however, make an assumption about what count as entities, namely the hippocampus and amygdala. The memory deficits that occur after lesioning are a first step towards counting the hippocampus and amygdala 23 or just the hippocampus as an entity that participates in memory related behavior. Therefore, we might also conclude that this entity is part of a level of organization a brain areas level of organization. There are a couple of issues that suggest that this conclusion is not warranted. First, a lesion of this sort clearly affects the entities and activities at lower levels of organization, and so the behavioral effects could reasonably be ascribed to destroying the entities or disrupting the activities at a lower level of organization. 24 Although I think that this is the case, this possibility is not entirely fair to someone who wanted to maintain the brain areas level of organization. It always could be the case that by lesioning or otherwise damaging an entity at one level of 23 However, we now know that these same deficits can be found with much narrower damage (i.e., with less of the brain lesioned). One helpful way of understanding their study is as an early attempt to determine what brain area(s) give rise to certain behaviors. As far as this particular study is concerned they were working with too large of an area. They could have left the amygdala alone and made selective lesions to the hippocampus to find the particular behavioral deficits that interested them. But they did not know this at the time and were simply working off the model of a patient who had received his brain lesions to help prevent seizures. 24 The hippocampus is just a single layer of cortex, essentially a cell network runs through it. So removing this part of the cell network for memory the part where the consolidation occurs causes the particular deficits that H.M. has. This way of looking at what is going on in Zola-Morgan and Squire s study makes it appear that this belongs at the cell network level.

91 Chapter 2 91 organization, the important or real effect of the damage is occurring at (what we might consider) a lower level. A second point is perhaps stronger. In this paper Zola-Morgan and Squire do not discuss or suggest what activities this entity, the hippocampus, may be involved in. In fact in this study they are not interested in the process that might be carrying out these memory related behaviors. Rather they are focusing on the kinds of behavioral deficits that correlate with this type of brain damage. As they say at the end of their paper, Study of the neurology of memory in monkey and man is nearing a point where it should be possible to identify the specific regions which when damaged caused amnesia. This information will be particularly useful because the study of human amnesia has already taught us a great deal about the function of this yet to be specified brain system (1984: 1083). This passage is suggesting that although the lesioning of a brain area does produce behavioral effects (like amnesia), the lesioning of the brain area does not inform us about the process that carries out the memory ability. The lesioning causes certain behavioral effects, but that is all that the study investigates. This being the case, we have to conclude that although this study makes a strong case for the hippocampus as an entity it does not demonstrate how this entity participates in any activities, which would be necessary in order to conclude that brain areas is a level of organization. Therefore, at least with the analysis of levels of organization that I am using Wimsatt s this is not a level of organization For a related discussion of Nottebohm s work see the appendix to this chapter.

92 Chapter 2 92 Appendix, chapter two Another study that I placed at the brain areas level was Nottebohm s work from Churchland s level 6. Churchland focuses on the seasonal changes in the songster nuclei of the canary brain although Nottebohm s article touches on a couple of other related issues. The finding that the nuclei that are required for song are larger in the spring than in the fall, only brings up the same issues that were just raised about the Zola-Morgan and Squire study, that is, that correlating a brain area here the hyperstriatum ventral, pars caudate (HVc) with a behavioral capacity does not necessarily identify a level of organization. Nottebohm in this article discusses another aspect of his work, which I think is more important for the issue being discussed here: the pathway that is used in producing song in canaries. This pathway is from the HVc to the robust nucleus of the archistriatum (RA), and form there to (the motor neurons in) the hypoglossal nucleus. From the hypoglossal nucleus the hypoglossal nerve innervates the syrinx (the vocal organ). This is illustrated in the figure below. Figure 2.1. L is the auditory projection originating in the neostriatum. nxii is the hypoglossal nucleus, and ts designates that these motor neurons innervate the trachea and syrinx. From Nottebohm 1981: 105.

93 Chapter 2 93 Here we do have entities, and although we do not exactly have any clear explanation of what interactions they have at this level, we at least do see how they can interact by way of the fiber bundles that connect them. If someone wants to insist that this is a level of organization, then so be it. Although it can be noted that, as I said in chapter one, introducing these fiber bundles only gives us another entity, not any activity. A point that I will take up again in chapter four, but want to introduce now with this example is that this level of organization is a very crude way to investigate a particular capacity. Sometimes that may be acceptable. If we want to know about song production in canaries, knowing what Nottebohm reports is certainly a huge improvement over knowing nothing. We do not however, really know much about the particular elements of canary song and song production (timing, pitch, loudness, etc.), and studying only the brain area (qua entity) will not inform us about these aspects of the capacity. As Nottebohm says, Following left HVc lesion virtually none of the preoperative components of song survives in a recognizable manner. Instead, song is produced in a rambling, poorly structured way reminiscent of the earliest stage in song development, ie. subsong. Destruction of the left HVc seems to eliminate the learned programme for song. After a comparable destruction of the right HVc some of the components of song disappear, others become more variable, yet the overall patterning of song remains little affected, and to the ear it still sounds like a good canary song (1981: 104). Perhaps with time one could sort out some elements of the canary s capacity for song production by studying the effects of lesioning this brain area (HVc), but the more realistic way of proceeding seems to be to move to a lower level to gain specific access to the capacity. The point being that even if one wants to insist that the brain areas occupy a level of organization, it is not the place where a capacity like song production (or psychological capacities) can be investigated.

94 Chapter Levels of Explanation In addition to levels of organization, another way of using levels is as levels of explanation (or description or analysis). 1 Whereas with levels of organization we are concerned with ordering the entities and their interactions that are found in nature, with levels of explanation we are concerned with using levels to order the different ways of describing some phenomena (e.g., a process) that we find in nature. David Marr (1982) has what is probably the best known account of levels of explanation and I will examine his account in this chapter. The reason for explaining Marr s account of levels of explanation is so that it can be used, along with levels of organization, to demonstrate how psychological descriptions of different capacities relate to descriptions of the relevant neurobiological material. In the next chapter I illustrate that Marr s highest level of explanation is consistent with the way that some explanations of psychological capacities are framed in cognitive psychology. To do this I use as an example models of the early part of the emotion process that have been proposed by cognitive appraisal theorists. Then in chapter five I offer an account of the relationship between this kind of psychological description of a capacity and the neurobiology that was discussed in the first two chapters. 2 1 I do not know of anyone that makes a serious distinction between: levels of analysis, description or explanation. Marr (1982) appears to move back and forth between description and explanation (cf. 1982: 25 and 329). 2 Note that there is a difference in meaning between a psychological description of a capacity and a description of a psychological capacity (eg., memory, vision, language). The first refers to the type of description that is offered in the language of cognitive psychology. That is, the terms used are those employed by this particular science. The latter is a description of a particular type of capacity in any of several different formats, ie., the language of neurobiology, the language of cognitive science, and of course the language of cognitive psychology.

95 Chapter Marr s account of levels of explanation Before I discuss Marr s account I want to look at what it means for something to be a level of explanation, a point that Marr does not explicitly cover. Churchland and Sejnowski suggests that Levels of analysis concern the conceptual division of a phenomenon in terms of different classes of questions that can be asked about it, (1988: 741). 3 This could be a good way to formulate the idea of levels of explanation, but on the face of it something appears to be missing since different questions do not appear, by themselves, to line up in any sort of hierarchy of levels. For example, taking Marr s example of a cash register, the questions: What does a cash register do? and How does it do it? are two questions that are posed at different levels of explanation. And insofar as they require different answers, they are different kinds of explanations. However, these questions do not in and of themselves suggest a hierarchical organization. A more promising suggestion is that levels of explanation are explanations at different levels of abstraction. At the very least, abstraction away from the physical or biological material allows one to put levels into a hierarchy. Abstraction needs to be understood loosely, because it is often an imperfect decision that has to be made in order to say that one sort of explanation is further away from the physical material than another. Nevertheless, even understood loosely, abstraction away from the physical material is a way of lining up different types of explanations into a hierarchy. It may also be the case that different sorts of questions set up answers about an entity that are more or less abstract. So, the idea of different types of questions may not be too far off the mark. For instance (following Marr), What does a cash register do? can be taken as the 3 Note that Churchland and Sejnowski are explicitly talking about Marr s work here so there is no distinction between levels of analysis and levels of explanation (or description).

96 Chapter 3 96 question that allows for the most abstract answer relative to the entity itself: arithmetic. How, generally speaking, does it do it? requires a somewhat less abstract answer, something like: by an algorithm that sums the rightmost digits, carries a digit if the sum is greater than 9, and then moves on the next column. And how, specifically, does it do it? requires an answer that is not abstract; instead the answer here a description of the particular physical mechanism that performs the operation, say an electronic processor. Another problem with the notion of questions is that we can rephrase the questions, at least in some cases, and get the same answer. For instance, the middle level question, How does the cash register do arithmetic? can be asked with no lose of content as, What algorithm does the cash register use to perform arithmetic? Hence, the questions may be an indicator for identifying levels of explanation, but it is the different types of answers that underlie the notion of levels of explanation. Therefore, it appears to be the case that a hierarchy of levels of explanation begins with the idea that there are a few different types of descriptions of a capacity or task. A description of a physical mechanism that carries out a particular task is one type of description and that description can be placed at one level, the lowest. A description of the task itself can be offered and can be placed at another level, the highest. And finally there are descriptions of the operation of the task that are distinct from (and can be given in different language than) the descriptions at the highest and lowest levels. The three levels of explanation that Marr uses are the level of the computational theory, the level of representations and the algorithm, and the level of hardware implementation. The highest of these, the level of the computational theory, provides a description of the task that a

97 Chapter 3 97 given mechanism performs. 4 It is at this level that what Marr calls the computational problem is identified. Identifying a computational problem entails identifying a particular task that an organism (or some physical system) performs. Often the articulation of the computational problem will rely on behavioral data that suggests that an organism is able to perform a task (i.e., solve a problem) in a particular way (Marr and Poggio 1976; Marr 1977). A theory at this level will answer the questions, what the device does and why, where the device is that part of the organism that performs the task in question (1982: 22). The what question is answered by articulating a theory of the device (what it is and what it does). So for a cash register, what the cash register does is arithmetic. The why question is answered by giving the constraints that explain why the device performs the task that it does and not other tasks, or the same task in a different way. This is basically specifying the rules for the device, and so the answers to the question why do cash registers perform arithmetic, instead of, say, multiplication, are the rules that are appropriate for totaling invoices. Marr s middle level, the level of representations and algorithms, is a description of the procedures or operations that carry out the computational task, or at least operations that are sufficient to carry out this task. The degree to which they describe the actual operations performed by the device depends on the access that is available to the device. In any case, this level does not reference the physical system that performs the task, it only describes the operation, which for Marr takes the form of an algorithm, plus representations of the inputs for the algorithm to operate on. 4 As has been pointed out by Bechtel (1994; Bechtel et al 1998) the computational theory is a misleading label for this level because it is not where a computational operation is described. As Bechtel, Abrahamsen, and Graham say, [Marr] called his highest level computational theory (a label that many have found misleading; it is somewhat akin to Chomsky s notion of competence and might best be called task analysis) (1998: 65).

98 Chapter 3 98 The purpose of working at this middle level, at least for Marr, is to test the assumptions concerning what the device does (what function it performs) that are made at the level of the computational theory. If the algorithm appears to mimic the device s performance, then this can be taken as evidence that the algorithm, or one similar, is a description of how the physical device carries out the task. That is, this level provides an answer to the question of how the device works (1977: 37). Marr, speaking about vision, says, once a computational theory for a process has been formulated, algorithms for implementing it may be designed, and their performance compared with that of a human visual processor. This allows two kinds of results. First, if performance is essentially identical, we have good evidence that the constraints of the underlying computational theory are valid and may be implicit in the human processor; second, if a process matches human performance, it is probably sufficiently powerful to form part of a general purpose vision machine (1982: 331). However, Marr also recognizes the ambiguities that can arise when selecting an algorithm that performs a particular task, in particular, in some cases we know that the same computational problem can be solved by different algorithms. For instance, as Marr notes, the Fourier transform can be described at the middle level as either a serial algorithm (the Fast Fourier transform) or as a parallel algorithm (1977: 37 8). Similarly, returning to the example of the cash register, any algorithm that performs arithmetic will be able to carry out the task required of a cash register. 5 However, some algorithms will work better with particular technologies (i.e., hardware) than others, which brings us to the lowest level. Marr calls the lowest level the level of the hardware implementation. At this level a description of the physical material that instantiates or realizes the device that performs this task is given. For the cash register this can be anything from an abacus to a computer. But with 5 Or, at least most will. The speed that the arithmetic is performed is factor in designing a cash register.

99 Chapter 3 99 respect to psychological capacities, this level focuses on descriptions of the relevant neurobiological material. Although Marr s background, before moving into cognitive science, was in neurophysiology, in much of his work that employs the idea of different levels of explanation he does not spend much time discussing this lowest level. 6 Marr s account straightforwardly applies to cognitive science (and is drawn from computer science [Churchland and Sejnowski, 1988: 741]). And the way in which Marr developed the idea of these levels (and used them himself) they focus to a large extent on modeling different psychological capacities. However, any process that takes an input and transforms it in order to produce an output is amenable to these three levels of explanation. For instance, taking an example from Bechtel (1994: 19), fermentation is a process that can be described at Marr s highest level as the anaerobic metabolism of organic compounds by microorganisms or their enzymes to products simpler than the starting material (Jarvis 1984: 113 4). At the biological level the description is of the particular molecules and their reactions. And at the middle level we could develop an algorithm that would transform a representation of the input (which could be the standard representation: C 6 H 12 O 6 for glucose) into a representation of the outputs (C 2 H 5 OH + CO 2 for alcohol and carbon dioxide). 3.2 An example from Marr In this section I review how Marr uses this account of levels of explanation for his theory of vision (1982). Marr suggests that vision is a process that produces from images of the external world a description that is useful to the viewer and not cluttered with irrelevant information 6 In two interesting papers (Marr 1977 and Marr and Poggio 1976) dealing with the general idea of different levels of explanation he does not discuss this lowest level at all.

100 Chapter (1982: 31). Marr explains this as three different stages of processing: from the two dimensional image of the external world that falls on the retina to the primal sketch, from the primal sketch to the 2½ dimensional sketch, and from the 2½ dimensional sketch to a three dimensional model of the objects in the world. Marr also suggests a series of more or less modular processes that together result in the formation of the 2½-dimensional (2½-D) sketch (1982: 102, 268). 7 These processes are: stereopsis, directional selectivity, structure from apparent motion, depth from optical flow, surface orientation from surface contours, surface orientation from surface texture, shape from shading, photometric stereo, and lightness and color as an approximation to reflectance. These processes take as inputs different representations from the first stage of the visual process. In general simpler processes such as determining directional selectivity can take representations that occur earlier in the process, and more complex processes, such as determining surface texture, require a fuller representation as an input (e.g., the full primal sketch) (1982: 265). Marr suggests that the goal of early vision, and possibly the termination of pure bottomup perception, is the construction of the 2½-D sketch (1982: 268 9, 279). The 2½-D sketch is a representation that occurs prior to decomposition of the scene into objects, (1982: 269). It is a viewer-centered representation of an image that makes certain features such as depth, surface discontinuities, and surface orientation explicit (1982: 277 8). Following this, the final representation that this system uses is the three dimensional model representation, which is a viewpoint invariant representation of objects in the environment. 7 And he says of modularity that The principle of modular design does not forbid weak interactions between different modules in a task, but it does insist that the overall organization must, to a first approximation, be modular (1982: 102).

101 Chapter What Marr has done is identify a general computational problem, vision. He has also identified several relatively independent (or modular) computational problems that collectively perform one stage of the task that he has identified for vision. I now want to consider one of these modular processes, which is relatively simple, the process of directional selectivity (1982, sec3.4; Marr and Ullman 1981). This is for the purposes of examining Marr s account of levels of explanation. What Marr offers here is a good example of the type of account that he was able to generate at the time for each of his three levels of explanation The computational theory At the computational level the task that is being analyzed is how the visual system uses partial information about motion specifically, only its direction defined to within 180 in order to discern the two-dimensional shapes of regions in the visual field based on their relative movement (1982: 165). That the visual system uses short-term, short range movement to detect objects was suggested to Marr by a series of experiments that showed that uniform direction of movement was sufficient to pick out a shape. 8 These experiments demonstrated that a collection of dots, as shown on the right in figure 3.1, moving uniformly on a screen are sufficient to discriminate the space of those dots from dots moving in a different direction. Directional selectivity is different than the perception of continuous motion, which Marr explains as a somewhat more complex process. The directional selectivity task is a simpler detection task that operates over a very small 50ms or so time scale (as compared to 250ms or more for real motion detection) (1982: 183). 8 Braddick (1973, 1974, 1980), Julesz (1971, chap. 4).

102 Chapter Figure 3.1. In the figure on the right, where motion is uniform, picking out the shape of the rectangle is easy. In the figure on the left the direction of motion is not uniform, but the speed within and outside of the rectangle is different (but uniform). However, discriminating the shape is not possible in this scenario. Adapted from Marr (1982: 167). Some of the constraints on how this process should be explained are: (1) the process should be carried out as quickly as possible (Marr and Ullman 1981: 152), (2) the mammalian visual system can detect very subtle movements objects that are moving only 1 /s (Marr and Ullman 1981: 153), 9 and (3) the process must take into account the aperture problem. The aperture problem (figure 3.2) arises when the edge of a moving object is larger that the aperture through which the movement is viewed. The same problem arises if, instead of an aperture, the unit that is measuring the movement like a center surround retinal ganglion cell is smaller than the edge of the moving object. 9 1 /s is one minute per second where a minute is 1/60 th of a degree (Graham 1965: 575; King-Smith et al 1977).

103 Chapter Figure 3.2. From Marr and Ullman (1981: 153). This figure illustrates the aperture problem. If edge E is moving and is viewed through the smaller aperture A, then it is impossible to determine if the direction is b or c (or any other specific direction within a 180 range). The first two of these three constraints, the need for fast and sensitive detection, suggested to Marr that the input to the system for measuring the direction of movement should be a primitive from an early part of the visual process. As the input, he selects the sharp intensity changes that mark the edges of objects, which are presumed to occur early in the visual process, and carry some information that can be used to determine the shape of the object (Marr and Ullman 1981: 153). 10 The third constraint, the aperture problem, arises because what is being measured is an edge moving through a small field. This requires Marr to suggest that the task has to be a local measurement of the direction of motion that is only within 180 of the actual direction (i.e., when looking through the aperture one can definitively say that the movement is, for example, down and/or to the left, and not up and/or to the right). Other processes that use the outputs of the directional selectivity process the separation of independently moving surfaces and the 10 Although this edge detection is not the first value detected on Marr s schema. The earliest are the measurements of the raw intensity of the image, but using raw intensity values would take the process off the course of eventually determining the shape of the moving object (Marr and Ullman 1981: 153).

104 Chapter detection of looming objects (Marr 1982: ) have to overcome this limitation on the information provided about direction of movement, but for directional selectivity itself measurement of the direction within 180 of the actual direction is sufficient. So for the computational level account of this process Marr: (1) identifies what the task is that is being performed; (2) uses different kinds of evidence to identify the constraints that offer insight into how the problem is solved; (3) identifies the inputs that are used by the system for this task; and (4) suggests what sort of outputs the system will have Representation and algorithm At the middle level, the inputs to this operation are represented as zero-crossings, which are the values that indicate where abrupt changes in the intensity of the image occur. The zero crossings are found by first applying a filter, the Gaussian, which blurs the image to remove small intensity changes that are not important for this task (1982: 56). The second step is to compute the second derivatives with a Laplacian operator. Where the Laplacian crosses zero on the x axis corresponds to these changes in intensity in the image [ 2 G * I]. These values are then used by the following operation in order to produce the required output: Measure the time derivative of the zero-crossing [i.e., δ/δt( 2 G * I)]. If this is positive at Z, the zero-crossing is moving to the right; if it is negative, it is moving to the left. If the edge has opposite contrast, the directions are reversed. 11 The first step is to determine the direction of the zero crossing. This is done by calculating the time derivate of the 2 G * I. When δ/δt( 2 G * I) is plotted we will get either of the following plots (b or c) in figure 3.3. If T is positive, as it is in (b), the zero-crossing is 11 See also the three steps suggested in Marr and Ullman 1981: 163.

105 Chapter moving to the right and if it is negative, as it is in (c), the zero-crossing is moving to the left. This calculation over a very small distance does not provide the speed of the movement, only the direction to within 180. Figure 3.3. The time derivative of 2 G * I and the units that are hypothesized to detect it. The distribution at the top (b) is the detection of an edge moving to the right, on the bottom (c) an edge moving to the left. From Marr and Ullman 1981: Neural implementation At the hardware level Marr suggests that the neural implementation of the process of detecting edges can be carried out by center-surround X-cells in the retina and lateral geniculate nucleus. If these cells are lined up such that detection of an edge will stimulate both appropriately, then together they can trigger a response from something like a logical AND gate when they are both active (figure 3.4 [1982: 169]). Several of these cells lined up in a pattern like the one on the right side of figure 3.4 would be able to detect an edge that falls anywhere between the two dotted lines.

