Fundamental Neuroscience (2 nd Edition): Section V. MOTOR SYSTEMS Chapter 32: Cerebellum James C. Houk and Enrico Mugnaini

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1 Fundamental Neuroscience (2 nd Edition): Section V. MOTOR SYSTEMS Chapter 32: Cerebellum James C. Houk and Enrico Mugnaini The cerebellum (Latin for little brain ) is a strategic part of the nervous system. It contains more neurons and circuitry than all the remainder of the brain, and it packs this into only 10% of total brain weight. It covers the dorsal surface of the brainstem and comprises the largest part of the hindbrain. The cerebellum s important function is to regulate neural signals in other parts of the brain, and it does this through loops of interaction. Currently, we know most about its regulatory actions on the populations of neurons that command movement and posture. Although the cerebellum is not necessary for the initiation of motion, movements become erratic in their size and direction when it is damaged a symptom that clinicians call dysmetria. The cerebellum is an important site of motor learning, in addition to movement execution. The size of the cerebellum in mammals parallels the evolution of the cerebral cortex, and the newest regions of the cerebellum appear to regulate higher cerebral processes for motor planning, cognition and problem solving. OVERVIEW The cerebellum has lobes and lobules. The cerebellum consists of three paired longitudinal subdivisions, the medial (or vermal) zone, the intermediate zone, and the lateral (or hemispheral) zones. The vermis (from the Latin worm), is a narrow structure that straddles the midline. On the cerebellar surface (Fig. 32.1A), the borders between the vermis and the hemispheres are demarcated by shallow indentations occupied by small veins. The medial part of the hemispheres bordering the vermis are called the intermediate zones. These zones are distinguished from the rest of the hemispheres primarily by their fiber connections. Deep transverse fissures subdivide the cerebellum rostrocaudally into three lobes, the anterior lobe, the posterior lobe, and the flocculonodular lobe (Figs. 32.1B & 32.6). The anterior and posterior lobe together form the corpus cerebelli. By contrast with the cerebral lobes, the cerebellar lobes are continuous across the midline. Shallow fissures subdivide further the cerebellar lobes into lobules. Each lobule consists of thin parallel folds called folia (leaves), which run roughly transverse to the long axis of the body. The lobules that appear in sagittal section are summarized in Box The number of folia in different lobules varies, but each folium contains a white matter core. In sagittal section, the core appears as arboreal branches departing from the roof of the fourth ventricle (Fig. 32.1C). Embedded into the deep white matter core on each side of the midline are the cerebellar nuclei (CN) -- the medial nucleus, which projects mainly to nuclei in the lower brainstem and the spinal cord, the interpositus nucleus, which targets the midbrain, and the lateral nucleus, which projects to the thalamus and on to the cerebral cortex. The interpositus nucleus consists of two subdivisions, which are usually referred to as anterior and posterior interpositus nuclei. In the human cerebellum, the Page 1

2 corresponding four nuclei (Fig. 32.1A) are classically termed fastigial, globose, emboliform, and dentate because of their morphological appearance. These nomenclatures are sometimes used interchangeably. Beneath the cerebellum is the vestibular nuclear complex, some divisions of which receive input from the cerebellar cortex and therefore bear analogy with the CN. The cerebellum is connected to the brainstem bilaterally by three cerebellar peduncles (Fig. 32.1D), the superior, middle, and inferior cerebellar peduncles (classically termed brachium conjunctivum, brachium pontis, and corpus restiforme), that carry information to and from the cerebellum. The superior cerebellar peduncle is mostly efferent and contains fibers from the CN to brainstem, red nucleus, hypothalamus, and thalamus; the middle cerebellar peduncle contains exclusively afferents from the contralateral pontine nuclei; the inferior cerebellar peduncle contains afferent fibers from the brainstem and the spinal cord, as well as cerebellar efferent fibers to the vestibular nuclei. In humans, the fibers of the superior, middle, and inferior cerebellar peduncles number approximately 0.8 million, 20 million, and 0.5 million. Interestingly, the number of fibers in the massive middle cerebellar peduncle (cerebrocerebellar afferents or pontocerebellar afferents) roughly equals that of the cerebral peduncle, which carries the input of the cerebral cortex to the brainstem and spinal cord and, via pons, back to the cerebellum. Box 32.1: NOMENCLATURE FOR CEREBELLAR LOBULUES In the classical literature, the cerebellar lobules were designated by descriptive Latin names, denoting their features in humans and other mammals. Although the Latin nomenclature is still in use, a later, practical Roman numeral system has facilitated comparative neurology. According to this system, lobules are numbered I-X beginning at the inferior anterior vermis and ending at the inferior posterior vermis. In most mammals, each lobule contains a number of folia. The anterior lobe consists of lobules I- V, the posterior lobe of lobules IV-IX, and the flocculonodular lobe of lobulus X. Lobulation is fairly consistent across individuals of the same species and extends with few exceptions across all mammalian species, despite great variation in hemispheric development (Brodal, 1969). Page 2

