Chapter 7 Mental Representation Mental Representation Mental representation is a systematic correspondence between some element of a target domain and some element of a modeling (or representation) domain. A representation, whether it be mental or any other, is a system of symbols. The system of symbols is isomorphic to another system (the represented system) so that conclusions drawn through the processing of the symbols in the representing system constitute valid inferences about the represented system. Isomorphic means `having the same form.' The following figure is a typical example of how we represent information mentally in our minds. Figure 8.12 A hierarchical network representation of concepts. Source: Collins and Quillian (1969) The cognitive psychologists have always agreed on the fact that human information processing depends on the mental representation of information; but there is a great disagreement with regard to the nature of this mental representation of information. Symbols are the representations that are amodal. They bear no necessary resemblance to the concept or percept they represent. The systematic correspondence between the two domains may be a matter of convention (only). For example, in algebra, we denote the different variables as x, y, z, and so on, but neither of these symbols have a direct resemblance to what they represent. Similarly, while solving a geometrical problem involving geometrical shapes, we might assign symbols such as A, B, or C to such geometrical shapes, even though these symbols do not have a direct resemblance to the shapes. Images are another way how the information can be represented in our minds. Images are basically representations that resemble what they represent in some non-arbitrary way. The systematic correspondence between the two domains is iconic. For example, a map of a particular city, or a caricature might resemble to what it is supposed to represent in terms of features iconically, but is not an exact replication of the same. Symbols and images are some basic ways by which information can be represented mentally. Some things such as visual percepts are almost obviously represented as images, while some other things
such as abstract concepts are a difficult thing to represent as images. For example, if a person is feeling tired of listening about a particular movie, so then it would be difficult for that person to represent that feeling as an image. Furthermore, some things fall in between the two. For example, the concept of a dog in general; this concept of dogness can both be represented as a visual percept as well as an abstract thing. Over the years, a number of studies have provided evidence regarding the mental images. In one such study, the participants were presented with some pictures of abstract 3D objects. Then the participants were given an object-matching task, and were asked; Are these two objects the same or not? It was seen that on correct same responses, subject took longer when there was a greater angle of rotation between the two objects. These results suggest that the participants were rotating the images until they matched up in their mind s eye. Subjects had to judge whether the two stimuli shown in Panel A are the same as each other,but viewed from different perspectives;likewise for the pairs shown in B and C.Subjects seem to make these judgments by imagining one of the forms rotating until its position matches that of the other form.[after Shepard & Metzler,1971]. In another study, the participants were engaged in a property listing task in which they had to list a few properties of some object. The subjects were asked to name a few properties that they thought were true of that objects. In one such task, the subjects were asked to name a few properties of a watermelon. The reported answers of the subjects included the answers that the watermelon is green, heavy, round, is generally bought in summer, etc. In another task, the subjects were asked to list a few properties of half a watermelon. Now the answers included that it is pink, has seeds, and is sweet, watery, and so on. These differences in the answers about essentially a same object showed that the responses the participants gave were dependent in part, on the imagery.
Imagery and Functional Equivalence Hypothesis Mental imagery (varieties of which are sometimes referred to as visualizing, seeing in the mind's eye, hearing in the head, imagining the feel of, etc.) is an experience that resembles perceptual experience, but occurs in the absence of the appropriate external stimuli. It is also generally understood to bear intentionality (i.e., mental images are always images of something or other), and thereby to function as a form of mental representation. Traditionally, visualmental imagery was thought to be caused by the presence of picture-like representations (mental images) in the mind, soul, or brain, but this is no longer universally accepted. The Functional Equivalence Hypothesis of imagery assumes that visual imagery, while not identical to perception, is mentally represented and functions the same as perception. This hypothesis was first suggested by Shepard and Kosslyn. According to this, an image is isomorphic to the referent object (second-order), meaning spatial relations are analogous, and an image is an analog representation of the object, as shown by mental rotation and image scanning. Propositions The proposition is the most basic unit of meaning in a representation. It is the smallest statement that can be judged either true or false. For example, Fred is tall is a single proposition coded as a relation with two arguments (is, Fred, tall). Similarly, The ants ate the sweet jelly that was on the table expresses four propositions. Furthermore, propositions are a means of specifying relationships between different concepts. Latent Semantic Analysis is a mathematical procedure for extracting and representing the meanings of propositions expressed by a text. It represents the co-occurrence of words and their contexts. Using a database of co-occurrence relations, it can compute the similarity in meaning of two words or texts. Figure 8.5 An imaginal and a propositional code for the concept of a robin Propositions differ from the images in the sense that they are abstract means of mental representation, whereas the images are the perceptual means of mental representation. Propositions are schematic and verbal, while the images are concrete and nonverbal. Furthermore, Propositions can be coded as a relation and arguments, and each proposition is an assertion which may be true or false.