106 Chapter Figure 3.4. P and Q are cells detecting the zero-crossing Z. The image in (b) is a series of these cells that are able to detect a zero-crossing anywhere within the dotted lines. From Marr and Hildreth (1980: 208). Marr suggests that the function for the time derivative is carried by Y-cells in the retina and lateral geniculate nucleus. As he says, The psychophysical studies of the transient channels and the neurophysiological recordings of the Y cells, to which the transient channels are thought to correspond, essentially demonstrate that these channels measure this time derivative, δ/δt( 2 G * I)! (1982: 170). The idea is that if X-cells are lined up so that they can detect edges the places where there is a sharp change in the intensity of the image that falls on the retina (the zero crossings) and the Y-cells are placed so that they can detect the direction of motion (the time derivative) as in the figure below (c; T represents the Y cell), then these cells can function as a local detector of directional selectivity. Figure 3.5. Same as in figure 3.4, except in (c), T is a Y cell that detects the direction of motion. From Marr and Ullman (1981: 154).

107 Chapter This has been a review of the way that Marr explains one aspect of early vision. There are three important points that have been covered. First is the way in which Marr uses a variety of information, which function as constraints, in order to determine what it is that this system does what this capacity is that individuals have. This is what constitutes the highest level, the level of the computational theory. Second, at the algorithmic level he details an operation that explains how the process is carried out. And then lastly, using information about the neural properties of the visual system, he basically matches the performance of the algorithm with the performance of the neurons found in the early visual system of mammals. One important point that I want to draw attention to is the difference between the descriptions of the input to the system that are offered at the highest and at the middle level. At the highest level, the level of the computational theory, we are told what the inputs are this is part of the description of the capacity. In the case of directional selectivity these inputs are the sharp intensity changes that indicate the edges of objects. At the middle level of explanation, the level of the representations and the algorithm, the representations of these inputs are selected and they are used as the input to the algorithm. For his algorithm for directional selectivity, the representation that Marr chose are the zero-crossings after the Gaussian and a Laplacian operator have been applied. The zero-crossings represent the intensity changes that fall on the retina. 3.3 Marr s middle level In this section and in the next chapter I am going to compare the types of descriptions offered at each of Marr s levels of explanation with the types of descriptions that we find in cognitive psychology and cognitive science. In this section I examine three types of models that are frequently used in cognitive science and explain why they fall within the scope of Marr s middle

108 Chapter level. A more lengthy treatment will be given in the next chapter to explanations of psychological capacities offered in cognitive psychology. For this I will use as an example some accounts that have been offered for the early part of the emotion process and I will explain how these explanations are similar to the ones that Marr places at his highest level of explanation. Here, however, I am going to look at three types of models found in cognitive science, which can be grouped into three rather broad categories: classical computational, connectionist, and biologically realistic. These types of models, although they differ significantly, all share the basic structure that is required of a middle level account. As I said earlier, Marr s middle level is the level of the representation and algorithm. Providing an explanation at this level requires selecting a way of representing the input or inputs to the system and then determining an algorithm that can operate on these representations in order to produce an appropriate output. The goal of providing an explanation at this level is to describe the operations that carry out the task or capacity being studied. Looking at these models will give us an idea of the range of different types of explanations that can potentially be offered at the middle level in a hierarchy that is concerned with the description of a psychological capacity. It will also be helpful to have these modeling techniques placed on the hierarchy of levels of explanation when we look at the relationship between psychology and neurobiology in chapter five so that we have a more complete idea of the range of ways of describing a psychological capacity Classical computational models Symbolic, or classical computational, models describe the operation of a capacity as a computer program. The representations are the symbols that are manipulated by the rules of the program,

109 Chapter although often instead of constructing the model of a capacity directly in a program language (such as LISP or Prolog), a production system is used. 12 Production systems consist of a body of rules that are in the form of conditionals. These conditionals, called production rules, specify an action to be taken if a condition is met. For example, one such rule might be: IF the goal is to classify a shape and the shape has three sides THEN classify the shape as a triangle. A cognitive task is modeled in this framework with a memory for storing information that is manipulated by a series of these production rules. As an example of the operation of a cognitive task using a production system, part of the procedure used by ACT-R to carry out a multicolumn addition problem (e.g., ) is shown in figure 3.6 (Anderson and Lebiere 1998a and 1998b). The table on the left is the English version for this procedure, showing the series of production rules that are followed when carrying out this task. The table on the right is the beginning of the same procedure in the ACT- R syntax. As is shown in the English version, when the first part of the rule (the condition) is satisfied then the action specified is taken and the next rule is engaged. In cases where the condition is not satisfied, then the action is not taken and another rule is investigated. For instance, in the step marked Extract-Answer in figure 3.6, the condition concerns the state after the first column of numbers have been summed and the answer is greater than 9 (thus requiring a digit to be carried). But if the sum was not greater than 9, then this condition would not be satisfied and a different rule would have to be engaged. 12 Examples of production systems are Newell s Soar (Newell, 1990), Anderson s ACT-R (Anderson and Lebiere, 1998a and 1998b), and Just and Carpenter s CAPS (Just and Carpenter, 1992).

110 Chapter Start-Problem IF the goal state is to do an addition problem but no column has been identified THEN set a subgoal to add the digits in ones column and note that the tens column is the next one to work on Read-Number 1 IF the goal is to add the numbers in the column and the first number has not been encoded THEN encode the first number in the column Read-Number 2 IF the goal is to add the numbers in the column and the second number has not been encoded THEN encode the second number in the column Add-Numbers IF the goal is to add the numbers in the column and another number is their sum THEN note that other number as the sum Extract-Answer IF the goal is to add the numbers in the column and the sum has been computed and the sum has a ones digit and a tens digit THEN note the tens digit as the digit to be carried and set the answer to the ones digit Process-Carry IF the goal is to add the numbers in the column and there is an answer and a carry THEN change the answer to one more and remove the marking of the carry Start-Problem =goal> isa ADDITION-PROBLEM column nil ==> =newgoal> isa ADD-COLUMN columns Ones note =carry carry Zero =goal> column Tens carry =carry!push! =newgoal Read-Number1 =goal> isa ADD-COLUMN number1 nil column =col =object> isa VISUAL-OBJECT value =num1 row Top column =col ==> =goal> number1 =num1 Read-Number2... Figure 3.6. The table on the left is the beginning of a procedure for addition in English, the table on the right is the same procedure in the ACT-R syntax. Adapted from Anderson and Lebiere (1998a: 7 and 1998b: 31). In the column on the right in figure 3.6 is the beginning of this same problem in the ACT- R syntax. This architecture encodes and stores information in chunks, which are manipulated by the production rules. An example of a chunk (which is not in figure 3.6) is the information = 11 stored in ACT-R s memory in the following way: Fact6+5 isa ADDITION-FACT addend1 Six addend2 Five sum Eleven The first line: Fact6+5 is the chunk s name, isa is a slot that specifies the type of chunk, and the next three slots (addend1, addend2, and sum) are the values for this particular addition fact.

111 Chapter Looking at the example in figure 3.6 we have under the Read-Number1 production two chunks for the condition to be satisfied, the goal is to add the numbers in the column and the first number has not been encoded : =goal> isa ADD-COLUMN number1 nil column =col =object> isa VISUAL-OBJECT value =num1 row Top column =col The first chunk is encoding a goal; isa, number1, and column are this chunk s slots; and ADD-COLUMN, nil, and col are values assigned to those slots. Anything followed by an equal sign is a variable, so goal is assigned the current goal and col is assigned to the current column. ADD-COLUMN, in the isa slot, specifies the type of goal. And nil in the number1 slot is a bit of syntax that indicates that there is not a value in that slot. The second part of the condition indicates what must be searched for: the number, which is a VISUAL-OBJECT, in the top row of the column. The action to be taken is to encode the first number in the column, which is represented as: =goal> number1 =num1 This encodes the number in the number1 slot of this goal, replacing the nil that was in this slot. This is a simple example of how this model, ACT-R, would carry out part of an addition task. There are more details to this production system that I am not going to discuss here. The point is simply to demonstrate the general idea of how the operation of a cognitive task is modeled in this framework. As we have seen ACT-R utilizes a specific type of structure, the

112 Chapter chunks, within which information is stored. And the production rules specify how these chunks are to be manipulated such that a cognitive task is performed Connectionist models A connectionist (or parallel distributed processing) model is a way of modeling a process that relies on the connections between simple units in order to transform the inputs into outputs. In this type of model the units are loosely based upon neurons. A diagram of a connectionist architecture is shown in figure 3.7. The inputs to the system are values, here represented as X1 1, X1 2, X1 3, X1 15, and each node in the input layer is given one value. From the input layer the values are passed along the connections to the nodes in the hidden layer. These connections are weighted so that each value is multiplied by a predetermined weight. These new values are then summed in the nodes of the hidden layer and passed through a function (a sigmoid) that limits the output of the node to a value between 0 and 1. The value that is calculated by each of the nodes in the hidden layer is passed on to the output layer. In the figure below the output layer has two nodes so this model outputs two values.

113 Chapter X1 1 X1 2 X1 3 X1 4 X2 1 X1 5 X1 6 X1 7 X2 2 X3 1 X1 8 X1 9 X2 3 X1 1 X1 10 X1 11 X1 12 X1 13 X1 14 X1 15 X2 4 hidden layer output layer X3 2 X1 2 X1 3 X1 4 X1 5 X1 1 (W 1 ) X1 2 (W 2 ) X1 3 (W 3 ) X1 4 (W 4 ) X1 5 (W 5 ) X1 6 (W 6 ) Σ Sigmoid X1 16 X1 6 X1 7 (W 7 ) input layer X1 7 Figures 3.7 and 3.8. Figure 3.7 is a connectionist network with one hidden layer. Figure 3.8 is the process that occurs in one node in the hidden layer. Both figures adapted from Smith (1997: 459, 461). A successful transformation of the input value into an output value is mainly accomplished by finding, usually by trial and error, suitable weights for each of the connections between the nodes. Often this is done by including an algorithm that the model uses to change its weights in order that it can produce the desired outputs. If a model is given a number of examples of what it is supposed to accomplish (input values and the correct output values), the learning algorithm alters the weights until the model can produce the correct output Biologically realistic models As the name implies biologically realistic models focus on specifying the operation of neurons in a more biologically realistic manner than is done with connectionist modeling. The process that is represented in a biologically realistic model is the flow of current through neurons and from one neuron to another. This is done by representing the neuron as a series of compartments, as is shown in figure 3.9. Each compartment is then treated as an electrical circuit, which for a whole

114 Chapter neuron can be pictured as the diagram in figure Each compartment has an electrical potential (its membrane potential) and the current flowing into or out of a compartment can be calculated based upon the difference between the electrical potentials in adjacent compartments. Figure 3.9. (A) is a drawing of a pyramidal cell showing its dendrites, cell body (soma), and the beginning of the axon. (B) is a simple compartmental model of the same cell. From Bower and Beeman (2003: 8). Figure A series of interconnected circuits each of which represents the electrical potential (the membrane potential) of a compartment. From Segev (2003: 67).

115 Chapter In addition to membrane potential each compartment is assigned additional parameters in order to represent other properties of that part of the neuron. Parameters can include basically all of the variables that influence the flow of current. In most models parameters are set for membrane and axial resistance (the amount of current that is lost over a given distance), the membrane s capacitance, and the membrane s equilibrium potential. These are the passive parameters that are constant whether or not electrical signaling is occurring. Other parameters include those that directly affect signal conductance, for example, the type and number of voltage dependent channels (and conductance values for each), and the current from other neurons that enters through synapses. This technique has been used to model single neurons, sometimes with thousands of compartments (as in a model of a Purkinjie cell from the cerebellum constructed by De Schutter and Bower [1994], which had 4550 compartments) as well as networks of neurons. One multineuronal model that I will describe briefly was constructed by Michael Vanier (2001). Vanier s model of the primary olfactory cortex included compartment pyramidal neurons and 931 single-compartment inhibitory neurons. The process of moving from a single neuron model to a model of a multi-neuron network like Vanier s involves, in addition to determining the number of neurons to use, determining how the individual neurons should be connected. This in turn entails determining which compartments are adjacent and how to represent the transfer of current at the synapses.

116 Chapter Figure Schematic diagram of how some neurons are connected in Vanier s model of the piriform cortex. A pyramidal cell is in the center, the circles are feedforward and feedback inhibitory neurons. From Vanier (2001: 342). The inputs Vanier used in his model were the firing patterns of 1000 mitral cells in the olfactory bulb. 13 One output of the model that he focused were the extracellular field potentials at various depths in the cortex from which current source density plots (CSD) could be constructed. CSDs are similar to EEGs except that they measure extracellular potentials in three dimensions instead of two. Vanier then compared the CSDs that his model generated as its output to CSDs generated by data collected from rats. By manipulating the connections between the pyramidal neurons in the model he was eventually able to get outputs that matched the data. 13 The pattern of inputs here is as follows: odors are the inputs to olfactory sensory neurons, which then project to the olfactory bulb, and then the olfactory bulb projects to the olfactory cortex, which is what Vanier is modeling.

117 Chapter Marr s middle level The reason for laying out these different types of modeling techniques is to illustrate the range of descriptions that can be placed in a hierarchy between the highest and the lowest levels of explanation, that is, between Marr s level of the computational theory, where a description of what the capacity does is offered, and the hardware level, where a description of the biological material is given. There are clearly significant differences among the three types of models that I have just described. Nevertheless, all of these types of models fall within the scope of Marr s middle level because they all take inputs that are represented in the appropriate way and transform them such that a particular type of output is produced. I do, however, want to address the fact that the biologically realistic model appears somewhat different than the other two types of models. When working with classical computational and connectionist models one specifies a capacity (or function) that the model performs and then uses the resources of that modeling technique in order to demonstrate (what might be) the operation of the capacity. However, when we look at the biologically realistic models, Vanier s for instance, we see that he does not refer to anything like what Marr characterizes as a computational theory. 14 However, it is not particularly significant that there is not a specific description of the capacity in this case. Biologically realistic models still belong on the hierarchy of levels of explanation. If we turn to Marr for a moment we see that what I am claiming is not exactly the same as saying that the goal of the middle level description is to explain How can this computational theory be implemented? (1982: 25). Marr is, in effect, suggesting that the middle level 14 It can be pointed out, however, that Vanier s model does perform a function. When given the appropriate input, the model produces current source density plots (CSDs) that match experimental data, although the olfactory cortex, of course, does more than just generate extracellular field potentials.

118 Chapter explanation has to demonstrate the operation of the computational theory. This appears to be a commitment to thinking of investigations proceeding by working down the hierarchy. In other words, a process is described at the level of the computational theory and then, as Marr says, In order that a process will actually run, however, one has to realize it in some way and therefore choose a representation for the entities that the process manipulates (1982: 23). This is the way that Marr may have proceeded in practice, but we do not have to be bound to this way of thinking about the relationship between the levels of explanation. What I am trying to do is step back from his account and give an analysis of it, and so the correct overall analysis might look somewhat different than his way of implementing his account. In any case there are three important points regarding the types of models that can be found at a middle level of explanation. First, when we say that a model falls within the middle range, all that we are claiming is that it is not a description of the hardware itself or a description of what the capacity does. We are asserting that it has an input-output structure that is sufficient to demonstrate the operation of a process (whatever that process might be). Second, although levels of explanation are not completely independent of each other, there is not any apparent reason why we have to work down the hierarchy (as Marr seems to suggest) instead of up it. Some models, for instance classical computational models, do not make explicit the entities and activities at the hardware level that perform the operations that are being modeled. Other models, the biologically realistic models, may not make explicit a description of the capacity that they are modeling, while they are explicit about the hardware that carries out the operations that are being modeled. It might be preferable that a model do both, but this is not always an option.

119 Chapter Third, we are confronted with the issue of how we know that one of these models falls within the middle range if the modeler is only explicitly committed to offering a model of the computational theory or the hardware. This is to say that a biologically realistic model carries out the processes that a series of neurons are believed to perform. And a classical computational model carries out the capacity that has been specified at the level of the computational theory. So based just on this, how do we know that the model falls between the highest and the lowest levels of explanation? This is an issue that I cannot fully resolve here, although I do address it in chapter five. But in outline, the answer is that we have to allow that certain assumptions are being made. On the one hand we acknowledge that the process that is carried out in the olfactory cortex is a psychological process simply because it falls with the range of the things that we call psychological (maybe on the edge of the range but in it nevertheless). Therefore, a biologically realistic model is a model of a psychological capacity (even if it is not committed to a description in the language of cognitive psychology). 15 On the other hand, we are willing to assume that psychological capacities are carried out by some sort of biological hardware, and so the classically computational model, as well as the connectionist model, is committed to there being a hardware level. With these two very general commitments we can establish that a range of different types of models fall within the middle range of the levels of explanation. Consequently, although we may recognize that a biologically realistic model and a classical computational model are working from different directions, given that they both have 15 By psychological capacity I mean a capacity of the type that we call psychological, which may or may not be a description of a capacity in the language of cognitive psychology.

120 Chapter an input-output structure, and are both seeking to explain a psychological capacity, they can both be placed in the range of Marr s middle level.

121 Chapter Models of Cognitive Appraisals and the Level of the Computational Theory In this chapter I examine the cognitive appraisal theories that have been developed by several psychologists to explain the early part of the emotion process. Looking at these theories demonstrates that they are what Marr specified as a description at the computational level of explanation. This shows us that Marr s level of the computational theory is a relevant account of the type of description that is used by psychological theories of human capacities (table 4.1). The appraisal theories that I will use are a good example because they are relatively simple and, although they have some shortcomings, the general form of the account is largely agreed upon by researchers working on emotion. I will focus exclusively on these accounts of the early part of the emotion process, however, the claim that they are computational theories is intended to generalize to other psychological accounts of human psychological capacities. Marr s level of the computational theory psychological descriptions of capacities Marr s level of representation and algorithm classical computational, connectionist, and biologically realistic models Marr s level of hardware implementation Table 4.1. The classical computational, connectionist, and biologically realistic types of modeling (broadly speaking) occupy Marr s middle level. The task in this chapter is to establish that the accounts that are offered in cognitive psychology occupy Marr s highest level. In chapter five I will examine Marr s lowest level of explanation. The main criteria that I will use for identifying an account that is at Marr s level of the computational theory are that it: (1) identifies what the task is that is being performed; (2) uses different kinds of evidence to identify the constraints that offer insight into what the capacity does; (3) identifies the inputs that are used by the system for this task; and (4) suggests what sort

122 Chapter of outputs the system will have. As a reminder, the inputs and the outputs mentioned in the third and fourth criteria are the actual inputs and outputs that this capacity is believed to use, not the representations of them that an algorithm uses to demonstrate the operation of the capacity. The representations of the inputs and the outputs belong at the middle level of explanation, the level of the representation and algorithm. In what follows I lay out the way in which the cognitive appraisal theorists have identified the appraisal task, and some of the constraints that have been used to construct these theories. Then, at the end of this chapter, I will address some of the differences between these theories and the types of explanations offered at Marr s middle level, the level of the representation and algorithm. 4.1 Background for the models Appraisal theories The term cognitive appraisals refers to some accounts of the early part of the emotion process. The appraisal capacity is the ability to transform the information contained in the perception of an event in the environment into an emotion response. I will give concrete examples of how the appraisals are described in section 4.2, but one way to understand them is as a system composed of a set of variables. Appraising a stimulus (object, event, or encounter in the environment 1 ) entails setting specific values for the variables. The values that are set determine which emotion 1 Events occurring in the environment are taken to be the main input to the system. This does not rule out other inputs such as internally generated thoughts or memories that can be inputs to the system. But insofar as we want to offer a description of the capacity based on tractable and basic instances of the operation of the capacity, these internal inputs are often although not always put aside.