3 Fig Gross features of human cerebellum. (A) Dorsal view of the cerebellum and brain stem. Part of the right hemisphere has been cut out to show the cerebellar peduncles. Profiles of the four cerebellar nuclei are projected onto the cerebellar surface to indicate their position. (B) Ventral view of the cerebellum detached from the brain stem. (C) Midsagittal cut through the cerebellum and brain stem, showing the white matter entering the vermal lobules. Left side view of the lower part of the brain stem after removal of the cerebellum to highlight routes of efferent and afferent inputs. Direction and thickness of arrows indicate directions and relative numbers of fibers in the three cerebellar peduncles. Cranial nerves are indicated by Roman numerals. (A, B, and C are adapted from Nieuwenhuis et al., 1988 and Kandel, E. R., Schwartz, J.H., and Jessel, T.M., Principles of Neural Science, Norwalk, CT: Appleton & Lange, 1991, with permission. D is adapted from Brodal, A., Neurological Anatomy. New York: Oxford University Press,1981, with permission.) Page 3

4 The microcircuitry is largely homogeneous across the surface. The cerebellar cortex is a three-layered, folded sheet of gray matter, only 1 mm thick and largely homogeneous throughout the whole cerebellum. It s unique anisotropic layout can be appreciated by comparing the simplified transverse and sagittal views of the microcircuitry provided in Figs [The full 3-D complexity is elaborated later (Fig. 32.9).] The three layers of this cortex are named - beginning from the pial surface - the molecular layer, the Purkinje cell layer, and the granular layer. The cerebellar cortex contains: (1) a single type of efferent neuron, the Purkinje cells (PCs), which are inhibitory and project to the cerebellar nucleus (CN) and to the vestibular nucleus; and (2) five main classes of interneuron, three of which are inhibitory (stellate cells, basket cells, and Golgi cells) and two are excitatory (granule cells and unipolar brush cells). The cortex receives two main types of afferents (illustrated in color in Fig. 32.3) -- the mossy fibers (MFs), show blue, and the climbing fibers (CFs), shown red, are both excitatory. The molecular layer (labeled a in Fig. 2) is cell-poor; it primarily contains PC dendrites and their afferents - the parallel fibers (PFs) and the climbing fibers (but also the inhibitory stellate and basket cells that are left out of Figs 32.2 & 32.3). The Purkinje cell layer is only one-cell-thick, but it is well marked by its large PCs (> 50 µm in large mammals). The granular layer is extremely cell-rich. It receives the MFs, which form excitatory glutamatergic synapses on the granule cells, unipolar brush cells, and Golgi cells. The dendritic tree of the PC arises from the apex of the cell body and branches profusely in the molecular layer (Fig. 32.3). It is fan-shaped (compare the PC s appearance in transverse and sagittal views), like a tree trained to grow flat against a railing, and extends in a plane perpendicular to the main axis of the folium (usually the parasagittal plane). The proximal branches of the Purkinje cell dendrite appear smooth, although they are provided with scattered spines (all in contact with a single CF). By contrast, the distal dendritic branches are covered with spines (spiny branchlets), most of which establish contact with PFs running perpendicular to the Purkinje tree (along the course of the folium as illustrated by the horizontal lines in Fig. 32.2). In large mammals, each Purkinje tree bears over 200,000 synaptic spines. The PC axon, after giving off some recurrent collaterals, enters the white matter and terminates in one of the cerebellar nuclei, or in the vestibular nucleus. Although PCs display some chemical heterogeneity, they all release the inhibitory neurotransmitter GABA. The output of the cerebellar cortex, therefore, is purely inhibitory. This output is regulated by two prominent excitatory influences, the MF PF pathway and direct CF inputs. PCs also receive feedforward inhibition from basket and stellate cells and neuromodulatory inputs from noradrenergic, cholinergic and serotonergic neurons in the brainstem. The granular layer contains an enormous number (billions) of granule cells, which are the smallest neurons found in the brain (Fig. 32.2). Their spherical cell bodies form densely packed clusters, which are separated by islands of neuropil termed cerebellar glomeruli. It is often stated that cerebellar granule cells outnumber the sum of all the other neurons in the central nervous system. The granule cell emits four or five thin dendrites that terminate in claw-like protrusions into the glomeruli. Their axons ascend into the molecular layer where they bifurcate to form the PFs, which may reach a length of 6-8 Page 4