Figure 8.9 The star of David demonstration of the limitations of visual imagery The propositional theory to mental representation believes that there is a single code which is neither visual nor verbal but propositional in nature that is used to store and mentally represent all information. Propositions can be linked together in networks, with two closely related ideas joined by sharing a number of propositions. In 1973, Pylyshyn asserted that the propositional theory could explain the results of imagery experiments. He believed that all the information is mentally represented and stored by propositions, and further suggested that the participants in visual imagery experiments might look as if they were consulting or manipulating internal visual representations, but they would actually be using internal propositional representations, which are the same kind of representations that underlie their processing of verbal materials such as sentences or stories. Kosslyn in 1976, further attempted to test these assertions though experiments, but found that the propositional theory could not predict the performance of the participants when they reported to use imagery in the tasks. Semantic Network Models Vs Feature Comparison Models A semantic network, or frame network, is a network which represents semantic relations between concepts. This is often used as a form of knowledge representation. Collins and Quillian suggested that a network consists of a number of nodes, which correspond roughly to words or concepts. Each of these nodes is connected to related nodes by means of pointers or links that go on from one node to another. This collection of nodes associated with all the words or concepts one knows about is called the semantic network. The feature comparison model assumes that the meaning of any word or concept consists of a set of elements called features. These features are of two types; defining features and characteristic features. Defining features are those that must be present in every example of the concept, while the
characteristic features are those which are usually but necessarily present. This model usually works in stages. In the first stage, the feature lists of the concerned concepts are accessed and comparisons are performed. If the lists show a great deal of overlap or if the overlap is very small, then the response is made quickly. However, if the overlap is neither very high nor very low, then the second stage of processing occurs where the comparison is made between the sets of defining features only. The feature comparison model also has explained the category size effect which refers to the fact that if one term is a subcategory of another term, then people will generally be faster to verify the sentence with the smaller category. For example, people would be faster in verifying the sentence A Labrador is a dog than to verify A Labrador is an animal. This happens because as categories grow larger, for example from Labrador to dog to animal to living things, they also become more abstract. And thus when the abstractness increases, the defining features become fewer in number. The two models, semantic network model and the feature comparison model differ from each other on a number of points. Firstly, the semantic networks model is a hierarchical network of concepts, whereas in the feature comparison model, each concept has been defined at each level. Furthermore, the semantic network model takes into account the principle of cognitive economy which states that properties and facts are stored at the highest level possible, and are represented only once in the hierarchy, and also uses word net to represent meanings.. While the feature comparison model explains the typicality effect through different stages of features search. Concepts Concepts are categories of things, events, or qualities that are linked by some common feature (s) in spite of their differences. Medin, in 1989, defined a concept as an idea that includes all that is characteristically associated with it. In other words, a concept can be said to be a mental representation of some object, event, or pattern that has stored in it much of the knowledge typically thought relevant to that object, event or pattern. For example, for most of the people, the concept of a dog would consist of information that includes that a dog is an animal, has four legs and a tail, has a reputation of being man s best friend, is a common pet, and so on. Concepts help us to organize our knowledge base. They also allow us to categorize things, and help us create mental slots in which we can sort the things we encounter and help us to treat the new things which we have never encountered before in the same way as we treat the familiar things that we perceive to be in the same set. Thus, concepts play an important role in our mental life, and without them our lives would be chaotic. Concepts can be of different types.ly, concepts have been classified into two types, namely, simple and complex concepts.