123 Chapter response will be generated. 2 These responses (which vary for different discrete emotions) are composed of autonomic nervous system changes, as well as other physiological changes in the body, tendencies towards certain behaviors, and subjective experience of the emotion. The examples that I will use of specific accounts of the cognitive appraisal capacity are meant to be representative of the descriptions that are offered in cognitive psychology for this capacity. However, there are other approaches that differ rather significantly. For instance, Izard (1993) suggests that that the early part of the emotion process should be thought of as reflex-like rather than as a cognitive process, at least for most cases of emotion elicitation. And from a different perspective, Parkinson, while not denying that the early part of the emotion process is in some sense cognitive, suggests that social interactions should be the focus of explanations of the occurrence of emotion responses, not an internal appraisal capacity (Parkinson 2001, 1996; Parkinson and Manstead 1993). 3 I do not have space here to defend the cognitive appraisal 2 There is some disagreement on the correct terminology to use here. Some would say, as I do, that the appraisals are the earlier part of the emotion process and the emotion response is the later part of the process. Others would say that the appraisals are the cognitive antecedents of emotion, where emotion refers to what I call the response. In any case, what follows are some examples of what this response is composed of. Lazarus says action tendencies, subjective experience or affect, and physiological response (1991b). Kappas says behavior, physiological responses, expressions, or subjective experience (2001: 159). Frijda and Zeelenberg have (1) the feelings of pleasure and pain, here referred to as affect, (2) the various physiological and expressive motor responses and their parameters and patternings, (3) motivational states that we designate as states of action readiness, and (4) intentional structures and the instrumental behaviors implementing them, such as a plan to escape from danger, and the behaviors to achieve that (2001: 142). Roseman (1984: 19 20) says phenomenology (thoughts, images, subjective feeling), patterns of bodily response, a gestural component (including facial expressions, vocal signals, and postural cues), a behavioral component, and an emotivational component that consists of goals to which particular emotions give rise, such as avoiding some situation (when frightened) or inflicting harm upon some person (when angered). See also Smith and Kirby (2000: 85). 3 A distinction can also be made between psychologists working on the early part of the emotion process the cognitive aspects of emotion and psychologist working on the later, bodily aspects of emotion (e.g., Levenson 1994). These two interests need not conflict since it is not necessary to deny the importance of the other just because it is not one s area of study.

124 Chapter approach against these other perspectives and in any case such a defense is not relevant to the point that I am trying to make in this chapter, which concerns the format of the explanation used by the cognitive appraisal theorists. Nevertheless, it is worth acknowledging that there are other approaches to explaining the emotion process. Before looking at some of the models that have been offered for the appraisals, I want to address a terminological issue. The appraisals, insofar as they take one class of information as their inputs and output a different class of information are examples of what I am going to call an ability or capacity that humans have. Alternatively, the appraisals can be called a system, given that when an input is presented an output is produced. And this transformation from input to output is a task that is described by models of the appraisals. Therefore I also at times refer to the appraisals as a task performed by a system Constraints A constraint is an indication of what a system does. A particular constraint is an indication that the system must or must not do something. Roseman and Smith discuss several constraints that appraisal theories are specifically design to address (2001: 3 6). The first of these is the need to account for multiple discrete emotions. Beginning with behaviorist theories there have been attempts to account for emotion only in terms of degree of arousal, or arousal plus valence. However, more recent data, particularly about facial expressions (e.g., Ekman 1971; Ekman 1994; Ekman and Friesen 2003) suggest that there are distinct emotions (anger, sadness, fear, happiness, etc.) and not just states of high or low arousal. The second constraint is the need to account for the generation of different emotions in response to the same event, either across different individuals or for the same individual at

125 Chapter different times. For example, for a case of the same event causing different emotions in different people we can imagine that in response to the end of a romantic relationship, some individuals may feel sadness, others anger, and still others guilt. Relief, hope, and the absence of emotion are among other possible reactions (Roseman and Smith, 2001: 4). The third constraint that Roseman and Smith discuss is the need to account for the range of events that cause the same emotion. Any theory of emotion has to be able to accommodate the fact that there does not appear to be any objective feature or property shared by all of the stimuli that can cause a particular type of emotion. 4 As Roseman and Smith say, sadness may be elicited by the death of a parent (see Boucher & Brandt, 1981), the birth of a child (see, e.g., Hopkins, Marcus, & Campell, 1984), divorce (eg., Richards, Hardy, & Wadsworth, 1997), declining sensory capacity (Kalayam, Alexopoulos, Merrell, & Young, 1991), not being accepted to medical school (Scherer, 1988), or the crash of one s computer hard drive (2001: 4). There are other issues that Roseman and Smith discuss, but these three are the main ones that motivate the approach that the cognitive appraisal theorists have taken, and are also the most useful for explaining what the capacity is that the cognitive appraisal theories are trying to explain. Therefore, when offering an account of the appraisals it is necessary to explain this capacity in light of the three constraints: the account must be able to explain the existence of a set of discrete emotions, how individuals can respond differently to the same stimulus, and how a large number of stimuli can all elicit the same emotion. 5 4 This point for the emotions can be compared with the case for the startle response, which is reliably caused by objective features of the stimulus, namely, a sudden and intense tactile, visual, or acoustic stimulus (Koch 1999: 108). 5 In Marr s terms these are the constraints that determine what the early emotion process this capacity is.

126 Chapter These are some of the more general constraints that apply to the early part of the emotion process. Any theory has to take these into account, but of course it also has to take into account more specific evidence that tells us more about what this capacity does. I will review some of this evidence in this chapter, but I do not want to deviate too much from my main interest which is examining the type of explanation that is being offered for this appraisal capacity Initial evidence for the appraisal process This section reviews some early evidence for one general constraint on these theories, namely, that other information that an individual has, in addition to the information that is attained by viewing a stimulus, influences the response that is generated. 6 Lazarus began developing the principles that eventually evolved into his cognitive appraisal theory while working on stress in the 1950s and 60s. This work on the cognitive content of stress was in large part motivated by arguing against a behaviorist concept of stress. The general behaviorist view was that what causes stress (the stressor) can be objectively defined such that if a particular stimulus is introduced it will necessarily cause a stress response. However, as Lazarus said later, Early on, and on the basis of emerging research findings, it seemed obvious that the arousal and the effects of stress depended on how the individual evaluates and copes with the personal significance of what is happening (2001: 38). There are several experiments that Lazarus and his colleges carried out in the mid-1960s, two of which are explained below (Speisman et al 1964; Lazarus and Alfert 1964). Although these experiments were carried out in the context of the study of stress, they came to be viewed by Lazarus and others as evidence for some sort of cognitive appraisal. In 6 This constraint is not independent of the second and third constraints discussed in the previous section.

127 Chapter these two studies Lazarus and his colleagues manipulated the way in which the subjects appraised a stimulus, and then found that the subjects autonomic responses could not be predicted just by the presence of a particular emotion-causing stimulus. Instead, information provided to the subjects influenced how the stimulus was appraised and is, in part, a predictor of autonomic response. (1) Speisman et al (1964). Experimental reduction of Stress based on ego-defense theory. In the first study the stimulus was the movie Subincision, which shows a ritual operation performed in an Australian stone-age culture: On the film is a young boy, 13 or 14 years old, being restrained by three or four older men. He exhibits some agitation and distress as 3 or 4 inches of the underside of his penis are cut to the depth of the urethra with a piece of sharpened flint (Speisman et al 1964: 368). 7 In order to vary the appraisals that were made by the subjects three different sound tracks (voiceovers) were created to accompany the movie. In one the viewer was meant to understand that the ritual did not do any permanent harm and the boys looked forward to it as a rite of passage (denial sound track). A second sound track was intended to lead to intellectualizing modes of thought (Lazarus and Opton 1966: 244). Here the anthropological qualities of the movie were pointed out and the operation was explained in a detailed but technical manner (the intellectualization sound track). The third sound track was meant to cause negative appraisals of the movie by pointing out the horror of the situation, the dread of the boys, and the harmful consequences that would befall some of the victims (Lazarus and Opton 1966: 244 5; the trauma sound track). The movie was also shown to a fourth group of subjects in its original silent form. 7 Lazarus (1991a) continues The film shows a series of these procedures, the insertion of maggots into the wound, and other ceremonial activities (141).

128 Chapter Measurements of skin conductance were taken every ten seconds during the movie. 8 This data is shown in figure 4.1, where the most striking difference is between the subjects in the trauma sound track condition and the subjects in the two positive conditions, in particular the intellectualization soundtrack condition. 9 The skin conductance measure was significantly higher for the subjects in the trauma sound track condition than those in the intellectualization soundtrack condition for 89 of the 100 data points that were collected during the showing of the film (at the.05 confidence level). And this same measure was significantly higher for the subjects in the trauma condition than it was for those in the denial condition for 57 of the 100 data points. So the trauma sound track, which presumably induced negative appraisals of the content of the movie, appears to lead to higher levels of autonomic arousal (as measured by skin conductance) than the two sound tracks that did not induce negative appraisals of the movie subjects were used, 35 in the denial condition, 35 in the intellectualization condition, 14 in the trauma condition, and 14 in the silent condition. 9 Note that because of the variability of the data for all of the conditions some of the differences are significant and some are not. For example, at the.05 confidence level, 89 of the 100 data points reach significance for the trauma versus intellectualization conditions, and for the intellectualization versus silent conditons, 26 of 100 do.

129 Chapter Figure 4.1. Skin conductance is on the y axis. The skin conductance levels for the subjects in the trauma sound track condition (the highest line) are significantly higher than the denial sound track group (solid line) for 57 of the 100 data points, and significantly higher than the intellectualization sound track group (dotted line) for 89 of the 100 data points (.05 confidence level). From Speisman et al (1964: 373). (2) Lazarus and Alfert (1964). Short-circuiting of threat by experimentally altering cognitive appraisal. One problem with the Speisman et al (1964) study is that because each movie had a different sound track, the stimulus was not the same in each condition. In particular Lazarus and his colleagues were concerned that the denial and the intellectualization sound tracks might have merely distracted from the movie rather than caused different appraisals about what was occurring in the movie. The effects of the trauma sound track make this possibility less likely. However, Lazarus and Alfert (1964) did a follow up experiment in which one of the conditions was the silent version of the movie preceded by an orientation statement that informed the subjects about the denial theme: the boys look forward to the procedure; it is a rite of passage; it does not do any permanent damage. The other two conditions were the movie with the denial

130 Chapter sound track (as in the previous experiment) and the silent condition without an orientation statement. In this study the denial orientation statement (with the movie shown silently) produced the lowest autonomic responses and the silent condition produced the highest as shown in figure Therefore, when two of the conditions did use the same stimulus, the movie shown silently, the information that one group acquired from the orientation statement, which was information that the other group lacked, appears to affect the autonomic responses. In particular, the denial orientation statement, which informed the subjects that the movie they were about to see had positive qualities (e.g., the boys looked forward to the procedure and considered it a rite of passage), led to much lower levels of skin conductance than the condition in which the movie was silent and there was not an orientation statement subjects were used. With regard to the degree of differences between the different conditions, In the previously cited study [Speisman et al (1964)], doing an analysis of the effects of the defensive-soundtrack conditions at such peak points yields significant effects even when the total means do not. In the present case, the differences even for total means reach significance in heart rate, and nearly so in skin conductance, and there is no need for the more costly procedure of point-to-point comparisons (Lazarus and Alfert 1964: 198).

131 Chapter Figure 4.2. Skin conductance (in micromhos) is on the y axis. The condition in which subjects were given the denial commentary prior to viewing the movie and then watched the movie silently is the lowest line. Those levels of skin conductance can be compared to the highest line, the condition in which the movie was also shown silently, but without any type of information provided prior to the movie. From Lazarus and Alfert (1964: 199). This early work by Lazarus illustrates a rather general, but important constraint on any theory of the early part of the emotion process. Namely, that the response that is elicited by a particular stimulus is not determined by the objective features of the stimulus, but by how the individual interprets or appraises the stimulus. After this work by Lazarus and his colleagues the next significant step was the development of theories that suggested what the different appraisal components might be. This was done initially by a number of psychologists who were working independently in the early and mid-1980s.

132 Chapter Models of the appraisal capacity Roseman Ira Roseman was one of the first to develop a relatively complete model that could explain what the specific appraisals are for different emotions. His initial model was presented at a conference and then published, with some revisions, several years later (1984). This revised model, shown in figure 4.3, has five appraisal components that together produce 14 discrete emotions. The appraisal components are: motivational state, situational state, probability, power, and agency. Circumstance-Caused Other-Caused Self-Caused Positive Negative Motive-Consistent Motive-Inconsistent Appetitive Aversive Appetitive Aversive Unknown Surprise Uncertain Hope Fear Certain Joy Relief Sorrow Discomfort, Disgust Uncertain Hope Certain Joy Relief Frustration Uncertain Disliking Certain Liking Uncertain Anger Certain Uncertain Shame, Guilt Certain Pride Uncertain Regret Certain situational state motivational state Weak Strong Weak Strong Weak Strong agency probability power Figure 4.3. The different appraisal components are motivational state, situational state, probability, power, and agency. The arrows point to the different values that each appraisal component can take. Each emotion type takes the values that its placement in the chart indicates. For example, for joy, the situational state is motive-consistent, the motivational state is appetitive, agency is circumstance-caused, probability is certain, and power can be either weak or strong. In cases where the emotion is placed such that it lines up with several values for an appraisal component (e.g., anger can be uncertain or certain) that indicates that any of those values can be assigned for that emotion. From Roseman (1984: 31). The basic idea is that each of these appraisal components can be assigned two or three possible values. Alternatively we can think of each appraisal as having two or three possible

133 Chapter outcomes. The combined values for all five of the different appraisals determines the emotion. 11 The appraisal components can be described as follows: The motivational state component distinguishes between states that the individual views as desirable (appetitive) versus states that are viewed as undesirable (aversive). The desirable are perceived as states-to-be-attained and the undesirable as states-to-be-prevented. Note that this is not an evaluation of whether the event itself is positive or negative; rather it is an evaluation of whether the event includes some important aspect that is perceived as a goal or some aspect that is perceived as a punishment. A punishment (or something perceived as a punishment) that is avoided is a positive event, but still includes an evaluation of a punishment. For example, on this model, relief, although it is a positive emotion includes an evaluation that some important aspect of the event is aversive. Conversely, sorrow, a negative emotion, includes an evaluation that some important aspect of the event is appetitive. The situational state component is an appraisal of whether the desirable or undesirable quality of the event is present or absent. The appraisal that something desirable is present, as well as an appraisal that something undesirable is absent, is motive-consistent. On the other hand, the appraisal that something desirable is absent or something undesirable is present is motive-inconsistent and contributes to a negative emotion. For instance, this appraisal component and the motivational state component that I just described are important for distinguishing between joy and relief. Joy, on this model, includes the appraisals that a desirable state is present, while relief includes the appraisals that an undesirable state is absent. The probability component is an appraisal of whether an event is definite (certain), only possible (uncertain), or of an unknown probability. On this component, an outcome of uncertainty contributes to hope instead of joy or relief, which involve an appraisal that the event is certain (that is, it has been determined). The possibility that the event can be appraised as having an unknown probability was added by Roseman in order to account for surprise, which is often considered a basic emotion (Tomkins 1962, Izard 1977, Plutchik 1980). The value unknown differs from uncertain in that for unknown the distinction between motive-consistent versus motive-inconsistent cannot be made, while for uncertain it can. The power component is for an evaluation of the individual s perception of their strength or weakness in a situation. If the individual perceives himself as having strength in the situation this contributes to frustration, anger, or regret. If the individual perceives himself as lacking 11 It should be pointed out that Roseman and the other appraisal theorists are not suggesting that these appraisals are, from the individual s point of view, deliberate actions or necessarily occurring within consciousness.

134 Chapter power in the situation, then this contributes to distress (discomfort), sorrow, fear, disliking, or guilt. For instance, what Roseman calls dislike is similar to anger except that the individual perceives himself as weak rather than strong. As an example Roseman uses this: consider someone being robbed at gunpoint. Will this person, quite unjustly treated but quite weak, be feeling anger? I contend that he would not, though he would probably feel some negative emotion towards his assailant. This emotion, in the structural theory, is dislike (1984: 27). And lastly, the agency component distinguishes between the perception that the event was caused by the individual himself, or by some other person, or merely as a result of the situation (that is, caused by events perceived as lacking an agent). This component also determines who or what the emotion is directed towards. This requires a subtle understanding of what the emotion-causing stimulus may be in a particular situation. For instance, take an individual who is presented with a gift by a friend. If the individual focuses on the gift and having just received it, that is, focuses on the general state of affairs, his emotion is (on this model) joy. If the individual focuses on the friend who has just given him a gift, that is, focuses on another person, his emotion is liking. I choose this early model of the appraisals in order to illustrate what is entailed in the move from Lazarus s early insights to a full model. Lazarus data motivate the idea that between the perception of an event and the emotion response there must be some sort of transformation that utilizes information that the individual already has. Roseman does not offer an account of what this specific information is that intervenes between the perception and the response, which would be impractical since the amount of information could be huge for any particular individual, and would vary widely from individual to individual. Rather he offers a model of what kind of system must be in place in order to efficiently utilize the information that an individual has prior to or in addition to the information from the perception of the event. A second reason for introducing this early model of Roseman s is that it is one of the simpler models that has been offered, and so it is a good way to easily explain the type of model that I am focusing on. It also relies upon a rather narrow body of empirical evidence that

135 Chapter Roseman collected. This is, of course, not ideal for the model itself, but it is a good way to introduce the types of empirical evidence that have been used to construct these models. Prior to developing his initial model, Roseman, along with Phoebe Ellsworth, collected written accounts from 200 people (students, faculty, and staff at Yale University). These people were asked: to think of an occasion in their lives when they felt a particular emotion (such as anger, guilt, frustration, love) and to describe in detail what happened on that occasion, including (a) what led up to feeling the emotion, (b) how the emotion was expressed, if it was, and (c) what happened once they felt or expressed their emotion, if anything. Respondents were also asked to explain, as best they could, why they felt the way they did on that occasion (1984: 16). Roseman then used these reports in order to determine what sorts of cognitive evaluations might be shared by one type of emotion but not by others. For instance, he says, a perception of having been unjustly treated seemed to characterize experiences of anger but not experiences of guilt. It also seemed characteristic of experiences of anger that the victim was unjustly treated by another person, rather than by circumstances. In this, they differed from frustration stories, which often featured some injustice but had no agent (My new car kept stalling) or negated human agency (They couldn t pay me as much as they had said) [that is, there is not someone willfully wronging the individual] (1984: 16 7). Based on his review of these accounts Roseman constructed his initial model of the different appraisal components and the values that each can take. 12 Roseman then tested the model by giving 120 subjects brief stories to read and having them rate (on an 11 point scale) how strongly the protagonist of the story experienced each of the discrete emotions generated by his model: joy, relief, hope, warmth-friendliness (liking), pride, distress, sorrow, fear, frustration, coolness-unfriendliness (disliking), anger, regret, guilt (1984: 24). Eight different scenarios were used in the stories and within each scenario the cues relevant 12 He also used some evidence from the emotion literature that for the most part focuses on what discrete emotion types there are, and what the characteristics are for these different emotion responses.

136 Chapter to the protagonist s emotion, i.e., the cues relevant to the appraisal components in Roseman s model, were varied. 13 For instance, within one scenario how the agency component is appraised is varied by giving different information: the teacher graded the exams very harshly and the protagonist failed (the agency value is other-caused); the protagonist did not study and failed (the agency value is self-caused). By varying the relevant information within each of the stories, 48 versions of each story were created. Each subject read and rated one version of each of the eight stories (eight stories per subject). The idea is that the subject reads the story and, using the available information that is presumed to be relevant to determining an emotion (as in the case of the reason why the student failed the exam), suggests what emotion the protagonist of the story would likely be experiencing. Based on the results from this study Roseman further refined his model to the state that is given above (figure 4.3) Methodologies In the next section I introduce a second model for the appraisals, but before doing that I will review the types of methodologies that have been used to generate the empirical evidence, which is then used for the modification of these models. I want to emphasize that this is not the main issue that I am addressing in this chapter, but there is presumably a need when discussing any psychological capacity to demonstrate that there is sufficient evidence for the way in which it is explained Some of the scenarios were: a student taking a final exam, a relationship in which one partner cheats on the other, a politician campaigning for reelection (1984: 24). 14 For other discussions about the methodologies for testing appraisal theories see Lazarus and Smith (1988: 291), Scherer (1997: 115), and Ellsworth and Scherer (2003: ).

137 Chapter There are two basic types of methodology that do not require the subjects to actually experience any emotion. One uses stories or vignettes in which the appraisal-relevant information is altered. Subjects then have to indicate what emotion they think the protagonist of the story would experience or what type of emotion they think they would experience in the situation. The study of Roseman s that I discussed in the previous section is an example of this methodology. 15 The second methodology requires subjects to recall an emotion experience they have had in the past and then to answer questions about the appraisal components. 16 For example, Frijda, Kuipers, and ter Schure (1989) had subjects recall an instance of each of eight emotions and to fill out questionnaires concerning each of them (1989: 214). In their study the subjects briefly described the recalled event and then in response to the questions had to rate on 7-point scales which value was most appropriate for 19 appraisal components (for example, for one appraisal component the 7-point scale ranged from very goal conducive to very goal obstructive). A third methodology, which is more difficult to employ, puts subjects in emotion causing situations and then different aspects of the situation are manipulated so that the appraisals that the subjects will make are likewise manipulated. Measurements of the emotion response are then taken in order to detect the presence of any emotion (i.e., the presence of a response versus no response) or the presence of a specific emotion. This methodology is, generally speaking, the one 15 This type of methodology is also used by Weiner, Russell, and Lerman (1979); Weiner, Graham, and Chandler (1982); McGraw (1987); Weiner, Amirkhan, Folkes, and Verette (1987); Stipek, Weiner, and Li (1989); Smith and Lazarus (1993). 16 This methodology has been used by Smith and Ellsworth (1985); Ellsworth and Smith (1988a and 1988b); Folkman and Lazarus (1988); Gehm and Scherer (1988); Frijda, Kuipers, and ter Schure (1989); Roseman et al. (1996); Tesser (1990); Mauro, Sato, and Tucker (1992); Reisenzein and Hofmann (1993); Reisenzein and Spielhofer (1994).