5 mm. The granule cell axon is provided with presynaptic varicosities along it s full course. Varicosities of the ascending granule cell axon terminate on Golgi cells in the granular layer and on PC spiny branchlets in the molecular layer. Most of the varicosities are along the PF and innervate the spiny branchlets of the PCs and the dendrites of the cerebellar interneurons that the PF passes along its course. Fig Transverse view of microcircuity. Schematic section of an ideal short cerebellar folium cut parallel to its course, based on the Golgi impregnation method. (a) Molecular layer with parallel fibers (PFs); (b) Purkinje cell (PC) layer; (c) granular layer; (d) white matter. Stained Purkine cell dendrites, which are oriented flat perpendicularly to the direction of the folium, appear as cypress trees. PFs, which are formed by granule cell axons after a T-division, synapse with a large number of PC dendrites which they traverse along their course. Mossy fiber terminals, which provide input to granule cells, are not shown. (Adapted from Cajal, S. R., Textura del Sistema Nervioso del Hombre y de los Vertebrados. Madrid: Imprenta y Libreria de Nicolas Moya, 1899). Page 5

6 Fig Saggital view of microcircuitry. Schematic illustration of a folium in parasaggittal section, with three PCs (black) illustrated in S. Ramon y Cajal s fashion. The PCs send their inhibitory axon to a single excitatory cerebellar nucleus (CN) neuron and are innervated by branches of a single climbing fiber (CF) (red). Two mossy fibers (MFs) (purple) branch in the granular layer forming terminals that innervate granule cells within glomeruli (not shown, but see Fig. 9). PFs, which run parallel to the direction of the folium, are represented by purple dots. The CF and one of the MFs give off collaterals, which form terminals (red and purple knobs) synapsing with the CN neuron. The CN neuron projects its axon (red arrow) to targets outside the cerebellum. Page 6