Simple Concepts - Simple concepts are those concepts that are based on a single common feature between various things, events, or qualities. For example, all animals are alive; anything living is composed of cells, etc. Complex Concepts Complex concepts are the concepts that are based on many common features between things, events, or qualities. Complex concepts are further divided into two types; conjunctive and disjunctive concepts. Conjunctive Concepts Conjunctive concepts are those concepts that help us to determine the similarity between tow dissimilar objects. For example, how is a pencil and a telephone alike. Disjunctive Concepts Disjunctive concepts help us to determine how two highly similar things differ from each other. For example, how is the right hand different from the left hand. Classical view of Concepts The classical view of concepts proposed that all the examples or instances of a concept share fundamental characteristics or features; and the features represented are individually necessary and collectively sufficient. This view states that each example must have that necessary feature if it is to be regarded as a member of the concept. In other words, the defining features are related by a conjunctive rule and also define the category membership on all or none basis. Some of the important assumptions of this view can be enumerated as follows This view assumes that the concepts mentally represent lists of features. They are not representations of particular examples but rather contain information about the properties characteristics that all examples must have. Further it assumes that the members of a category either have all the necessary and sufficient features or lack one or more of these features. It also assumes that all members within a category are created equal. Prototype View A prototype can be defined as the best or most typical example of a category that serves in the mental representation of a concept. According to the prototypic view, the range of feature variation on a stimulus dimension and feature frequency of occurrence defines in part the gradient of category membership. The gradient creates typicality effects in categorization speed, acquisition order, and priming. Prototypes are basically idealized representations of some class of objects or events. This view holds that the prototypes of concepts include those aspects or features that are characteristic or typical of the members of the category rather than necessary and sufficient. It is not necessary that a particular feature or aspect be present in an object for it to count as a member of the category, but the more characteristic features or aspects an object has, the more likely it is to be regarded as the member of the category.
The prototype view of concept explains the typicality effects by reference to family resemblance. The more characteristic features an instance of a concept has, the stronger the family resemblance between the instance and other instances, and therefore the more typical an instance it is. Figure 8.2 Typicality of members in a basic-level category For example, a robin or a sparrow is thought to be a more typical bird than a penguin because the other two possess more characteristic bird features such as is small, eats worms, flies, and lives in a tree. Thus, the general idea of a prototype view can be said to be that the concepts have one or more core representations based on a family resemblance structure, but have no rigid boundaries. Schema View Schema is a cognitive structure that organizes related concepts and integrates past events. The term schema usually refers to something larger than an individual concept. In other words, a schema is an active organization of past reactions, or of past experiences, which must always be supposed to be operating in any well adapted organic response. Thus, a schema is a cognitive framework or concept that helps organize and interpret information. Schemas can be useful because they allow us to take shortcuts in interpreting the vast amount of information that is available in our environment. The use of schemas as a basic concept was first used by a British psychologist named Frederic Bartlett as part of his learning theory. Bartlett's theory suggested that our understanding of the world is formed by a network of abstract mental structures. A script is a schema for routine activities, and thus scripts represent routine activities (e.g., a restaurant script). Cumulative recall of script events is linear whereas object exemplars follow a negatively accelerated curve. Scripts are thought to be used in a variety of situations, and also let us make a number of inferences. The schemata/script view of concepts, thus, assumes that concepts are schemata or frameworks of knowledge that have roles, slots, variables, and so on. Meta-representation and Theory of Mind Meta-representation can be defined as a mental representation of another mental representation. Thinking about thinking requires meta-representation. For example, pretending a banana is a telephone requires a meta-representation linking the two object concepts. Meta-representation thus affords flexible and creative cognition. A meta-representation is a representation of a representation: a higherorder representation with a lower-order representation embedded within it. The use of metarepresentation develops between ages 2-4. Theory of mind refers to the human ability to infer that others, like ourselves, have mental states. It helps account for why we are not all adherents of solipsism. By age 4 children can not only pretend but can predict the consequences of another having false beliefs. In other words, theory of mind deals with the ability to form thoughts about attributed thoughts. Suppose a child sees a ball being put into a box. Having formed the thought in (1), he may go on, by observing his companions, to form thoughts of the type in (2): 1. The ball is in the box.
2. (a) John thinks the ball is in the box. (b) John thinks the ball is not in the box. (c) John thinks Sue thinks the ball is in the box (d) John thinks Sue thinks the ball is not in the box Sometimes, people may differ, for example, in their ability to attribute to others beliefs incompatible with their own. A child who believes (1) and lacks this ability would be limited to the metarepresentations in (2a) and (2c). A child with first-order theory of mind could attribute to others beliefs that differ from his own (as in (2b)); and one with second-order theory of mind could attribute to others beliefs about the beliefs of others which differ from his own (as in (2d)). Mind-blindness is an inability to understand that others possess mental representations and is characteristic of autism. An autistic child is socially isolated and treats others as robots without feelings and thoughts.