138 Chapter that Lazarus used in the studies that I described earlier, although at that time he had no notion of what different appraisal components might be. 17 For the first methodology, the most significant problem is that the subject is not in the emotion-causing environment and not experiencing the emotion him or herself. This leaves open the possibility that the subject may be relying on different cues in the stories than the ones that are relevant to the appraisal components. Alternatively, different processes might be employed when a subject is observing events that another individual (or character) is experiencing than when a person is experiencing the event him or herself. Similarly, for the second methodology, where subjects are asked to recall an emotion event and then answer questions about it, there are questions about how well this method can track the appraisal process. Here the main problem is that, if, as is generally assumed, the appraisal process occurs outside of conscious awareness, then asking subjects questions about these processes may not yield useful data. Moreover, there is the additional problem that the subject is being asked to remember a past emotion-causing event, which may not be recalled with complete accuracy. These problems for these two types of methodologies are, I think, significant ones. However, there are some things that can be noted. One is that the difficulty in gaining access to any psychological capacity should not prohibit the effort to understand the capacity. It just means that the data that is generated has to be understood as less than perfect. That being said the problems with these methodologies do not mean that the data is deeply flawed. Even if it is the case that subjects do not appraise a story in exactly the same way as they appraise an event that 17 This methodology has been used by Smith (1989); Smith (1992); Pecchinenda, and Smith (1996); Pecchinenda, Kappas, and Smith (1997); Pecchinenda and Kappas (1998); Kappas and Pecchinenda (1999); Kappas, Pecchinenda, and Bherer (1999).

139 Chapter they are experiencing, if they appraise it in a reasonably close way then the data may be useful. Likewise for the second methodology, even if the appraisal process occurs outside of awareness, that does not mean that individuals are completely cut off from ever accessing the appraisal components; it just means that they normally do not access them (although it could mean that they are always cut off from them). If they are not always cut off from them, then, as with the first methodology, some well designed experiments may yield some useful data. And this still leaves the third methodology that I mentioned above. This is the method where attempts are made to manipulate the appraisals that subjects make, a process that will then affect the emotion that they experience. This does not always require verbal reports on the part of the subjects. The subjects just have to be engaged in a controlled emotion-causing event and the experimenter has to measure some aspect of their response. To a certain extent it is preferable to the first two methodologies. The difficulty is presenting emotion-causing events and manipulating the aspects of the event that correspond to the appraisal dimensions in a laboratory setting. Experiments that have been carried out using this methodology have used as the emotion-causing events solving anagrams (Pecchinenda and Smith 1996), solving math problems (Smith 1992), and playing video games (Kappas 1997; Pecchinenda, Kappas, and Smith 1997; Pecchinenda and Kappas 1998; Kappas and Pecchinenda 1999; Kaiser, Wehrle, and Schmidt 1998). These experimental frameworks have been shown to be useful for manipulating appraisal components such as goal or motivational congruence (or incongruence) and coping potential, Coping potential refers to the evaluation of how well the encounter can be managed. It does not involve actually coping with the encounter, but just assessing the resources and ability to do so (Lazarus 1991a: 150). Smith and Lazarus (1993), Smith and Kirby (2001), and Scherer (1993, 2001) also include this or a similar appraisal component in their models. In Roseman s model the combination of the probability and the power appraisal components basically captures the same idea.

140 Chapter but, so far at least, they have not been used to examine other appraisal components. They also are limited in how strong an emotion response they are able to elicit. And finally for all the work in developing a methodology that does not rely on verbal reports, it is limited by an incomplete understanding of the patterns of bodily response that correspond to each emotion type. In all of the studies just cited measures of different physiological changes were taken (skin conductance, heart rate, finger temperature, recording of the electrical activity of facial muscles, and facial expression). These measurements indicate if the manipulation of the appraisal component affects the response that is generated. However, to asses the emotion that is being generated the subjects report has to be used. 19 In any case, this third methodology seems to be promising and is, to an extent, replacing the first two methodologies. 20 Overall, the important point to keep in mind with respect to all of these methodologies is that they are not generating evidence that there is a capacity here at all. That some sort of appraisal capacity exists at all has been agreed upon by these researchers. At this stage the evidence that is generated is used to refine a particular model. The evidence either confirms or disconfirms a hypothesized component or the hypothesized values for a component. In other words, the evidence is meant to constrain the finer details of the models. However, unlike the more general constraints that I discussed in section 4.1.2, the accuracy of this evidence takes more work to establish. 19 But this is not a major drawback, if as most theorists agree, the subjective awareness (or feeling) of an emotion is, along with the bodily changes, an output of the appraisal process. 20 An additional point to mention is that a model of the appraisals is meant to provide the structure that has to be in place in order to transform the perception of events in the world into discrete emotion responses. Therefore part of the construction of the model relies on providing a way of explaining however many types of emotion responses there are, no more no less. The data that is needed here is not data about the appraisal process; it is data about types of emotion responses. I am not, however, going to review that data here.

141 Chapter Scherer This section introduces a second model of the appraisals, one offered by Klaus Scherer (Scherer 1984, 1993, 2001; Leventhal and Scherer 1987). One reason to look at Scherer s account is to contrast it with Roseman s and show that among appraisal theorists there is a fair amount of agreement about what this early part of the emotion process is and how it should be described. A second reason is to set the stage for a discussion of the resources that are available to an account that includes a description at Marr s level of the computational theory, but also tries to address questions about how this process is carried out (that is, an account that is offered at Marr s middle level). In this section I will describe (what we can call) Scherer s computational theory for the appraisals. He uses this model as a basis for a more elaborate account that seeks to explain how this process is carried out (Scherer 2001) and I will examine this middle level model in section Scherer (2001) bases his account of the appraisals around four appraisal objectives: (1) relevance detection, (2) implication assessment, (3) coping potential determination, and (4) normative significance evaluation. Each of these appraisal objectives are carried out by a series of what Scherer calls stimulus evaluation checks (SECs), which are listed, along with the values that can be assigned to each, in the table below. Relevance detection consists of three checks that determine fairly simple qualities of the stimulus and which allow the organism to determine if the event requires deployment of attention, further information processing, and possibly adaptive reaction or whether the status quo can be maintained and ongoing activity pursued (2001: 94 5). The second of the appraisal objectives, implication assessment, is considered by Scherer to be the most important of the four. This appraisal objective consists of five stimulus evaluation checks that determine the immediate

142 Chapter consequences of the event for the individual as well as the longer term implications of the event. The third appraisal objective, coping potential determination, consists of three stimulus evaluation checks that collectively determine the individual s available resources for future action. And the normative significance evaluation determines how the event fits into a set or hierarchy of norms and values that the individual holds for himself, and recognizes as being held by the social group that he is a part of. Appraisal Objectives Relevance detection Novelty check Suddenness Familiarity Predictability Intrinsic pleasantness check Goal relevance check possible values for each SEC low, medium, or high low, medium, or high low, medium, or high low, medium, or high low, medium, or high Implication assessment Causal attribution check Cause - agent Cause - motive self, other, or natural intentional, negligence, or chance low, medium, or high Outcome probability check (degrees of certainty) Discrepancy from expectation consonant or dissonant check Goal/need conduciveness high (conducive) or obstructive check Urgency check low, medium, or high Coping potential determination Control check Power check Adjustment check low, medium, or high low, medium, or high low, medium, or high Normative significance evaluation External standards check low, medium, or high Internal standards check low, medium, or high Table 4.2. Scherer s stimulus evaluation checks (SECs) and the values that each can take. The way in which this model explains which emotion response will be generated is basically the same as it is for Roseman s model. Each appraisal component, or in Scherer s terms stimulus evaluation check, is assigned one of two or three possible values. The combination of all of these values indicates the emotion type that is generated. For most emotions, however,

143 Chapter some of the evaluation checks are irrelevant and are not assigned a value, or can take any of the possible values. A chart of the different emotion types and the values that Scherer assigns for each is in the appendix to this chapter. Roseman s model and Scherer s model overlap a good deal. Both account for how the event corresponds to the individual s current goal or goals; the role of other agents or factors in the event (Scherer s causal attribution component, Roseman s agency component); the pleasantness or valence of the event (Scherer s intrinsic pleasantness, Roseman s motivational state); the probability concerning the outcome of the event; and the power that the individual perceives him or herself as having in the situation. There are also differences. For one Scherer includes the normative significance evaluation which does not correspond to anything that Roseman includes in his model. But perhaps more importantly Scherer offers a model that has many more appraisal components in it (16 versus 5). However, I do not think that has too much significance for my larger concern about the type of explanation that is being offered here. Roseman s model and Scherer s model illustrate that different theorists have fairly similar ideas about what the cognitive appraisal capacity does. Therefore, I take it that these are reasonably good explanations of the early part of the emotion process. They are based on a variety of different types of data, and the implications of the data and how the models should be constructed have been debated and to a large extent agreed upon (other similar models are Roseman et al 1996 and 2001[see the appendix]; Lazarus 1991a; Smith and Lazarus 1993; Smith and Kirby 2001). But regardless, my larger interest is not specifically in how good these explanations are but in what kinds of explanation they are. The lesson that I want to draw from these models of cognitive appraisals is that these descriptions and others of a similar kind belong at Marr s highest level of explanation, the level

144 Chapter of the computational theory, which is where the analysis of the task occurs. This means that these accounts of the cognitive appraisals are descriptions of what this capacity is. And conversely, they are not a description of how this capacity is carried out, which would be a middle representation and algorithm level description, or an account at Marr s lowest level the level of biological implementation. Roseman s and Scherer s models are accounts at the level of the computational theory because they (1) identify what this task is that is being performed; (2) use different kinds of evidence to identify the constraints that offer insight into what this capacity does; (3) identify the inputs that are used by the system for this task; and (4) suggests what sort of outputs the system will have. 21 Although I have not discussed it too thoroughly I did say that the inputs to the system are the perceptions of events in the environment and the outputs of this system are the bodily responses. Given the placement of this system it is not a sensory system that received inputs at the periphery it is difficult to specify these inputs accurately and precisely. The outputs of this system, the bodily changes that characterize the emotion response, are, on the other hand, easier to specify and measure. Concerning (2), among other constraints upon these models, they must be able to produce a certain set of discrete emotions; they must allow ways in which the same event can cause different emotions across different individuals or different emotions for the same individual at 21 Note that the inputs and outputs that I am referring to here are the actual inputs and outputs, not representations of them, which would belong at Marr s middle level, the level of the representation and algorithm. The actual inputs and outputs that the system uses are specified at Marr s highest level, the level of the computational theory.

145 Chapter different times; and must allow a way in which a range of events can cause the same emotion response. Further, more specific constraints are provided by experiments that utilize one of the three methodologies that I discussed above. The point here is that the theory of this capacity develops with a set of constraints in mind. Hence, specifying the theory of this capacity, requires acknowledging these constraints. In essence, determining the constraints is part of the project at this level of explanation. With respect to (1), when a model of these appraisals is constructed it is model of what this process is and what the process does. Essentially, the models offered by Roseman and by Scherer indicate what kind of system must be in place in order to accomplish this transformation from the input to the output. For example, Roseman suggests that anger is the result of the following appraisals: the value for the motivational state appraisal component is appetitive; the value for the situational state component is motive inconsistent; the value for the appraisal of power is strong; the value for the appraisal of agency is that it is other-caused; and the value for the appraisal of probability is either uncertain or certain, either value being possible for anger. What this means is that the capacity that humans have to generate an emotion response, in this case an anger response, is an ability to assign these particular values to each of these appraisal components. Roseman s claim is that in order to understand what this appraisal ability does, these components and these values have to be part of the explanation of the ability. And so the conclusion here is that, the accounts of the appraisal process that I have reviewed are, in their basic outline, similar to what Marr characterized as a description of a capacity at the level of the computational theory (i.e., the highest level). That is, these accounts are descriptions of what it is that this particular capacity is.

146 Chapter Process models of the appraisals A review of Marr s middle level Since these models occupy Marr s level of the computational theory, it follows that they are not accounts at Marr s middle level, the level of the representation and algorithm. In the next section I will examine an attempt by Scherer (2001) to extend his model in order to explain how the process is carried out, which would, prima facie, make the model a middle level account. I find that this attempt is largely unsuccessful. However, before going any further it might be helpful to review what kind of explanation a middle level account offers. For Marr, the middle level explanation is one that describes the operation of the capacity, but does so without reference to the particular hardware that carries out the operation. Rather, at this level the operation or operations that the hardware performs are described in terms of an algorithm and the representations that have been selected for the algorithm to manipulate. One might ask what is the difference, in the case of the appraisals, between an account offered at the level of the computational theory and an account offered at Marr s middle level? When Roseman offers an explanation like the one above for anger he is explaining this part of the emotion process as the assignment of those particular values for those appraisal components. A middle level account, on the other hand, would not explain what this task is, but rather provides a description of how it is (or might be) carried out. That is, it would detail an operation that would demonstrate how the capacity is carried out. It might seem easy to transform Roseman s account into a description that could demonstrate how this process is carried out since, in a way, it has the form of the process written into it. That is, an input is given to the system, values are assigned by the various components, the values are summed, and an output is produced. However, this misses on several counts.

147 Chapter Recall that for Marr the move from the highest level to the middle level entails completely switching frameworks. At the highest level everything that needs to be said about what the capacity is (or does) gets said in psychological language. At the middle level, for Marr at least, all of that talk about what the capacity is and the terms that are used to offer that explanation are dropped. Here representations are identified and how an algorithm transforms these representations is suggested. In the example of directional selectivity the representations that Marr chose are the zero-crossings after the Gaussian and a Laplacian operator have been applied. The zero-crossings represent the intensity changes that fall on the retina. For the appraisals, choosing representations is a significantly harder task. Since the system does not take inputs that are encoded at the periphery (as in the case of vision, which uses inputs that are encoded by the retina) it is difficult to know exactly what the inputs are, and then selecting appropriate representations for the inputs is a further step. That does not mean that it cannot be done for the appraisals, or that preliminary suggestions about what representations might be used cannot be proposed. However, a model like Roseman s simply does not offer this. And likewise for the algorithm: once there is a representation of the input, then the algorithm is used to illustrate how the input is transformed into an output. But again a model like Roseman s does not propose an algorithm. To underscore this point, it is not merely that these things representations and an algorithm are forgotten. The point is that since they have been left aside, the process has not in fact been specified, and, further, the process cannot be specified, in any rigorous sense, without them. Hence, the two accounts of the appraisals that I have reviewed in this chapter leave out all of the required information about the operation itself. The question of how this process is carried out has to be answered in a context that can provide representations of the inputs, and

148 Chapter operations that can demonstrate how the outputs are produced. But a model like Roseman s does not provide any of this. Rather what his model is for is to describe what the particular appraisal components are and what the values are that can be assigned to them. How this would be done is a different issue. I am not saying that an account at Marr s middle level could not be given for the appraisal process. The point I do want to insist upon, however, is that when an account is given such that it explains what a particular task is, it is not also explaining how the task is carried out. And more importantly, a middle level account would not resemble an account at Marr s highest level. This is because the move from the highest level to the middle level is not one of adding more detail or being more explicit about certain details. Rather the move entails switching frameworks to offer a different kind of description. In the next section I am going to look at a model offered by Scherer that does attempt to offer an explanation that is similar to what Marr characterized as a middle level explanation. One reason for looking at this model is to further clarify the difference between these two levels of explanation. 22 Also, in the next chapter I will offer an account of how we might conceive of the relationship between a psychological description of a capacity and the relevant neurobiology. To do this we need to have a clear idea of what a psychological description is, and so it is necessary to distinguish descriptions offered at Marr s highest level and his middle level now. 22 I take it that this is important because there is an intuitive appeal to believing that the computational level model and the language that it uses is describing (or comes close to describing) how psychological processes are carried out. But it is important for my overall project that a psychological description, like the one that Roseman offers, be understood as a very specific sort of explanation, an explanation of the type that Marr calls a computational level description.

149 Chapter A process model of the appraisals This model, offered by Scherer (2001: 99ff), is designed to explain the process that occurs rather than just the structure of the appraisal components. The motivation for this process model is described by Roseman and Smith as follows: Most structural models have been relatively silent with regard to the specific operations involved in making the appraisals. Despite acknowledging that appraisals can be made automatically and outside of conscious awareness, few structural theories attempt to articulate the process by which such evaluations might occur. Recently, however, building on a seminal proposal by Leventhal and Scherer (1987), there have been several attempts to develop process models, encompassing multiple modes of appraisal and specifying the cognitive principles and operations underlying these appraisal modes (2001: 12). 23 These process models attempt to specify the operations by which the appraisals are made. Therefore, they are describing how the process is carried out and not merely what the capacity is. 24 In order to create a process model Scherer basically extends the model of his that I described earlier by adding several new features (figure 4.4). The first concerns the level or stage of processing at which the stimulus information can be inputted to the system. 25 Scherer proposes three different stages of processing at which the stimulus evaluation check can occur: (1) the sensory-motor level, (2) the schematic level, and (3) the conceptual level (see also Leventhal and Scherer 1987). Although all or most of the stimulus evaluation checks can occur at any of these stages of processing, they will be evaluating different information at each stage. 23 And as Wehrle and Scherer say, The purpose of process modeling is usually the attempt to simulate naturally occurring processes using hypothesized underlying mechanisms (2001: 354). 24 See also Smith and Kirby 2000, 2001 for a different model that is developed with the same goal, to modify a computational level model so that it begins to explain how the process is carried out. 25 See the introduction to this dissertation for a discussion of what levels of processing are.

150 Chapter At the first stage of processing the evaluations are made by way of simple sensory detection of the stimulus. At the schematic level evaluations are made using schemata or representations that have been acquired by the individual. And at the conceptual level, propositional knowledge is employed for the evaluations. So for example, the intrinsic pleasantness stimulus evaluation check evaluates innate preferences/aversions at the sensory-motor level; learned preferences/aversions at the schematic level; and recalled, anticipated, or derived positivenegative estimations at the conceptual level (2001: 103). The second feature that Scherer introduces are appraisal registers. The outcome of the stimulus evaluation checks are stored in appraisal registers, of which there is one for each of the stimulus evaluation checks. The information stored in these appraisal registers directs the changes that occur to the neuro-endocrine system, autonomic nervous system, and somatic nervous system. The information in the appraisal registers is then integrated into the different classes of appraisal objectives: relevance, implication, coping potential, and normative significance. 26 These different classes of information are then used to direct behavior (but see n27). The third feature that Scherer adds to his model is the sequence in which these classes of information can be utilized. On this model the different classes of the evaluations relevance, implication, coping potential, and normative significance occur in that order, although the order can be repeated or terminated early. Scherer suggests a specific sequence because he believes that the system should be able to establish as early as possible whether further, expensive processing is worthwhile. For instance, Scherer takes it that relevance detection has to 26 And, it is expected that the different checks are integrated through weighting functions, giving them different importance in the combination. These weighting functions may vary depending on the nature of the context (2001: 105).

151 Chapter have a determined value before it is worthwhile for the other evaluations to be completed (although they may already have started). And likewise, Scherer states that the evaluations for the implication assessment should be determined before further processing is warranted. As he says, extensive further processing and preparation of behavioral reactions are useful only if the event actually concerns a goal or need of major importance or when a salient discrepancy with an expected state is detected (2001: 99). Another reason for the sequence is to allow the later evaluations to use the information established in the earlier evaluations. The coping potential determination requires information about the values for the two previous appraisal objectives, relevance and implication, before it can be determined. And then all of the prior values are used for the last appraisal objective, the normative significance evaluation. The fourth feature that Scherer adds to this model is a description of the outputs. On this model each appraisal component is hypothesized to have its own output, and Scherer has characterized what these outputs might be for the neuro-endocrine system, autonomic nervous system, somatic nervous system, changes to the facial musculature, and vocal changes fairly specifically, although I am not going to discuss these in detail here (Scherer 1997; Scherer 2001: ). Scherer s process model is illustrated in the figure below. First, information from the environment is appraised in terms of the stimulus evaluation checks at the different stages of processing. The outcomes of these appraisals are sent to the appraisal registers. Here the stimulus evaluation checks that were made at each level of processing are combined. For instance, the goal relevance stimulus evaluation checks that are made at the sensory motor level, the schematic level, and the computational level are all combined in the goal relevance appraisal

152 Chapter register. The values that are now stored in each of the appraisal registers direct the bodily changes. These values are also combined into the four classes of appraisal objectives: relevance, implication, coping potential, and normative significance. The values that are determined for each of these appraisal objectives then determine the behavioral responses. 27 On this model the type of emotion that is ultimately produced is, as Scherer says, the net effect of all of the subsystem changes brought about by the outcome profile of SEC [stimulus evaluation checks] sequence (2001: 106), where the subsystems are the different types of bodily changes (shown at the top of the diagram) and behaviors (shown on the right). 27 The placement of the neuro-endocrine system, autonomic nervous system, and somatic nervous system in the diagram is a little odd because it suggests that the behaviors (on the far right of the figure) and the autonomic nervous system and the somatic nervous system are distinct and directing each other. Scherer, I believe only wants to capture the ideas that each of the stimulus evaluation checks (in the appraisal registers) can direct autonomic and somatic nervous system changes, and that the values that combine as appraisal objectives direct the more macro behaviors. So, bodily changes and behaviors have to be represented separately, but then they also have to be related, which I believe is all that the connections between them are meant to represent.