7 Neural signals are processed according to a modular scheme. From the signal processing perspective, the two main divisions of the cerebellum are cerebellar cortex and cerebellar nucleus (Fig. 32.4). The cerebellar cortex is specialized for processing extremely large amounts of information about the states of body parts, of objects around us, and of ongoing brain activities. This variety of state information is conveyed to the cerebellum by its numerous MF inputs. The state of body parts comes from our kinesthetic receptors, which signal the forces, lengths and velocities of the many muscles throughout the body and the strain and motion of the skeletal joints. The state of the world is monitored by our tactile receptors, which sense contact forces, shears and locations of nearby objects, and by our visual and auditory systems, which analyze the properties of more distant objects in the world around us. The internal state of our brain is monitored by projections from neurons in brain areas that deal with perceptions, goals, motor commands and problem solving. The large array of state information is called a MF state vector (vector is simply a concise way of referring to a set of variables). The MF state vector is diversified further by the interneuronal circuit in the granular layer so as to produce a PF state vector, which functions as an enormous, highly diverse array of potential input to a large number of PCs. Under the influence of training signals conveyed by CFs to the molecular layer (Fig. 32.4), PCs learn to detect specific patterns in their state vectors. This allows the PCs to classify the many patterns of state that occur at different times and under different contexts. This specialized neuronal architecture functions as a remarkable learning machine. The pattern classifications detected by the PC's are transmitted to CN neurons via inhibitory projections (open arrows in Fig. 32.4). As a consequence of the PC to CN projections being inhibitory, the cerebellar cortex is not well-suited for initiating nuclear cell activity directly. However, the inhibitory input from PCs is indeed potent and is highly effective in regulating the spatial and temporal patterns of CN discharge promoted by other causes. CN discharge is promoted both by the intrinsic properties of the neurons and by excitatory synaptic input, especially that coming from collaterals of select MFs. The CN serves as the final common output from the cerebellum. The CN projects to neuronal output populations that are located in different regions of the brain, and these output neurons send collaterals that loop back onto the same region of the cerebellum (part of this loop is labeled Attractor Network in Fig. 32.4). These loops effectively bind populations of neurons that are located in many other parts of the brain to the regulatory operations of the cerebellum. The signal processing scheme outlined above is organized in a modular fashion. Different zones of the CN receive their PC input from different parasaggital zones in the cerebellar cortex. Zones in the vermis and flocculus regulate the accuracy of trunk, leg, head and eye movements -- movements that are critical for the control of posture, locomotion and gaze (Chapter 30). Intermediate zones regulate the accuracy of movements that we call voluntary -- the reaching and grasping movements that we use to obtain and manipulate objects with our hands and arms (Chapter 30). The most lateral zones, in the hemispheres, regulate higher aspects of behavior. The enormously expanded hemispheres in humans plan complex movements, regulate cognition and engage in problem solving. Page 7

8 Fig Modular signal processing scheme. A variety of state information arrives to this schematized module of the cerebellum via its MFs. These signals are diversified further in the granular layer to present (in the molecular layer) enormous arrays of potential PF input to many PCs (only 3 of which are illustrated). Under the training influence of the CFs, the PCs learn to detect specific patterns when they occur in their MF PF input. The inhibitory PC CN projections then function to regulate the spatiotemporal pattern of activity in an Attractor Network formed by a group of cells in CN that connect reciprocally with an Output Population (OP) of neurons in another part of the brain. State transitions of the attractor network, eg. from relative quiescence to intense activity, can be initiated by one of the Diverse Inputs to the OP, under the regulatory influence of the inhibitory projection sent from the basal ganglia. When the attractor network is in its active state, the cerebellar cortex can shape OP activity into a useful spatiotemporal pattern of output. In a nutshell, a cerebellar module learns to use it s complex state-related input to control the dynamics of the output population that it targets. Page 8

9 Voluntary motor commands exemplify modular signal processing. To illustrate modular signal processing more specifically, we focus on the intermediate cerebellum and its regulation of voluntary movement commands (Fig. 32.5), since this is a relatively well understood example of the generic modular processing diagrammed in Figure 32.4 (Houk, 2001). In Figure 32.5, the module regulating voluntary motor commands is highlighted, both in blue (Intermediate Cerebellar Cortex) and in red (the Limb Premotor Network). The limb premotor network is an example of the Attractor Network diagramed in Figure It is comprised of an elaborate set of interconnections between CN, red nucleus and motor cortex. Interpositus neurons project to the red nucleus directly, and some project on to the motor cortex by way of the ventral thalamus. Most of the input to the motor cortex, via thalamus, derives from CN neurons in a relatively small dorsal zone of dentate. Both the red nucleus and the motor cortex transmit voluntary movement commands to motor neurons in the spinal cord and brainstem via their output fibers (Chapter 30), but they also send collaterals to precerebellar nuclei, the pons and the lateral reticular nucleus (LRN), that originate MFs which loop back to the intermediate cerebellum. These copies of motor commands (efference copy signals) inform both the cerebellar cortex and the CN about actions currently being commanded. Figure 32.5 also illustrates connectivity with other areas of the cerebral cortex and basal ganglia. The MF collaterals that loop back to intermediate nuclear cells close the recurrent pathways of the attractor network that was illustrated generically in Figure 32.4; the concept of attractor neural networks is elaborated in Box The resultant positive feedback in the limb premotor version of an attractor network (red in Fig. 32.5) appears to be an important driving force for the amplification of motor command generation. Additional neurons need to be recruited, while the activity in already recruited neurons needs to be amplified in intensity and in duration, so as to create the population of intense burst discharge that comprises a composite voluntary motor command. When positive feedback is sufficiently strong, it promotes the regenerative activity that is needed for amplification and for sustaining discharge in nuclear cells in the face of the potent inhibition sent from PCs. This regenerative activity can be initiated by any of the Diverse Inputs (Fig. 32.4) sent to motor cortex or to red nucleus, such as the inputs produced by sensory cues. This raises the question of how the initiation process is regulated. Initiation of motor commands appears to be regulated by inhibitory inputs sent from the basal ganglia (Chapter 31), as shown on the left side of Figure This influence amounts to a disinhibition in the motor cortex, which allows other cortical inputs to initiate regenerative activity in the cortical-cerebellar loop. Box 32.2: ATTRACTOR NEURAL NETWORKS Our quest to identify and understand the brain mechanisms responsible for the complex dynamics observed in neuronal assemblies has found a powerful tool in the use of neural network models. These models are based on relatively simple nonlinear units that capture only the most basic properties of individual neurons, such as synaptic integration of Page 9