153 Chapter Figure 4.4. Adapted from Scherer (2001: 104). Although it is not clear in the diagram all three levels of processing have access to all of the stimulus evaluation checks (SECs). The bodily changes (neuro-endocrine system, autonomic nervous system, and somatic nervous system) receive inputs from all of the appraisal registers. These systems send output to, and receive feedback from, all of the different behavior types. Compared to the models discussed earlier (in sections and 4.2.3), this model of Scherer s attempts to specify what the inputs to the system are, what the exact outputs are, or might be, and to a certain extent how the transformation from the former to the latter is achieved. However, insofar as this model attempts to describe the operation of the appraisal ability it appears to be largely unsuccessful. In order to have an algorithm that can transform an input into a value stored in the appraisal registers (or into any kind of value) Scherer needs to specify a representation of the

154 Chapter inputs that the algorithm can operate on. 28 Scherer suggests the three stages of processing at which the inputs are provided to the system. However, he does not suggest representations for the inputs themselves that might be used by an algorithm in order to demonstrate how the transformation is achieved. Choosing appropriate representations is an important aspect of constructing an account at this level. This is a point that Marr is clear about, saying that the choice of which [representation system] to use is important and cannot be taken lightly. It determines what information is made explicit and hence what is pushed further into the background, and it has a far-reaching effect on the ease and difficulty with which operations may subsequently be carried out on the information (1982: 21 2). Although Scherer has not specified how to represent the inputs, he has elsewhere developed an algorithm for transforming the values that are assigned to the appraisal registers into outputs which are in the form of reports of the expected emotion and a prediction of the facial expression (Scherer 1993, Wherle and Scherer 2001). 29 So he can demonstrate the operation of part of this process. The problem with this algorithm is that it takes as inputs values that are set by the user. 30 In the studies that Scherer has carried out using this algorithm (i.e., computer program) the subjects are either presented with a story, or asked to recall an emotional 28 In the algorithm that Scherer does have the representations that the algorithm operates on are just numerical values that represent the outcome of each individual appraisal, which are provided by the user. 29 Scherer takes it that individual units of facial muscular activity are individually affected by the different appraisal components, rather than a specific facial expression (or set of expressions) being an indicator of a specific emotion. Therefore, putting together a report of a complete facial expression that is generated by the different appraisals is a significant task. 30 This program (that is described in Scherer 1993 and Wherle and Scherer 2001) is typically used in an experimental setting to test Scherer s choice of appraisal components and how they should be combined such that a particular emotion is elicited.

155 Chapter experience they have had, and then asked questions corresponding to the different appraisal components. The answers that the subjects provide are then used by the program to set the values for the appraisal registers (see figure 4.4). Essentially the subjects answers are the values. The program then computes the emotion type by combining the values (which are weighted by the system). This is then compared to the subject s report of the emotion to confirm or disconfirm the choice of weights. So the algorithm does not transform inputs that are provided to the system. The values are just placed in the appraisal registers based on the users reports. But it is the transformation of the (representation of the) perception of the event into the values in the appraisal registers that we are interested in. Therefore, the algorithm that Scherer developed is not one that performs the relevant transformation that is, the transformation that we want this type of explanation to describe. What we do get from this model of Scherer s is basically just more detail: the levels of processing at which inputs are present to the system, the sequence in which the stimulus evaluation checks occur, and the specification of the particular outputs are all just more specific elements of the computational theory. These are important aspects of the computational theory but still part of the computational theory. Regarding the suggestion that the stimulus evaluation checks occur in a particular sequence is only another constraint upon Scherer s model, one that Scherer (1999) has found some evidence for. It is in effect a claim about what kind of information the system compiles, but not how it does this. Therefore, as an account at the level of the representations and algorithm this model is unsuccessful. The main point that I wanted to demonstrate in this section was that Scherer s account is firmly a computational level account. Perhaps with more work is could demonstrate how this

156 Chapter process is carried out (and hence qualify as a middle level account). However, since it does not specify how the inputs to the system are to be represented it is not at that stage, or even very close to it, yet. In the next, brief, section I discuss a problem that may be influencing the way in which Scherer is attempting to construct a model for how this process is carried out Critique In order to understand the problem that Scherer s process model encounters we should back up for a moment. In the models that I described earlier (Roseman s and Scherer s first model) the appraisal capacity is described in terms that are derived from the external world. 31 This is to say that this capacity is described using language that refers to external relationships the appraisal components describe a relationship between the individual and the emotion causing event. For example, Roseman and Scherer both suggest that there is an appraisal component for agency, the idea being that in emotion-causing situations who or what caused the event is generally relevant to the emotion response that is generated. When Roseman says that othercaused is one value that can be assigned to the agency appraisal component, what this means is that the event was caused by another person, and this information is relevant to the emotion that is generated. For instance, if someone intentionally threw a glass of water on you, then this person is the cause of your present wet state. If someone accidentally tripped and spilled a glass of water on you then the consensus would probably be that your present wet state was the result of a particular set of circumstances and not the result of an intentional action by another individual. In this case, the value assigned to the agency appraisal component would (or could) 31 Note that Marr s account of directional selectivity was also, i.e., in terms of motion and shape.

157 Chapter be circumstance-caused. 32 In both of these examples the value for this appraisal component is based upon the relationship that holds or is believed to hold between the individual and other people or things. Therefore, accounts such as Roseman s and the first one of Scherer s that I looked at accounts at the levels of the computational theory are developed based upon this information about relationships in the external world. However, it is not obvious that when the move is made from describing the relationship between the individual and some event in the world, to describing an internal process that the constructs from the former description should be used. The higher level explanation of the process puts constraints on how the process is carried out, but it is not itself a description (even a partial one) of how the process is carried out. 33 As tempting as it is to look at a model like the one that Roseman has developed, and suggest that an explanation of how this part of the emotion process is carried out could be determined just by adding more details, this seems like a mistake. The wrong sorts of things would be used in trying 32 However, one of the important insights that these cognitive appraisal theorists are using is that in the case of emotion these rules about objective states of the world, or even consensuses about events have to be relaxed in order to explain the generation of emotions. Rather how the evaluation is made by the individual is what is important. For instance, if a student fails a class his anger may be based, in part, on an appraisal that the professor is the cause of failing grade. It may be the case, an objective fact, that the reason that the student failed was because he never studied and the professor is not the relevant agent that caused this negative event; the student is. Knowing this does not, however, explain the student s anger. To understand the anger we need to invoke the agency appraisal component and understand what value has been assigned to this component. The point here is that although an appraisal component is not used to assign values for the exact way in which the world is, they still derive their meaning from events in the world. It is just the case that what is the objectively correct value for any component does not determine the value that is actually assigned. Nevertheless, we still want to assume, at least in non-pathological cases, that the appraisal components and the values at which they can be set are objectively recognizable, even if they are not objectively correct (see also Scherer 2001: 94). 33 A similar point is made by Bechtel and Abrahamsen (1993) with respect to folk psychology and connectionism, and Bechtel (1994: 19) when discussing biochemistry with the implication that it generalizes to psychological capacities.

158 Chapter to explain the operation of the process, wrong that is in the sense that the constructs used in the process model are taken from a different type of explanation. This is a point that I think Scherer is unaware of. In order to make progress on how the process is carried out, he most likely needs to switch frameworks. After establishing a fairly complete, computational level account of the appraisals, the next step is to turn to a framework, either artificial or neurobiological, that can be used to describe how a process is carried out. In any case, as it stands now, Scherer s process model falls short of what we want from a middle level account, namely an account of the operation of a capacity. I have not eliminated the possibility that his process model is only incomplete, and could eventually be a legitimate middle level account. However, we can see that Scherer is unwilling to switch frameworks. He is maintaining the concepts and the language from the higher level of explanation the level of the computational theory. Furthermore, he also seems to place the emphasis of his approach in the wrong place. He is trying to figure out how the values for the different appraisal components are combined. However, it seems to me, and this is following Marr, that the more pressing question is to determine what the inputs to the system are and then if he wants to offer a middle level account to determine how to represent them so that a rigorous model of how the process is performed can be constructed.

159 Chapter Appendix, chapter four Roseman (2001) This is Roseman s most recent model of the appraisals and the emotions that they determine. This models has seven appraisal components (pointed out) that determine 17 discrete emotions. The changes from the model of Roseman s discussed earlier are in bold. Positive Negative unexpectedness Motive-Consistent Motive-Inconsistent situational state Appetitive Aversive Appetitive Aversive motivational state Circumstance-Caused Unexpected Surprise Uncertain Hope Fear Low Control Certain Joy Relief Sadness Distress Potential Uncertain Hope High Control Frustration Disgust Certain Joy Relief Potential Other-Caused Uncertain Low Control Dislike Certain Potential Love Uncertain High Control Anger Contempt Certain Potential Self-Caused Uncertain Low Control Regret Certain Potential Pride Uncertain High Control Guilt Shame Certain Potential agency Instrumental Intrinic probability Problem problem type Problem control potential Figure 4.5. Roseman s (2001) model of the cognitive appraisals.

160 Chapter Relevance enjoyment, happiness elation, joy displeasure, disgust contempt, scorn sadness, dejection despair anxiety, worry fear irritation, cold anger rage, hot anger boredom, indifference shame guilt pride Novelty Suddenness Familiarity Predictability Intrinsic pleasantness Goal/need relevance low high, medium open open low high low high low high very low low open open open open low open low very low open low open low high open open open medium low low open open low open low medium low very high open open open high open very low open open open open low open open open open open open medium high low low high high medium high medium high low high high high Implication Cause: agent open open open other open other, natural other, natural other, natural open other open self self self Cause: motive Outcome probability Discrepancy from expectation intentional chance, intentional open intentional chance, negligence chance, negligence open open intentional, negligence intentional open intentional, negligence intentional intentional very high very high very high high very high very high medium high very high very high very high very high very high very high consonant open open open open dissonant open dissonant open dissonant consonant open open open Conduciveness Urgency high very high open open obstruct obstruct obstruct obstruct obstruct obstruct open open high high very low low medium low low high medium very high medium high low high medium low Coping potential Control Power Adjustment open open open high very low very low open open high high medium open open open open open open low very low very low low very low medium high medium open open open high medium open high medium very low medium low high high high medium medium high Normative significance Internal standards compatibility open open open very low open open open open open open open very low very low very high External standards compatibility open open open very low open open open open low low open open very low high Figure 6. Scherer's model of the cognitive appraisals. Adapted from Scherer (2001).

161 Chapter A Two Dimensional Model of Levels In the first two chapters I examined levels of organization and offered a hierarchy of the levels of organization that fall within the scope of the brain. In chapters three and four I turned to levels of explanation and the kinds of descriptions of psychological capacities that are found at different levels of explanation. In this chapter I suggest that we need to use these two types of levels together in order to understand the relationship between psychology and the relevant neurobiology. It is important to employ both of these types of levels when trying to understand this relationship because we want to keep separate (1) the levels that we use to order those things that are found in nature, and (2) the various ways that we have of describing those things that are found in nature. The former, ordering the entities and activities that are found in nature, is done using levels of organization. The latter, the different ways we have of describing the things that are found in nature, is done using levels of explanation. By keeping these two separate, but showing how they are related, we can see how psychological descriptions are related to the neurobiological material. Conversely, if we do not keep them separate, which is what happens if we use only one type of level, then we are giving psychological descriptions and neurobiological descriptions the same status (ontologically speaking). Since they do not have the same status, I think this is a mistake. However, I will wait until chapter six to look at the problems with using a single hierarchy to explain the relationship between psychology and neurobiology. In this chapter I offer my positive view, and in next chapter I will criticize William Lycan and Carl Craver s accounts, which do employ a single hierarchy of levels.

162 Chapter In the first part of this chapter I discuss the utility of combining these two types of levels and the account that this generates. In the second part of the chapter (section 5.2) I will look more closely at how the two types of levels should be combined, which is a question of what level or levels are part of both a hierarchy of levels of organization and a hierarchy of levels of explanation. This, in effect, indicates the specific relationship between psychology and neurobiology. 5.1 Levels of explanation and levels of organization The importance of levels of explanation is that they provide a framework for laying out different types of descriptions of a capacity. As I explained in chapter three, Marr s account includes three levels of explanation: the level of the computational theory, the representation and algorithm level, and the hardware implementation level. These three levels correspond to different types of descriptions in the mind-brain sciences. The type of description that Marr suggests for the level of the computational theory is what is offered by a psychological description of a capacity. What Marr intended as a middle level description is captured by a range of different types of models the symbolic, connectionist, and biologically realistic (and variations of these) that seek to specify the operation of a capacity. This leaves Marr s level of hardware implementation. For Marr the level of hardware implementation is a description of the biological material that carries out the psychological capacity. As Marr says, the level of the hardware implementation is the level of explanation where mechanisms are realized in hardware and where basic component and circuit analysis are offered (Marr and Poggio 1976: 1, 2). Since the biological material that carries out the process that we are studying is identified and described at this level of explanation, this is

163 Chapter therefore a description of some of the entities and their activities at a level of organization. Recall that levels of organization are identified by entities interacting in stable and predictable ways with other entities (Wimsatt 1976). Since psychological capacities are implemented in a series of entities interacting in regular ways, Marr s level of hardware implementation and some particular level of organization identify the same class of things. The only difference between what is found at a level of organization and the lowest level of explanation is that qua level of explanation the description is dedicated to a specific capacity, while the level of organization is a feature of a broader series of interactions, which are not limited to just one capacity. That is to say that at the level of hardware implementation we identify and focus on a particular series of activities that carry out the capacity. This series of activities is set within all of the activity at that level of organization, which includes more interactions than just those that are concerned with a single capacity. The question is then which of the levels of organization is the appropriate one at which to locate the level of hardware implementation (i.e., the lowest level of explanation). I will address this question in the second part of this chapter. However, as a first pass we can look at Marr s example of directional selectivity, which I reviewed in chapter three. Marr suggests that this capacity (which is the ability to take incomplete information about the motion of an object and use it to identify its two dimensional shape) is carried out by the retinal ganglion cells and neurons in the lateral geniculate nucleus. Therefore, Marr believes that the entities and activities for this lowest level of explanation, the level of hardware implementation, are found at the cell network level of organization. This choice of a level of organization is, I think, partially correct and in the second half of this chapter I will discuss it further. But for now, using the cell network

164 Chapter level of organization is sufficient to illustrate how levels of explanation and levels of organization fit together. With the intersection of levels of explanation and levels of organization a two dimensional model can be constructed with levels of organization as one hierarchy and levels of explanation as a separate hierarchy. The two hierarchies are connected in that what is described at one level is part of both hierarchies. A summary of this two dimensional model is shown in figure 5.1. In that figure the hierarchy of levels of organization is on the leftmost axis. Different levels of explanation (or the particular sciences that offer the relevant types of explanations) form the hierarchies that are the other axes. social psychology, economics organism level cell network level psychological description cognitive science (modeling) cognitive neuroscience (modeling) sub-cellular level levels of explanation levels of organization chemical level Figure 5.1. A two dimensional space of levels. Levels of organization are on the left axis. Levels of explanation are the hierarchies on the right. On the hierarchy of levels of explanation that has psychological descriptions at the top there are two levels for the modeling techniques that were reviewed at the end of chapter three (classical computational, connectionist, and biologically realistic). The levels of explanation where descriptions of psychological capacities are given are the levels of explanation on which I am focusing. However, a level of explanation can have other forms, as is shown in figure 5.1. And it might be helpful to introduce the general relationship

165 Chapter between a level of organization and higher level of explanation with an example of a statistical explanation. One type of statistical explanation, a type sometimes offered in economics, is at a level of explanation that is above the organism level of organization (or the level of individuals). The statistical explanation is located among the levels of explanation because it is a particular way of describing the entities and their activities that are found at this level of organization. 1 To take one such explanation, Gallup and Sachs (2001) detail the strong inverse correlation between malaria and per capita GDP. The populations with the highest incidences of malaria per capita have the lowest per capita GDPs. This, although it is an informative description of individuals with and without malaria, is not a description of the actual entities (people) that have malaria and live in poverty. There may not even be any individuals who earn the per capita gross domestic product of their country and have malaria. Nor is it a description of what, if any, causal relationships there are between having malaria and living in poverty. As Sachs and Malaney point out in another article, This correlation can, of course be explained in several possible ways. Poverty may promote malaria transmission; malaria may cause poverty by impeding economic growth; or causality may run in both directions. It is also possible that the correlation is at least partly spurious, with the tropical climate causing poverty for reasons unrelated to malaria (2002: 681). The point is that if the description were at the lowest possible level of explanation it would just be a description of all the people with malaria and their incomes (GDP is not the same as income, but I will leave that aside). 2 The statistical description abstracts away form this 1 And, I take it that this illustrates an interesting feature of levels of explanation, that the least abstract description (i.e., the one at the lowest level of explanation) is not always the most informative. This is also shown for the behavior of molecules in gases, their actual behavior could be described (at least hypothetically). However since the individual actions of a molecule are random this would be a very tedious task. The statistical average of the behavior of a group of molecules on the other hand, does provide an informative answer about the behavior of the molecules. 2 And if we were working at this level of organization we might look for causal factors between living in poverty and malaria.

166 Chapter information and provides a useful summary of the relationship between the two variables. Therefore, the statistical explanation is a particular kind of description of some of the organisms that are found at this level of organization. The type of description that we have for psychological capacities are different of course, but the general point is the same: the description at the higher level of explanation provides a particular kind of description of what is found at the level of organization, which we are taking for the moment to be the cell network level. With respect to psychological capacities, in the next section I discuss the significance of having a series of levels of explanation above a level of organization The hierarchy of levels of explanation Marr s claim is that all three levels of explanation are necessary for generating a complete understanding of a capacity (what he refers to as an information processing task). To this end each level poses a question or set of questions that can be answered with the resources of that level. The answers, collectively, are a complete explanation of the capacity. At the computational level the question is: what is the capacity and why is performed in the way that it is? 3 At the representation and algorithmic level the question is, in Marr s terms: How can the computational theory be implemented? This question might also be stated as: What procedure can specify the transformation that the capacity performs? And at the hardware level the question as Marr states it is: How can the representation and algorithm be realized physically? 3 For Marr the why question is a subset of the what question insofar as understanding why a task is performed in a certain way, and not some other way, indicates what sorts of constraints apply to the system s performance of the task. So for Marr s cash register example the reason why the cash register performs addition instead of multiplication gives us insight into what the cash register does, i.e., total invoices linearly.

167 Chapter These different questions convey the idea that each description that is offered at a particular level of explanation serves a specific purpose. For instance, at the level of the computational theory that purpose is to give an account of what the capacity is (or does), whereas a description at Marr s middle level suggests how the operation that carries out the capacity is performed. Thus, levels of explanation are a way of separating different types of descriptions of a capacity. Since there are different ways of describing the capacity, thinking in terms of levels of explanation emphasizes this. This is one reason to employ levels of explanation. Another way to think of levels of explanation is as abstractions away from the hardware level. I am using abstraction to mean dropping some of the details about the entities and their interactions (from the appropriate level of organization). 4 For instance, a biologically realistic model of how a collection of neurons interact simplifies those entities (the neurons) and their activity. A connectionist model, we can say, offers much less detail about actual neurons and their interactions, but seeks to describe the same capacity. Alternatively, if we are using Marr s levels, then at his middle level abstracting away from the hardware level takes the form of dropping all of the biological details and just focusing on the algorithm that the biological material is presumed to be performing. At Marr s highest level of explanation the abstraction away from the hardware level is greater in that all the 4 Note that I am not using abstraction in a way in which it is sometimes used (see for instance, Owens 1989) where everything above the level of physics is an abstraction away from physics. I am only using it to refer to levels of explanation that abstract away from a level of organization. So every hierarchy of levels of explanation is (essentially) created by a process of abstraction. The way that Owens uses abstraction is to describe the relationship between (what I call) levels of organization. This is not the way that I am using the term abstraction.

168 Chapter details about the hardware are dropped except for the description of the task that the entities that constitute the hardware are performing. The advantage of this notion of abstraction is that it allows us to order levels of explanation in a hierarchy and it gives us a sense of what moving away from (or towards) the level of organization entails. 5 Once that is established, we are able to see that each of these levels of explanation is a certain way of talking about what is occurring at the hardware level. That is, once we accept that the capacity that we are trying to explain is carried out by some collection of physical entities interacting in particular ways, then it follows that all other descriptions of the capacity are abstractions away from this physical level. Therefore, in the case of these psychological capacities Marr s highest level is a certain way of talking about what is occurring at the hardware level. Once we recognize this it then follows that it is not necessary to know what is occurring at the hardware level in order to talk about the hardware level in abstract terms. All that we need to know, or at least need to think that we know, is that a capacity is present. 6 To take an example, the account offered by Roseman, which was discussed in chapter four, specifies a capacity that is carried out by whatever may be occurring at the hardware level. Roseman does not say, or give any indication at all about, what the hardware is that carries out the capacity that he has described. Nevertheless, once his abstract description of the capacity is placed in a hierarchy of levels of explanation we can see that he is offering a certain kind of 5 Although it should be noted that it orders them imperfectly. For instance, perhaps there is an intuitive feeling that a symbolic model is at a slightly higher, ie., more abstract, level than a connectionist model. However, there does not seem to be any real criteria that can support this. (The more essential point is that levels of explanation give us a way of separating explanations that have different goals.) 6 This demonstrates that psychological descriptions of a capacity, while they do serve their own specific purpose, have (in a broad sense) a similar type of relationship to the relevant level of organization that statistical analyses have to their level of organization. Both are merely abstract descriptions of the activities occurring at the level of organization.

169 Chapter description of the physical entities that carry out this capacity. This much we can say without having any idea of even what kinds of things are at the hardware level. Therefore, the utility of the model that is represented in figure 5.1 is that it illustrates that higher levels of explanation, in particular psychological descriptions, are just different ways of describing what is occurring at the appropriate level of organization. And this is the relationship between psychological descriptions of capacities and neurobiology that this model generates. It should be clear that we get this particular account of the relationship because we have used both levels of organization and levels of explanation. In chapters one through four I motivated the idea that we need both of these types of levels simply because they are applicable: levels of organization are the way in which we organize the different types of activities that are found in the brain, and levels of explanation are the way that we organize different kinds of descriptions of psychological capacities. What has been accomplished here is simply putting these two types of levels together. In chapter six I will contrast my account with two accounts that try to explain the relationship between psychology and neurobiology but employ only one type of level; a type that is similar to what I call a level of organization. In that chapter I will discuss further the advantages of using levels of organization and levels of explanation, but right now I am going to turn to the details of determining the appropriate levels of organization for psychological capacities.

170 Chapter Levels of organization Determining the appropriate levels of organization In figure 5.1 I have the cell network level of organization as the lowest level of explanation. In the rest of this chapter I am going to argue that the cell network and the sub-cellular levels of organization are the lowest levels of explanation for psychological capacities. I am not, however, going to determine what the specific entities and interactions are for a psychological capacity such as emotion appraisals. Rather I am just going to identify the types of entities and the types of interactions that are psychological capacities. In other words I am going to identify the level or levels of organization at which psychological capacities occur. What I mean by the level at which psychological capacities occur is analogous to other biological investigations that were originally understood only at a higher level of explanation. For instance, compare the cases of the fermentation of sugars or carrying hereditary information (Bechtel 1994, 2005; Bechtel and Richardson 1993). What these capacities are (i.e., what they are able to do) was understood first, and then the physical processes that carried them out was determined. Hence, the question, At which level of organization do psychological capacities occur? is analogous to the question, At which level of organization does fermentation occur? Or, At what level of organization are genes found? The latter two questions are, today, straightforward and simple to answer, although it took some time to discover the answers. As Bechtel says of the search for the physical process that carries out fermentation, The challenge confronting those seeking to provide chemical explanations of basic physiological processes was to characterize the component operations (reactions) at an appropriate level of organization. Elemental composition was too low a level at which to characterize changes, while decomposing fermentation into fermentations simply invoked

171 Chapter the vocabulary designed to explain the overall behavior to describe the operation of its components (2005: 318). 7 The task in the rest of this chapter is to specify the appropriate levels of organization for psychological capacities. As is shown in figure 5.1 Marr indicates that the cell network level of organization is the appropriate level for carrying out psychological processes. This, I think, is partially correct. In what follows I will argue that both the cell network and the sub-cellular levels of organization carry out psychological capacities. This yields the diagram in figure 5.2, which represents my account of the relationship between psychology and neurobiology. social psychology, economics organism level cell network level psychological description cognitive science (modeling) cognitive neuroscience (modeling) levels of organization sub-cellular level chemical level levels of explanation Figure 5.2. A more complete two dimensional space of levels for psychology. The work that was done in chapter one to establish a hierarchy of levels of organization provides the foundation for the claim that the cell network and the sub-cellular levels of organization are where psychological capacities occur. Recall that the levels of organization that were laid out in chapter one are the cell network level, the sub-cellular level, and the chemical 7 Bechtel also says later, Recall that in the early 19th century many chemists attempted to explain physiological processes directly in terms of elemental composition. Although it is certainly true that changes in elemental composition of substrates occur in physiological processes, the relevant operations involved higher-level molecular units (2005: 321).

172 Chapter level. At the cell network level the entities are neurons, and their activities are the generation of action potentials and the excitatory and inhibitory transmissions from one to another. Below the cell network level, at the sub-cellular level, the entities are, for the most part, large molecules (for example, proteins, enzymes, ion channels, receptors) that interact with each other in and around neurons. Below the sub-cellular level is the chemical level where the entities are atoms, and their interactions are, for instance, bonding, the non-bonding interactions between atoms, and the interactions between atoms and the solvent they are in. Of these levels of organization it has to be demonstrated that the cell network and subcellular levels of organization have the properties that are required in order to carry out psychological capacities. I will do this in what follows. I will also explain why the other levels of organization that are in figure 5.2, the organism level of organization and the chemical level of organization, are not the appropriate levels at which to locate psychological capacities The organism level of organization Starting at the highest level of organization shown in figure 5.2, the organism level is a level above the neurobiological levels that I have been discussing. At the organism level the entities that we are concerned with are (for the most part) humans and their activities and interactions (that is, their behavior). I have been focusing on levels of organization that fall within the scope of neurobiology and I am committed to the view that these psychological capacities are internal to individuals. I do, however, want to describe how the level of organization where individuals are found fits into my model. Psychological capacities, in the way that I have been describing them, are processes that are spatially and temporally extended. So, as a process, the capacity needs a series of entities

173 Chapter interacting in order to carry it out. When we are interested in these psychological capacities as processes then we focus on levels of organization where the process can be explained by entities interacting with each other (i.e., the cell network and sub-cellular levels of organization). At the higher, organism level of organization the capacity is not characterized as a process, but as a state or a property of an individual. At this level, we are observing single entities individuals in this case and their interactions (as we do at any level of organization). At this level we no longer have the opportunity to view the psychological capacity as an extended process. All that we can observe is if an entity has the capacity or not, and how that influences their interactions. That is, whereas a capacity, such as the capacity to comprehend language, is a process that occurs at the neural levels of organization, at the organism level of organization it is a property that individuals have or do not have; they either can or cannot comprehend language Brain areas Before moving on to the three levels of organization that I established in chapter one I want to mention another set of entities that I considered in that chapter. There I looked at the possibility that there may be a level above the cell network level and below the level where the whole brain is taken as a single entity. There are entities above the cell network level, brain areas such as the lateral geniculate nucleus (LGN), the primary visual cortex (V1), and V2. However, I argued in chapters one and two that brain areas do not constitute a level of organization. I am not going to review all of those arguments here, but the main issue is that it is difficult to see how these sorts of entities (brain areas) interact with each other. To the extent that they can be said to interact it seems that it is in virtue of the neurons that send axons from one area to another. This activity is, however, the activity of the entities at the cell network level, and so the conclusion is that brain

174 Chapter areas do not interact with each other. Insofar as brain areas do not constitute a level of organization, they are not a candidate for carrying out psychological capacities. I will in this section add another argument against brain areas. The conclusion of which is that even if brain areas did constitute a level of organization, it would not be the correct level at which to describe a psychological capacity. This can be shown as follows. Even if we are able to distinguish between different psychological capacities at a level of brain areas, e.g., between vision and memory or emotion, we will not be able to give a detailed description of a particular psychological capacity. For example, the LGN, V1, and V2 are entities that may be referred to when talking about vision. However, if we are only using these brain areas in our explanation, then we cannot make any distinctions between, or say anything specific at all about, the visual perception of different orientations, the direction of movement, or color. 8 But we can describe the ability to perceive these features when we describe the activity of neurons (Hubel and Wiesel 1977; Livingstone and Hubel 1987). To take a simple example, in layer 4B of the primary visual cortex (V1) we can find a neuron that has an optimal response to a bar of light at a 0 orientation (i.e., ). If we move to a neighboring neuron about.45mm away we find that it has an optimal response to a 90 orientation ( ). The example would become more complex if we introduced the other features and gave an account of how these neurons interact (but see the example from Lund in chapter 1). But the point is that if we only look at the response of the brain area V1, we no longer have access to the appropriate entities to describe this feature of vision: the processing of lines of different orientation. And if we are trying to describe the capacity for vision, then we need to be able to describe how these sub-capacities perceiving orientation, the 8 This point was also made at the end of chapter two when discussing Nottebohm s (1981) work on the song abilities in canaries. And in addition to vision and the areas dedicated to vision, the same problem appears to apply to all other brain areas, e.g., motor cortex, auditory cortex.

175 Chapter direction of movement, color, and so on are carried out. To the extent that these aspects of vision cannot be explained while only referencing brain areas, then brain areas cannot be the level where psychological capacities are found. Remember that the issue is not whether employing these entities (LGN, V1, V2 etc.) is helpful in understanding a psychological capacity, or whether they are ever used when talking about a psychological capacity. The issue is at what level of organization do these psychological capacities occur. And brain areas do not constitute a level where psychological capacities occur The cell network level of organization The cell network level does appear to be an appropriate level at which to locate psychological capacities because this level is occupied by entities that interact over the appropriate spatial and temporal scales. 9 By the appropriate spatial scales I mean the distances over which neural processing occurs, for example, for stimulation at the periphery (i.e., the perception of a stimulus) to move to diverse parts of the brain, or in the other direction, from regions of the brain to the periphery (at which point we are able to observe the behavior). And by the appropriate temporal scale I mean the correlation between the time that it takes a cognitive (or behavioral) operation to occur and the time over which a series of neurons interact. One example of this is work that Graziano and his colleagues have done with electrical microstimulation of the neurons in the motor cortex (Graziano et al 2002a). Electrical microstimulation is a technique that uses an electrode to penetrate to a certain depth in the brain 9 One premise of my argument here could be that the numbers of neurons that are available and their diverging and converging connections appear to allow for something like the right kind of computing power to carry out these psychological processes. However, I am going to focus on a simpler line of argument.

176 Chapter and then a series of electrical pulses are applied to the neural tissue. There is some variability in exactly how many neurons are directly activated, which is based on the density and threshold of the neurons in the area of cortex that has been penetrated, the amount of current being applied, and the size of the electrode (Tehovnik 1996). However, the working assumption is that if a particular behavior can consistently be elicited by stimulating a single site, then there is a specific collection of neurons from the site to the periphery that are being recruited when the stimulation is applied (Graziano et al 2002a, 20002b). In this study Graziano and his colleagues used electrical microstimulation to induce complex movements of the limbs. The arm and hand movement caused by the stimulation of one site in the motor cortex (precentral gyrus) in the right hemisphere is illustrated in figure 5.3. These trials began with the monkey s left arm in a variety of different positions. When the stimulation began there was, after a brief latency (less than 33ms, i.e., one video frame), a smooth and coordinated movement of the hand to the mouth, the hand closing into a gripping posture (thumb against the forefinger), and the mouth opening. The duration of the movement was determined by the length of the electrical microstimulation. The full movement was performed when stimulation was applied for 500ms. With 1000ms of stimulation to the neurons the movement was accomplished and the hand was held in front of the open mouth for the remainder of the stimulation, and if the stimulation was applied for 100ms, there were partial movements of the arm, hand and mouth.

177 Chapter Figure 5.3. Drawings traced from video footage of eleven trials in which mictrostimulation was applied to the same site in the precentral gyrus in the right hemisphere for 500ms (at 100 µa and 200 Hz). Each dot represents the position of the hand in one frame of the video. From Graziano et al (2002a: 842). This study illustrates both the spatial and the temporal scales over which activity at the cell network level occurs. In particular, we see that stimulations of neurons in the motor cortex leads to activity at the periphery of the organism, and the time scale of the stimulation of the neurons is directly correlated with the behavior that is evoked. There are other examples that I could offer, but the idea should be clear from this one that the entities and their activities at the cell network level have to have a primary role in carrying out psychological capacities. Therefore, we can start with the claim that this is one level of organization where psychological capacities are found The sub-cellular level of organization Given that the cell network is one level where psychological processes are found, then we would expect that the next level of organization down would also be important for understanding psychological processes. The lower level is important because we often want to know why some of the interactions that occur at the cell network level occur as they do, or why variations or changes occur to the cell network level. These changes generally fall under the notion of plasticity: changes that occur to the connections between neurons during learning and

178 Chapter development. In order to understand these changes what activity accounts for these changes we need to look at the activity at the sub-cellular level. I examined one example of this, ocular dominance plasticity, in chapter one. There I discussed some of the sub-cellular level activities that carry out the restructuring of connections between neurons in V1 when one eye is deprived of input. 10 One way of characterizing the relationship between these two levels of organization is that the activity at the cell network level establishes where and how the process is carried out and the activity of the sub-cellular level is used to investigate any important variations or changes i.e., plasticity that occur to the entities at the cell network level of organization The chemical level of organization At levels lower than the sub-cellular level it seems that the relevance of the activities found there for explaining psychological kinds begins to diminish. In this section I am going to argue that psychological capacities do not occur at the chemical level. I will, however, begin with some qualifications. First, this argument is different than the argument that was used with brain areas. There the main issue was whether or not there is an actual level of organization occupied by the different brain areas. For the chemical level I am not questioning whether this is a level of organization. I believe that it is. And since it is there, right below the sub-cellular level and not in danger of being eliminated from the hierarchy of levels of organization, this argument will not be as decisive as the argument was against the brain areas level. 10 Another well known example of the sub-cellular activities that drive plasticity are the activities and structural changes that occur to a post synaptic site during long term potentiation (Soderling and Derkach 2000; Abel et al 1997).

179 Chapter The second qualification is that, although my conclusion is going to be that the chemical level is not a level where psychological capacities are found, in some cases the entities and activities at the chemical level do appear to directly participate in carrying out psychological capacities. The obvious examples are electrical charge and the flow of ions across the cell membrane (and in some cases their binding to proteins, e.g., as is the case with positively charged calcium ions [Ca 2+ ]). These are extremely important for psychological capacities, but I take it these types of cases are not the norm, and so I am going to put them aside and focus on interactions among entities of roughly the same size and type of structure i.e., interactions among macromolecules, interactions among atoms, and so on. The third qualification is that I am not claiming that the activities at the chemical level do not register at higher levels, as clearly they do. They register in the sense that a change to an entity at the chemical level will (or might) have consequences for activities at, say, the cell network level. The claim that I am making is that the chemical level is not where psychological capacities are found which is to say that psychological capacities are not the entities and the activities found at the chemical level (cf. the Bechtel quote in n7 of this chapter). These qualifications having been offered, let me explain the structure of the following argument. Backing up for a moment, there are two general objections that might be made to my claim that the cell network and sub-cellular levels of organization are where psychological capacities are found. First, one might say that the cell network level is too high a level and so the pair of relevant levels should be shifted from the cell network and sub-cellular levels to the subcellular and chemical levels. However, I argued for the importance of the activity at the cell network level in section In that section the conclusion was that the activity of neurons

180 Chapter occurs over the right sort of spatial and temporal scales, and so it is reasonable to conclude that the activity there has a primary role in carrying out psychological capacities. Given that there is agreement that the cell network level is one level where we can say that psychological capacities occur, the second potential objection is that the question where do psychological capacities occur? cannot be limited to such a narrow range of levels. For instance, Carl Craver, whose account of levels I discuss in the next chapter says, But there is no single neural level, or neurophysiological level, or neuroscientific level of explanation. Neuroscientific phenomena span a hierarchy of interconnected levels from molecules to behaviors. Explanations in neuroscience are explanations in the middle range between elementary particles and astronomical phenomena (forthcoming, chap. 1: 14 15). 11 I am not arguing for a single level, but I am arguing against the view that all levels are relevant, or may be relevant, for describing psychological capacities. The argument that follows addresses the objection that the chemical level should not be excluded. All that this argument aims to accomplish is to demonstrate that if it is agreed that the activity at the cell network level is one level where psychological capacities occur, then the chemical level is by and large too many levels away from the cell network level to have a direct effect on the explanation of the activity that is occurring there. Some of the premises in this argument are, first, that the cell network level is central to carrying out psychological capacities. Second, there is a composition relation between these 11 A little context might be helpful here. Craver is responsonding to Kripke s claim that The rough uniformities in our arithmetical behavior may or may not some day be given an explanation on the neurophysiological level (1982: 97). So the issue is not, What is neuroscience? which would appear to be a question about how science is practiced, not about levels. Rather Craver s point is that the relevant neuroscientific explanations (that Kripke is after) span many levels of organization.

181 Chapter levels of organization. Although I did not use composition as the property that defines levels of organization, it still is a background feature of these levels. Third, this argument is about complete, or attempts to offer complete, explanations of different processes the processes that are occurring at each level. This contrasts with investigations of these processes, which will certainly proceed by working at any number of different levels. To take the example of ocular dominance plasticity discussed in chapter one, the goal of the investigators working on that process is to identify all of the entities involved and what the specific activities are for those entities. The explanation that this work yields is what I am calling a complete explanation of ocular dominance plasticity. This contrasts with all of the different experimental investigations that aid in putting the complete explanation together. The investigations themselves operate at a number of different levels from the organism level (sewing one eye closed) to the chemical (changing the amino acids in certain locations on a protein so that it cannot phosphorylate). An analysis of different investigative techniques and how it is that working at one level can provide insights to the activity at another level is an interesting topic but I am not going to take it up here. All that I want to establish is that my focus is on this idea of the complete explanation of a process that occurs at a level of organization. And fourth, it is worth keeping in mind that generally when we want to understand a process we are not looking for the details at a lower level, rather we are trying to understand the interactions that occur at one level. For instance, we want to know all of the macromolecules involved in a particular form of plasticity, and which specific interactions occur, but we may not need very many, or even any, of the details of the activity at the chemical level in order to understand the changes that result from the plasticity. Therefore, the issue of looking down levels and how many levels down we need to look only occurs in special cases.

182 Chapter This argument can proceed without talking about the actual entities and their activities at each level. Rather, we can start with the idea that there are three levels of organization, levels A, B, and C. At each level interactions are occurring among the entities that constitute that particular level. When the interactions that are occurring at level A need a certain type of explanation that looking down a level can provide, then one looks down to the interactions at level B. This occurs, for instance, when we want to determine how a particular type of plasticity occurs this is the point that I mentioned earlier with respect to the relationship between the cell network and the sub-cellular levels. The same point holds for levels B and C. If one wants a further explanation for some of the activities at level B, then the entities and their activities at level C can be examined. Let us say that the entities at level C, call them c 1, c 2, and c 3, are behaving in such a way that at level B b 1 and b 2 are able to interact. Given that b 1 and b 2 are able to interact, then at level A, a 1 is able to interact in a particular way with a 3 instead of a 2. So, the activities at level C do register in this way at level A. Level A: a 1 interacts with a 3 ; a 3 interacts with a 4 Level B: b 1 b 2 b 3 b 4 Level C: c 1 c 2 c 3 c 4 Figure 5.4. A simple model of entities interacting at three different levels of organization. Although the activities at level C register at level A I am claiming that the activity of the entities at level C are not part of the explanation of the activity at level A. The reason for this is that any time more information is needed about what is occurring at level A (information of the type that looking down a level will help with), the activity at level B will provide that

183 Chapter information. There are two reasons for this. First, there cannot be changes at level C that do not impact the activity at level B, but do impact the activity at level A. 12 That is, there will not be phenomena skipping levels such that looking down one level will not be informative at all, but looking down two levels will be. Recall that I said that this argument relies on a premise about composition. I consider composition a feature, but not the primary feature, of levels of organization. To the extent that someone else relies on composition more strongly this point should be that much more salient. The second reason follows from the first: any changes to the entities at level C will register at level B. Therefore, if we want to know why a 1 and a 3 are interacting in some particular way, then we can look down to level B and see that b 1 and b 2 are interacting. The activity at level B will answer the question: why are a 1 and a 3 interacting?. Looking down to level C might answer another question, for instance, why are b 1 and b 2 interacting in the manner that they are? To answer this question we can look down to level C and see that c 1 and c 2 are interacting. In this case however, we look down to level C in order to answer a question that is posed about the activity at level B, not level A. It is important for this argument to keep in mind that the goal here is restricted to understanding what is occurring at level A, and the goal is not to continue to look for the answers to questions at lower and lower levels. To briefly put this argument back into the language of levels of organization, if it is the case that the cell network level is the main level where psychological capacities occur, then the sub-cellular level has to be the subsidiary level, because it is the next level down. When more detail is required about the events that are occurring among a certain set of neurons (at the cell network level), then we look at the activity occurring among the entities at the sub-cellular 12 At least most of the time. Electrical current is one counterexample here.

184 Chapter level as we did for the case of ocular dominance plasticity in chapter one. Discovering what we are looking for here would, on the face of it, answer the question that caused us to look down a level. There are changes that are occurring at the chemical level, but they are, ipso facto, the changes of the entities at the sub-cellular level. 13 This is to say that while changes to the entities and their activities at the chemical level can certainly have effects that register at the cell network level, these changes will be changes to the entities at the sub-cellular level. Therefore, questions that need to be answered by looking down a level (from the cell network level) are answered by looking to the sub-cellular level. So, by a process of eliminating levels of organization that are occupied by entities that cannot account for psychological capacities, we are left with the cell network level and the subcellular levels of organization. These two levels, together, are occupied by entities that have the right sort of features and behave in the right sort of way, in order to carry out the capacities that are described by psychology. Therefore, the conclusion is that a description of a capacity that is offered in the language of cognitive psychology is an abstract description of particular entities and their activities at the cell network and the sub-cellular levels of organization. 13 For instance, when a molecule like CaMKII becomes active, what this means is that it has undergone a conformational change the bonds of the individual atoms that compose it have changed. The changes of these bonds, can be described (at least in theory) and this will give us a more complete description of what it means for a certain enzyme to be active. However, the description (at the sub-cellular level) of the conditions under which CaMKII will become active we already know (calmodulin binds with it).

185 Chapter Critiques of Lycan and Craver The account that I offered in chapter five explains the relationship between the descriptions of psychological capacities that are offered in cognitive psychology and the neurobiological entities and activities that carry out these capacities. William Lycan (1981, 1987) and Carl Craver (2002, forthcoming) offer alternative accounts of the relationship between psychology and neurobiology, and so in this chapter I will examine their accounts and contrast them with my own. The first of these, Lycan s, requires stepping back from the cognitive psychology and neurobiology that I have been dealing with up to this point. Lycan s argument is important, however, because he has been, as Craver says, widely cited as the foremost advocate of a multilevel view of psychological explanation (forthcoming, chap. 1: 14). The second, related, account that I am going to look at in this chapter is one offered by Craver himself. His account does focus on neurobiology and it is in some ways similar to my own although he follows Lycan in advocating a multilevel account of psychological capacities. In the previous chapter I suggested a way of understanding how psychology can be placed in a space of levels that employs both levels of explanation and levels of organization. According to my account certain types of psychological description are a higher level of explanation of two levels of organization: the cell network level and the sub-cellular level. This differs from the view, defended by both Lycan and Craver, of a single hierarchy of levels that has atoms and molecules near the bottom and mental and social entities somewhere near the top. Lycan and Craver also endorse the idea that to move from the mental or psychological to the neurobiological and lower is to move through a number of levels, none of which picks out the

186 Chapter single place where psychological capacities occur. The account that I offered in chapter five contrasts with this approach, in that I am claiming that psychological capacities are found, if not at a single level of organization then at two: the cell network level and the sub-cellular level. 6.1 Lycan Lycan s account of the relationship between the mental and the physical, which he explains in terms of a hierarchy of levels of nature, is laid out in his paper Form, function, and feel (1981) and in his book Consciousness (chap. 4, 1987). Lycan motivates his account by arguing against those who, when explaining the mental, make an absolute distinction between function and structure, role and occupant, software and hardware, or what have you. As he says, Very generally put, my objection is that software / hardware talk encourages the idea of a bipartite Nature, divided into two levels, roughly the physiochemical and the (supervenient) functional or higher-organizational as against reality, which is a multiple hierarchy of levels of nature, each level marked by nexus of nomic generalizations and supervenient on all those levels below it on the continuum (1987: 38). Although Lycan does perhaps argue convincingly against an absolute distinction between the functional and the structural, he has not defeated a more general formulation of the two level distinction that can be used to describe the relationship between the mental and the physical. The account that I offered in the previous chapter I take to be a general formulation of this distinction. 1 In what follows I lay out Lycan s account and some internal problems that arise. I then demonstrate how my account can handle these problems. 1 My account is a more general formulation of the two level distinction insofar as it includes descriptions of capacities at higher levels of explanation and descriptions of the neurobiological entities and activities at the cell network and sub-cellular levels of organization.

187 Chapter Lycan s commitment to homuncular functionalism I will begin by laying out two of Lycan s commitments. The first commitment is to what he calls homuncular functionalism, which is a method of reducing mental (psychological, intentional) abilities to non-mental (or non-intentional) ones. The idea is that a person may be identified as a corporate entity that corporately performs many immensely complex functions functions of the sort usually called mental or psychological (1987: 40). Any one of these functions can then be explained by positing a theoretical set of homunculi (that is, sub-capacities) that together perform the function. Any of these homunculi (the sub-capacities) can then be explained by another set of sub-capacities, and so on. As Lycan says, To characterize the psychologists quest in the way I have is to see them as first noting some intentionally or otherwise psychologically characterized abilities of the human subject at the level of data or phenomena, and positing as theoretical entities the homunculi or sub-personal agencies that are needed to explain the subjects having those abilities. Then the psychologists posit further, smaller homunculi, etc., etc., (1987: 40). Each of these steps to smaller homunculi introduces entities (the homunculi) that are individually bearing less of the human s functional (teleological) capacity. As the steps proceed downward each level is less teleological than the one above it until the explanation is relatively non-teleological. That is, the explanation is mechanical. 2 At some sufficiently high level the entities will have marked and obvious teleological characterizations, teleological, that is, in the sense that the function of an entity identifies the purpose of that entity and this purpose has probably been selected by natural selection. 3 A 2 As Lycan says, Now at what point in this descent through the institutional hierarchy does our characterization stop being teleological, period, and start being purely mechanical, period? I think that it is clear that there is no such point, but rather a finely grained continuum connecting the abstract and highly teleological to the grittily concrete and only barely teleological, (1987: 44). 3 For Lycan mental kinds are a subset of teleological types occurring for the most part at a high level of functional abstraction (1987: 43).

188 Chapter relatively uncontroversial example is that the function of the heart is to pump blood. As we move down the levels the entities (ventricles, arteries, etc.) are characterized less teleologically and more mechanically. And when we drop down to the level of molecules, although there is still a functional way of characterizing molecules, we are less inclined to characterize molecules in terms of teleology and more inclined to characterize them in terms of how they fit into a particular mechanism Lycan s commitment to the continuity of levels of nature The second of Lycan s commitments is his commitment to a multiple hierarchy of levels of nature, each marked by nexus of nomic generalizations and supervenient on all those levels below it on the continuum (1987: 38). Call this the commitment to the continuity of levels of nature. This commitment contrasts with the view that there is a single functional level and a single structural level, defended by those who Lycan calls two-levelers. Against two-levelism Lycan points out that at any particular level the constituents of that level can be explained functionally by referring to their purpose or structurally by referring to their constitutive parts, which occupy a lower level of the hierarchy. The entities at this lower level can be characterized functionally or, by dropping down another level, by their structure. As he says, See nature as hierarchically organized in this way, and the function / structure distinction goes relative: something is a role as opposed to an occupant, a functional state as opposed to a realizer, or vice versa, only modulo a designated level of nature (1987: 38). Lycan does not offer a very thorough idea of what he has in mind as the features that individuate a level of nature. His definition is as follows: levels are nexus of interesting lawlike generalizations, and are individuated according to the types of generalizations involved (1987:

189 Chapter ). I am not convinced that introducing nexus of interesting lawlike generalizations is (or is even intended to) be a precise criterion. In any case I take it that this allows Lycan to draw on anything that falls within the purview of science. He can then employ the notion that different entities that science offers explanations for are organized into a hierarchy of levels. For instance, as Lycan says, cells can be characterized functionally, by reference to what they do, and structurally they are constituted of cooperating teams of smaller items including membrane, nucleus, mitochondria, and the like: these items are themselves systems of yet smaller, still cooperating constituents (1987: 38). And working up the levels, cells to look back upward along the hierarchy, are grouped into tissues, which combine to form organs, which group themselves into organ systems, which cooperate marvelously to comprise whole organisms such as human beings (1987: 38) A critique of Lycan s account These two commitments, to homuncular functionalism and the continuity of levels of nature, are, together, supposed to give us a picture of how the mental is related to the physical. They are combined such that the mental (or teleological) is at a higher level of nature, and as characterizations are offered that are less teleological that is, as we decompose mental capacities via homuncular functionalism we move down the levels of nature. So, on Lycan s account the commitment to the continuity of different levels of nature requires something like this: level 5: entity A has function F A 1 and structure S(B 1 & B 2 & B 3 ) level 4: entity B 1 has function F B 1 and structure S(C 1 & C 2 & C 3 ) level 3: entity C 1 has function F C 1 and structure S(D 1 & D 2 & D 3 ) level 2: entity D 1 has function F D 1 and structure S(E 1 & E 2 & E 3 ) level 1: entity E 1 has function F E 1 and structure S(F 1 & F 2 & F 3 )

190 Chapter Each entity can be characterized functionally or structurally and how this is done is relative to the level that one is focusing on. For instance, entity C has some particular function: function F C 1, and C s structure is explained (or determined) by the entities that compose it: D 1 & D 2 & D 3, which are found one level down. At this lower level, D 1 & D 2 & D 3 are characterized functionally and their structures are explained by the entities that are one more level down. Now we can add to this picture the commitment to homuncular functionalism. Homuncular functionalism suggests that there are at the higher levels, say level five, very teleological characterizations of psychological capacities. For instance, F A might be the capacity to comprehend language. Meanwhile, down at level one the characterizations are not very teleological at all and are no longer descriptions of psychological capacities. Therefore, we find that function F A (from level 5) is what gets characterized as abstract and highly teleological, while function F E (from level 1) is a function that we would characterize mechanically. One of Lycan s goals is to demonstrate that the two-leveler who adheres to an absolute function-structure (software-hardware, role-occupant) distinction is committed to a bipartite nature that is really an illusion. Lycan counters the two-leveler by observing that functional characterizations exist for all levels (save perhaps the very lowest). This does indeed work against two-levelers who are committed to an absolute function-structure distinction, that is, those who take it that at (or above) a certain place everything is only functional and below that point everything is only structural and not functional at all. However, a more lenient two-leveler, as (I suppose) I am, can very well grant that the entities at all levels can be functionally characterized, but still insist that a distinction a more general two-level type distinction can be made at that place between levels occupied by what

191 Chapter are only functional characterizations and levels where the entities can be characterized both functionally and structurally. Lycan says there is no such place. For example, he writes: There is no single spot either on the continuum of teleologicalness or amid the various levels of nature where it is plainly natural to drive a decisive wedge, where descriptions of nature can be split neatly into a well-behaved, purely structural, purely mechanistic mode and a more abstract and more dubious, intentional, and perhaps vitalistic mode certainly not any spot that also corresponds to any intuitive distinction between the psychological and the merely chemical, for there is too much and too various biology in between (1987: 45). However, on my account there is a place to drive a decisive wedge, namely, between descriptions that are placed at a higher level of explanation and descriptions that are found at a level of organization. Let me contrast Lycan s account with my own. Lycan s levels of nature may not be exactly the same thing as levels of organization, but we can take them as being similar for the moment. Levels of organization constitute one hierarchy on my account. At the various levels of organization we get descriptions of the entities that are found in nature, as well as descriptions of the functions that those entities have. In order to add higher level functional characterizations of mental capacities we need to turn to levels of explanation (although I am not making any claims about what is or is not teleological). 4 In particular, Marr s level of the computational theory is a description of the function that a series of entities performs. The tension between Lycan s account and mine indicates a disagreement over how to understand functional characterizations with respect to structural or physical characterizations. I agree that functions are found at all levels. However, my account allows that some functional descriptions of mental capacities for instance are instantiated in physical structures that have functional characterizations separate 4 I agree with Lycan that functions are at all levels of nature insofar as the entities found at each level have functions, but with respect to mental capacities they have to be placed at a level of explanation.

192 Chapter from (or in addition to) the mental functions. For instance, we can characterize the functions that neurons perform in biological terms, but we can also say that a series of neurons are carrying out a mental function, for instance memory. This possibility is denied by Lycan. Our competing accounts are illustrated in the figures below. Levels of Nature level 5 highly teleological level 4 Levels of Explanation functional characterization (of the mental) level 3 level 2 level 1 mechanical structural characterization Levels of Organization Figures 6.1 and 6.2. Lycan s account is illustrated on the left, mine on the right. For Lycan a mental kind would be found around what I have as level 5. Although, the levels 1 5 in the diagram of Lycan s account are taken from the list above, his account is not restricted to five levels. I agree with Lycan that functional characterizations can be offered at each level of organization, but in the diagram on the right I am just identifying the level of organization as the structure with respect to the functional characterization of the mental capacity. The problem with Lycan s account is that homunucular functionalism and the continuity of level of nature, although both have a levels structure, are not actually compatible with each other. As a consequence, they cannot simply be combined in order to offer a coherent account of the relationship between the mental and the biological. We can begin investigating the problem by looking at Lycan s homuncular functionalism. Homuncular functionalism is a type of analysis used by philosophers of psychology. Cummins (1975, 1983) has argued convincingly that functional analysis of which homuncular functionalism is a variety is a reasonable way to analyze a functional capacity. There is not

193 Chapter however, anything built into the technique of explaining a psychological capacity by way of decomposing homunculi that even mentions functions that have been selected by natural selection. Moreover, analyzing functional capacities by way of decomposing them into other less sophisticated capacities does not even require that the sub-capacities be instantiated in distinct physical entities. 5 All that is needed in order to construct a functional decomposition for a particular capacity is an understanding of the capacity and a little imagination. What Lycan is doing is motivating his view of homuncular functionalism by referring explicitly to theoretical entities, not physical components that each performs different aspects of the capacity. But then by stating that his flavor of functionalism is honest-to-goodness natural teleology (1987: 44), these theoretical entities, the homunculi, are given the status of actual physical entities that are presumed to fit somewhere into the levels of nature. The root of the problem seems to turn on different uses of the term structure. Lycan decomposes a mental capacity into several sub-capacities, each of which is a less sophisticated capacity, and then these sub-capacities are decomposed in the same way, and so on. When this occurs, the term structure refers to the organization of the sub-capacities at a lower level. Conversely, when Lycan describes levels of nature, he points out that at each level the entities can be characterized in terms of their structure. However, in the case of functional analysis the structural entities are not physical entities and do not occupy a level of nature. When we talk about structure with respect to functional analysis we are, basically, talking about a program or flowchart. A flowchart has an organizational structure, but the different functions that a 5 What I have in mind, generally speaking, by physical are those things described by physics plus any composites made up of those same things. However, it might be more helpful to think of physical entities as those entities that occupy a level of organization (or in Lycan s terms levels of nature).

194 Chapter flowchart identifies do not necessarily each have a physical structure that is found at a level of nature. So both homuncular functionalism and levels of nature identify structures (or structural features) that can be organized into hierarchies of levels. However, the way in which the term structure is being used is not the same in both cases. Hence the incompatibility between Lycan s two commitments. Once we separate the different uses of the term structure, then we see that we can make function-structure (i.e., two-level) type distinctions. Just stating that these functional entities are teleological that is they have been selected by natural selection does not demonstrate either (1) that they have in fact been selected for or (2) that they are even actual entities that occupy a level of nature. If Lycan is unable to demonstrate this, then the two-leveler can make a distinction in Lycan s hierarchy of levels at the place where structure switches from meaning a team of different functionally characterized entities to meaning physical realizer. 6 Lycan offers an example of the capacity for face recognition that may help to illustrate why homuncular functionalism and the continuity of levels of nature do not fit together (1987: 43 4). One way that face recognition might be carried out, he suggests, is by implementing the following sort of plan: a particular program is engaged only when the input is a face viewed from either the right, left or straight forward profile, a viewpoint locator identifies which profile it is, an analyzer then codes the relevant features (based upon what the viewpoint locator has told it) and then passes this information on to a librarian that compares this information with a memory store (see figure 6.3). If the librarian is successful in finding a match it will be able to look at the identification tag attached to the information stored in memory. The librarian will then pass the 6 Although this distinction will not be absolute since all levels will have functional characterizations.

195 Chapter information tag on to the public relations officer who will be able to give instructions to the appropriate motor subroutine that will verbally enunciate the appropriate name. This explanation is one step below the teleological characterization of a face recognizer. If information about any of these particular capacities was called for each could be similarly decomposed. For instance, the analyzer might be a projector that projects a grid onto the profile and a scanner that encodes each square of the grid in a binary code to be passed onto some subcapacity of the librarian. If more information about the scanner were required, the scanner could be decomposed into a light meter and some way of reporting 0 or 1 based upon the degree of darkness. The light meter could then be explained by invoking photosensitive chemicals, and so on. Thus the face recognizer has been decomposed after several steps downward into entities that are relatively non-teleological. A face recognizer a viewpoint locator analyzer librarian public relations officer motor subroutine projector & scanner lightmeter photosensitive chemicals Figure 6.3. Lycan s example of the decomposition of a face recognizer. In this example face recognizer is at the top of the hierarchy, and viewpoint locator, analyzer, librarian, public relations officer, and motor subroutine are its structure at the next level down. The entities at this level, analyzer for instance, has a functional characterization and is characterized structurally as projector and scanner, which are one more level down. Lycan may not mean this seriously as a description of a psychological process, but I take it that he

196 Chapter believes that a real description of a psychological capacity will be in a similar format. In an ideal case that moved from the psychological to the neurobiological, face recognizer would be the highest level of this hierarchy and the molecules that are found in neurons would be at or near the bottom. The problem that this example illustrates is that it is not obvious that these so called structural entities that occupy the levels below face recognizer are entities that exist (and hence occupy a level of nature). Rather it appears that this is only an example of functional decomposition and these entities are merely a team of different functionally characterized entities (that is, an example of homuncular functionalism). Analyzer, librarian, and public relations officer are clearly not in the language of neurobiology. This level occupied by analyzer, librarian, and public relations officer is however a nice example of functional analysis (that is, functional decomposition). The burden is on Lycan to show that they are the actual physical structure of the face recognizer, and occupy a level of nature. Lycan has not shown that they are physical entities and I do not see why the critic of Lycan should accept that just because the functional decomposition has been successful that it is also a case of demonstrating physical instantiation at various levels of nature. Lycan can decompose the function of the face recognizer as far down as he wishes (and there may be some utility to this), but until he makes the move to language that picks out actual physical entities that reside at levels of nature the explanation will remain purely functional. Based on what I have said about Lycan s account I take it that there is a place where the switch can be made from the functional language that describes the capacity (which I place at a level of explanation) to the physical entities that carry out this capacity and which occupy a level of nature (or in my terms a level of organization). And then there may also be levels below this

197 Chapter level (eg., if we introduce physical talk at the cellular level, then there are levels: the molecular, the atomic, etc, below this). This may not be the absolute two-levelism that Lycan is arguing against, but there is a striking similarity here. A portion of Lycan s explanation is in functional language, and then there is a specific place where the switch is made to physical entities that occupy a level of nature. This criticism can be expanded by looking at another example that Lycan offers. This example is interesting because it is tractable and is offered by Lycan as a way of illustrating how teleological functions can be decomposed while maintaining the continuity of levels of nature. However, as I see the example, it highlights the problem with Lycan s account: these two commitments do not go together. Instead this example is handled better by my account. The example of Lycan s, which is supposed to illustrate degrees of teleologicalness, is: One and the same space-time slice may be occupied by a collection of molecules, a piece of very hard stuff, a metal strip with an articulated flange, a mover of tumblers, a key, an unlocker of doors, an allower of entry to hotel rooms, a facilitator of adulterous liaisons, a destroyer of souls (1987: 43, discussed further on 137 n12). This gives us the hierarchy: a destroyer of souls a facilitator of adulterous liaisons an allower of entry into hotel rooms an unlocker of doors a key a mover of tumblers a metal strip with an articulated flange a piece of very hard stuff a collection of molecules The two ideas that are supposed to be captured here are first, that the most teleological description is at the top of the hierarchy (a destroyer of souls) and by moving down the hierarchy

198 Chapter the descriptions become less teleological. And then second, this is also supposed to illustrate the way in which function and structure are relative to a level (see 1987: 137 n12). Let s start with key. Fitting with Lycan s notion of a hierarchy of levels of nature it is a functional term that can also be characterized structurally. The structural description Lycan intends is metal strip with an articulated flange (1987: 137, n12). Metal strip with an articulated flange can then be structurally described as a piece of very hard stuff, and a piece of very hard stuff can be structurally described as a collection of molecules. 7 However, this description does not work in the manner that it is supposed to because there is a break somewhere in-between a metal strip with an articulated flange and an unlocker of doors. On one side of this break there are entities that are characterized in terms of their physical structure and on the other side of this break things are characterized only functionally and are not, at least explicitly, characterized in physical terms. On the functional side are the four highest levels: an unlocker of doors, an allower of entry to hotel rooms, a facilitator of adulterous liaisons, and a destroyer of souls, all of which are purely functional descriptions. After the metal strip with an articulated flange, Lycan never moves to a higher level of physical material, so all of these functional descriptions are instantiated at the same level of nature (or something like a level of nature). An unlocker of doors, an allower of entry to hotel rooms, a facilitator of adulterous liaisons, and a destroyer of souls, do all have a physical structure, namely a key shaped piece of metal. However, each of these four functional 7 This might be more levels than is really necessary since we could eliminate a piece of very hard stuff by pointing out that if the structure of a key is a metal strip with an articulated flange, then the metal has to be a hard one (And in fact Lycan ignores this level (a piece of hard stuff) when discussing the instantiation relations in the endnote (137 n12)). Also, mover of tumblers is a key s function, not its structure, so it is not clear why it gets a level to itself between key and metal strip with an articulated flange.

199 Chapter characterizations does not have its own unique physical structure so, right here we can drive a decisive wedge between the functional and the structural. This example is not an illustration of Lycan s account, it is a counterexample to it. It is not however, a problem for my account. On the contrary, it just reinforces my point that a set of purely functional levels may be instantiated at one level of nature. metal strip with an articulated flange piece of hard stuff collection of molecules destroyer of souls facilitator of adulterous liaisons allower of entry into hotel rooms unlocker of doors key piece of hard stuff Figure 6.4. Lycan s key example illustrated using my account of levels of organization and levels of explanation. It may not be the case that the five functional levels line up in such a neat hierarchy, but the idea is that all are realized at the same level of organization. What I want to take from this example is the idea that we do find a place in a series of levels of nature where certain functional descriptions are instantiated. If we keep track of what descriptions belong at higher levels of explanation, then we have a coherent way of understanding the relationship between the psychological (i.e., the higher level functional) and the biological. If we use only one hierarchy, as Lycan does, then we obscure this relationship because we cannot separate different kinds of descriptions from each other. We can conclude that there may be a series of levels that are only functional (all of which are implemented in the same physical entity). Lycan may have made some progress against the two-levelers by pointing out that functional characterizations can be made of the entities all the way down the hierarchy. He has not however, closed off the possibility that there are still levels

200 Chapter that are only functional. All that the critic of Lycan has to do is insist that some functional descriptions (i.e., higher level functional descriptions) are distinct from the descriptions where what is functional and what is structural is relative to a level. This we get on my account with the higher levels of explanation and levels of organization. But besides this problem with Lycan s account, the lesson to draw here is that we need a way of distinguishing between these different kinds of descriptions in order to understand the relationship between the psychological and the physical. And this we get from my account, but not from Lycan s Kim Before moving on to Craver s account, I want to briefly discuss Kim s (1998) use of orders and levels, which resembles my account in some respects. However, it should be pointed out that while the view that Lycan defends can, I think, be taken as contributing to both the philosophy of psychology and the metaphysics of mind, Kim s account is less straightforwardly contributing to the philosophy of psychology. Nevertheless, it is worth seeing how Kim s account is similar to mine. Kim suggests that some functional properties, for instance, mental properties, are secondorder properties of other, more basic first-order properties. He writes an example of a functional property is dormitivity: a substance has this property just in case it has a chemical property that causes people to sleep. Both Valium and Seconal have dormitivity but in virtue of different first-order (chemical) realizers diazepam and secobarbital, respectively (1998: 20 1). In this case the chemical compounds for these drugs are the first-order properties and dormativity is the second order property that is realized by the first-order property.

201 Chapter Based upon this view, Kim draws much the same conclusion that I do concerning Lycan s commitment to the continuity of the levels of nature, namely, that not all functional characterizations are entitled to a unique structural characterization as Lycan would have it. Rather in some cases there may be multiple functional characterizations of one set of structurally characterized entities (figure 6.3). In Kim s terms, there may be higher-order functional properties of a particular first-order (base) property. Concerning Lycan s continuity of the levels of nature Kim says, the realization relation does not track the micro-macro relation. The reason is simple: both second-order properties and their first order-realizers are properties of the same entities and systems... a second-order property and its realizers are at the same level in the micromacro hierarchy; they are properties of the very same objects (italics removed, 1998: 82). What Kim calls micro-macro levels are essentially what Lycan calls levels of nature and what I call levels of organization. Kim s point is that given the appropriate level of nature, a mental property is a second-order property of the entities found at the level of nature. And consequently the mental property is not at a higher level of nature than its realizer. Hence, the way in which Kim employs orders is not unlike the way that I use levels of explanation. Orders and levels of explanation both provide a way of describing the entities and activity at a level of organization without moving to a higher level of organization. Kim is focused on higher order functional properties while I allow that higher levels of explanation need not be functional descriptions although they can be. This is a nice convergence between Kim s work in the metaphysics of mind and my project in the philosophy of psychology. There is still a gap between our projects, however, that I am not going to address here. For instance, I have not expressed a view about realization or

202 Chapter about mental causation, and I do not think that my account commits me to the views that Kim expresses on these issues. 6.2 Craver Craver s account of mechanistic levels Craver s account of levels is based upon his analysis of mechanisms. For Craver mechanisms in neuroscience are collections of entities and activities organized in the production of regular changes from start or set up conditions to finish or termination conditions (2002: 84). This organization of the entities and activities that constitute a mechanism, both the spatial and the temporal, is essential for the successful performance of the mechanism s role. The role is the behavior or activity that the mechanism (as a whole) performs. In the case of a mechanism that has multiple levels the mechanism is composed of a number of mechanistic levels. Each level is occupied by what is essentially a mechanism itself insofar as each of these mechanistic levels is identified by entities and activities organized in the performance of a higher level role (2002: 89). So, the whole multilevel structure is a mechanism and at each level there is basically a (sub-) mechanism. In the case of a particular multilevel mechanism, some sort of operation is identified: a task or process, the exercise of a faculty, or the performance of some function (2002: 84). This operation, as it is investigated, decomposes into several different mechanistic levels. At each level the mechanism is defined spatially and temporally, so that the entities composing the mechanism must be appropriately located, connected, structured and oriented with respect to one another [and temporally:] the activities composing mechanisms also have crucial temporal orders, rates, and durations (2002: 84).

203 Chapter The relationship among different levels is identified by the decomposition of the activity of an entity at one level into a series of entities and activities at a lower level (2002: 89 and figure 6.4). As Craver describes this vertical organization it is: a decomposition into entities and activities organized in the performance of a higher level role. The activities and properties of the entities in the lower level mechanism may themselves be subject to mechanistic decomposition. In such cases, each mechanistic decomposition adds another level to what may become a multilevel mechanism (2002: 89). This model is meant to provide a complete picture of the levels that carry out a role (which can be a psychological capacity). In the next section I contrast Craver s analysis of a level with my own and identify some tensions between our accounts. In the section that follows (2.3) I review an example of Craver s that demonstrates how this model explains spatial memory and discuss some problems with two of his levels. In the final section I will examine the relationship that Craver suggests exists between levels more carefully and raise a more serious problem for his account The mechanistic level Craver and I both conceive of a level as a feature of relatively stable and regular interactions among entities. Where these sorts of interactions occur we have a level, which on my account is a level of organization, and for Craver is a mechanistic level. And further we are both interested in isolating the entities and their activities at these levels that carry out a particular capacity, or in Craver s terms a particular role. The main difference between our accounts of what is found at a level is that levels of organization identify all of the interactions that occur (or potentially could occur) among a series of entities. This is broader than Craver s notion of a mechanistic level, which only includes the

204 Chapter entities that participate in carrying out one particular role. For instance, a mechanistic level could include a pyramidal cell that is part of the mechanism for some capacity. Another pyramidal cell that is not part of the mechanism for that capacity would not be at that same mechanistic level (see Craver forthcoming, chap. 5: 21 22). In part the reason for this view seems to be that it is the result of the way in which Craver views the relationship between levels, which is a decompositional relationship. That is, if a component at one level is decomposed into a series of pyramidal cells, then those particular cells occupy the lower mechanistic level and Craver is agnostic about cells that are not part of that series. I discuss this aspect of Craver s account in section But I can right now contrast Craver s view of what is found at a level with my own. Like Craver, I am interested in distinguishing the activities that carry out different capacities from each other. But in order to do this I need to introduce levels of explanation. At a level of organization we find a broad series of interactions that are not limited to just one capacity, while the lowest level of explanation is a description of only those activities that carry out the particular capacity that we are interested in. Hence, on my account the lowest level of explanation identifies one set of interactions that are occurring within a larger series. What the introduction of the level of explanation accomplishes on my account Craver already has with his mechanistic levels, that is, a specification of the activities that carry out the capacity (at that level). One advantage of my account is that we can grasp levels of organization prior to knowing how a capacity is carried out. That is, we have identified the level of organization and then we look at how the capacity is carried out. On Craver s model there is no conception of what a level is prior to the identification of the mechanism. Craver may not think of this as an advantage for

205 Chapter my account, but it certainly seems, contra his account, that neurobiologists have some notion of levels in mind prior to the discovery of (or just the investigation of) a mechanism. Given that this is the case, the legitimacy of Craver s account turns on his use of decomposition to establish his mechanistic levels. This is to say that Craver can reply that there may be some vague notion of levels in the background, but his analysis of mechanistic levels, which are found by decomposing the components of one level into lower mechanistic levels, is the precise account of levels. However, if decomposition is not in fact the relationship that holds between Craver s levels, a point that I will make in section 6.2.3, then it is not clear that mechanistic levels are an accurate description of these neurobiological activities. A second advantage of my account is that the distinctions made between different capacities (e.g., where vision stops and where memory begins) are only distinctions that concerns the level of explanation, not the level of organization. For Craver s mechanistic levels the distinction between different capacities is a more substantial issue since what falls outside the boundaries of a mechanism is no longer at the same level. But neurobiological activities in the service of vision and those in the service of memory do interact with each other. Therefore an analysis of how to determine the boundaries of a mechanism is required. Concerning this issue Craver and Bechtel say, One reason that setting the boundaries of mechanisms is often controversial is that what is inside or outside depends on additional judgments of explanatory relevance. The components of most mechanisms have strong interactions with components that, intuitively, aren t part of the mechanism Investigators have to decide to put some things in the mechanism (viewing them as components of the mechanism), and to leave some things as necessary background conditions for the operation of the mechanism (2005: 5). The interesting point here is that Craver and Bechtel acknowledge that determining the boundaries of a mechanism, at least sometimes, depends upon explanatory goals. And that the

206 Chapter interactions among entities cut across these boundaries. The advantage of my model is that, with levels of organization, it can account for a series of interactions that are not limited to what we would call a single mechanism, as well as the choices that are made when we limit a particular series of interactions in order to describe a single capacity (with levels of explanation). This discussion concerns the merits of the way in which Craver conceives of a mechanistic level. I am now going to look at an example of Craver s that will give us a chance to examine his account of a multilevel mechanism Spatial memory Craver offers, as an example of his analysis of mechanistic levels, a series of levels for spatial memory (2002: 89 91, also 2003: 160). He proposes four levels: a behavioral-organismic level is at the top, then a computational-hippocampal one level down, below that an electricalsynaptic level and at the bottom a molecular-kinetic level. 8 However, my main concern with this particular account of spatial memory is that some of these levels do not meet the standard that Craver has specified for a mechanistic level, insofar as, some of these levels are not occupied by entities and activities organized in the performance of a higher level role. 8 Concerning the status of these four levels Craver says in another place: As currently understood, there are roughly four levels in the LTP-spatial memory hierarchy (2003: 160).

207 Chapter the behavioral-organismic level the computational-hippocampal level the electrical-synaptic level the molecular-kinetic level Figure 6.5. Craver s four mechanistic levels for spatial memory. From Craver 2002: 90. Starting at the bottom of Craver s hierarchy of the mechanistic levels for spatial memory there is his molecular-kinetic level. At this level Craver identifies the molecules and the activities they are engaged in when long-term potentiation (LTP) occurs. Some of the entities at this level are: NMDA and AMPA receptors, glutamate, Ca 2+ ions, and Mg 2+ ions, and these entities engage in activities like attracting and repelling, binding and breaking, phosphorylating and hydrolyzing (2002: 89). Above the molecular-kinetic level is what Craver calls the electricalsynaptic level. Found at this level are such entities as neurons, synapses, and dendritic spines and such activities as vesicular release and the generation and propagation of action potentials (2002: 89). With these lowest two levels of Craver s we get a relatively clear idea of what he intends by mechanistic levels. The molecular activities that occur at the molecular-kinetic level when long-term potentiation occurs, are, reasonably, described as a mechanism (see figure 6.6 below

208 Chapter for a more complete diagram). The entities and all of their interactions that are necessary for this process are specified. And at the electrical-synaptic level action potentials propagate from the cells in the dentate gyrus to cells in the CA3 region of the hippocampus, which in turn project to cells in the CA1 region of the hippocampus and so on. The activities at this level, at least as Craver has described this process, seem to me to be a somewhat looser sense of mechanism than we find at the lower (molecular-kinetic) level. At the molecular level, we expect that what is important about this process is relatively fixed, such that each occurence of LTP is more or less the same. When we switch to talking about the activity of neurons, we expect that the basic types of activities will be the same, but we do not expect that the specific activities will all be the same. After all, we want the memory process to treat different stimuli uniquely. 9 Nevertheless, I do not find it problematic to call the activities at this level mechanistic. The next highest level is Craver s computational-hippocampal level. Here an explanation of the hippocampus s job in spatial memory is offered: its cytological, anatomical, and structural features, its pathology, its connectivity with other brain regions, and the computational or processing stages it is thought to perform (2002: 89). As far as I can tell this is not a mechanistic level. I have, in several places in chapters one, two, and five, criticized the idea that brain areas, such as the hippocampus, constitute a level of organization because interactions that brain areas might have cannot be specified. The same concerns apply here, and can be stated explicitly in terms of whether or not a brain area such as the hippocampus is part of what Craver calls a mechanism. 9 This is assuming that we agree that at the cellular level we describe the activity that occurs from the periphery to the hippocampus and then back to the cortex (cf. the example of Lund s in chapter 1).

209 Chapter Presumably Craver takes it that the hippocampus is an entity, and an important entity to reference when talking about certain kinds of memory. However, he has set the bar much higher than this for an entity to be a component in a mechanism. And, it is not obvious that the hippocampus meets this standard. That is, it does not appear to be the case that the hippocampus participates in activities organized in the production of regular changes from start or set up conditions to finish or termination conditions (2002: 84). I am not going to review all of the problems that I have raised concerning brain areas occupying a level, but I will offer a couple of criticisms that are relevant to Craver s project. First, besides the hippocampus, Craver does not say what the entities and activities are that operate at this level. He points to the hippocampus s connectivity with other brain regions, and we might assume that he means that the hippocampus interacts with the parietal and temporal cortex (for example). However, the idea that the temporal lobe interacts with the hippocampus, which then sends information back to the temporal lobe does not, as I just said, seem to meet Craver s definition of a mechanism. It is in a certain sense true that the hippocampus interacts with other areas of the cortex, but it is a very loose way of talking. In particular this way of talking does not capture what Craver means by mechanism. And further, it is not obvious that an explanation in terms of specific spatially and temporally organized activities among the hippocampus and cortex areas could be given. 10 Craver also says that this level is concerned with the cytology, anatomy, structural features, and pathology of the hippocampus. However, it is not clear how these different perspectives lend themselves specifically to explanations in terms of mechanisms in general or 10 It can also be pointed out that if there were a mechanism here (which included the hippocampus), Craver would hardly be straining his readers by laying it out particularly given the detail that he puts forward for the cellular and molecular levels.

210 Chapter this mechanistic level in particular. It does not seem to matter if the entities and activities that occur at a particular level are uncovered by a neuroanatomist or someone working in neurophathology, or both for that matter. The whole point of a mechanistic explanation is to lay out what the entities, activities, and their organization are such that they perform some role. It seems tangential for Craver to point out that researchers from different areas work at this level, especially without specifying what the mechanism is (i.e., the interactions) that they are working on. It also bears mentioning that if cytology is an area of biology that is concerned with the structure and function of cells, then it belongs at the level where cells are found (Craver s electrical-synaptic level) not at this hippocampal level. Moreover, I do not see how the study of the anatomy, structural features, and connectivity of the hippocampus really differ. In any case, none of the three suggest an answer to the problem that I began with concerning the idea that the hippocampus cannot itself be an entity in a mechanism. Given what I have said in earlier chapters concerning the problems with a brain areas level and since Craver does not offer any compelling arguments for his computationalhippocampal level, I think my conclusion stands: brain areas such as the hippocampus do not occupy a level when a level is understood as entities participating in specific interactions. Since interaction among entities is a requirement for Craver s mechanistic levels I am skeptical that there should be a computational-hippocampal level in his hierarchy, i.e., his multilevel mechanism. The highest level in this hierarchy is the behavioral-organismic level. The behavioralorganismic level is where spatial memory is explained in terms of the various types of learning and memory, the conditions under which different memories may be stored or retrieved, and the

211 Chapter conditions under which storage or retrieval are likely to improve or fail (2002: 89). In this case, it is again not clear that this meets Craver s definition of a mechanism. In his description of the behavioral-organismic level Craver does not talk about entities and activities organized in particular ways which is supposed to be the mark of an explanation of a mechanism. 11 Although this description of the behavioral-organismic level does not look like a description of a mechanism, it does seem to identify the role that the mechanism has. Recall that a role is the activity or behavior of the mechanism as a whole (2002: 84). And in his description of the behavioral-organismic level for spatial memory Craver basically points to various features of this type of memory, the conditions under which this type of memory is utilized, and how this type of memory is different than other types of memory. In other words, Craver just appears to be giving an explanation of the role for this multilevel mechanism, and so, as with the computational-hippocampal level, I am suggesting that Craver s highest level is not actually a mechanistic level. All of this having been said, Craver is left with a model that, at least in outline, is similar to mine. He has a mechanistic level for macromolecular activity and a mechanistic level for the activity of neurons. Craver s computational-hippocampal level, is eliminated because it is not a genuine mechanistic level. And his highest level the behavioral-organismic level which is also not a genuine mechanistic level, is recast as a description of the role for this mechanism. Therefore, we have, in Craver s terms, a mechanism that has a role and this role (spatial 11 It is possible that if the organism is taken to be one entity and the things in the environment are others, then the interactions among these entities could be put together in the language of a mechanism. This would make this level similar to my level of individuals. The problems with doing this are (1) Craver does not indicate that this is what he has in mind, (2) this could only be understood loosely as a mechanism since organisms at least humans do not generally participate in activities that are highly spatially and temporally organized and (3) in Craver s account a mechanism needs a role in order to be coherent so settling on this as a role and not a mechanistic level appears to help Craver s account.

212 Chapter memory) is the activity that is described at these two mechanistic levels. And so the four levels that Craver proposes can be, by merely applying his own definition of a mechanism, narrowed to two levels. This does not share the exact format of my account, but I think that it is clear that we are both offering accounts of the same activities and coming to, if not the same, at least similar conclusions about how levels in the brain should be conceptualized Decomposition If we look at a mechanism that is composed of neurons and their activities, or a mechanism composed of macromolecules and their activities, then I am (more or less) sympathetic to the notion of levels of mechanisms. However, this final section reviews a problem with Craver s account that I have left aside up until now, namely, his description of the relationship between his mechanistic levels in terms of decomposition. This is a large issue that I will only treat briefly here, but I do want to point to one problem with the notion of decomposition that arises in Craver s account of spatial memory. For Craver, a component that is part of a mechanism at one level decomposes to reveal a complete mechanism at a lower level (figure 6.5; 2002: 89; 2005: ; forthcoming, chap. 5: 20 1). 12 This is similar to the view that Lycan defended (see for example figure 6.3). However, although it has the format of Lycan s homuncular functionalism, Craver is clear in insisting that the decomposition that he is interested in is decomposition into actual (physical) components, not theoretic sub-capacities (2002: 88). 12 Craver (forthcoming) says, Lower-level components (entities and/or activities) are organized together to form higher-level components (chap. 5: 20).

213 Chapter Figure 6.6. Craver s schematic showing the relationship between levels. A component at each level is decomposed into a series of entities and activities (i.e., a mechanism) at the next level down. From Craver (forthcoming, chap. 5). This account of the relationship between levels is problematic because this does not appear to be the relationship that holds between levels that fall within the scope of neurobiology. A mechanism at one level is a series of activities, but it is not a series that, collectively, will always compose a higher level component. Taking Craver s example of long-term potentiation (LTP), if we look at the range over which the activities that carry out LTP at the molecular level occur then we find the following: we begin, at the presynaptic terminal with the release of the neurotransmitter glutamate; from there we move onto the activities that occur at the postsynaptic site (within the postsynaptic cell s dendrite); these activities progress to the cell nucleus in the cell body where gene expression occurs; and from there the activities that we are interested in move back to the postsynaptic site, and possibly to the presynaptic terminal as well (Kandel 2001; figure 6.6). These activities and the entities that carry them out do not, however, form any single entity at a higher level.