10 inputs and nonlinear modulation of the firing rate. The rich dynamical behavior observed at the network level is due to a high degree of connectivity, and it is through the organization of this connectivity in specific circuits that functionally and computationally useful dynamical properties can be selected and stabilized. Complexity is thus a collective property whose source is to be found in connectivity. Two basic types of network connectivity are to be distinguished: layered and recurrent. Layered networks, based on forward maps between subsequent layers, implement arbitrarily complex input-output maps. Recurrent networks, of particular interest here, incorporate feedback loops to sustain iterative dynamical processes based on the continuous update of network state. For a recurrent network composed of N neurons, the state of the network is specified through an array of N numbers representing the firing rates of the N neurons. The state of the network at any time can be visualized as a point in an N-dimensional space, where each coordinate axis corresponds to the firing rate of a specific neuron. As the state of each neuron changes with time, the point that represents the state of the network moves in this N-dimensional space of firing rates. The trajectory described by this multidimensional point allows us to visualize the dynamical evolution of the network. Trajectories that keep on moving about and visit more and more regions of network state space, never settling anywhere, correspond to a type of dynamical behavior called ergodic. More interesting dynamical behavior, associated with persistence, arises when trajectories are attracted to special regions of state space. These regions are labelled as attractors, and the recurrent networks whose dynamics converge to them are called attractor neural networks. The attractors are of three types: fixed points, limit cycles, and strange attractors. Here we are interested in fixed point attractors. Each one of these special points controls a specific region of state space, its basin of attraction. If a trajectory starts at any point within this basin, it will go towards the corresponding fixed point, where it will settle. The basin of attraction thus defines a set of network states that will evolve dynamically until they reach the attractor state. The attractor is called a fixed point because once the network reaches this special state, it remains there. The fixed point is stable because network states that are close to it flow into it. It is as if the point that represents the state of the network were a ball frictionally gliding on a landscape of hills and valleys. The ball will move towards lower points until it reaches the bottom of the valley that is strictly downhill from its initial position. Once the ball reaches this minimum, it will stay there. The attractor fixed points thus correspond to the network states at the bottom of the valleys. Fixed point attractors provide a mechanism for the implementation of a set of motor commands in the limb premotor network (Fig. 32.5). The cerebello-thalamocorticalponto-cerebellar excitatory loop acts as a recurrent network. A computational model (Hua & Houk, 1997) has established that pathways around the loop provide a mechanism for each one of these modules to develop effective lateral connections which, in the case of the cerebellar nucleus and the thalamo-cortical circuits, take the form of a banded diagonal excitatory matrix. This type of connectivity leads to dynamical behavior controlled by the existence of two fixed points: a low activity state in which all neurons Page 10

11 fire at very low baseline rates, and a high activity state in which all neurons would fire at very high rates. In the absence of further inputs, the low activity state is an unstable fixed point and the high activity state is the stable fixed point, the attractor. But the activity of the cerebellar nucleus neurons is strongly modulated by inhibitory projections from the cerebellar Purkinje cells. This modulation introduces two important modifications in the dynamical behavior of the recurrent network. First, the low activity state is stabilized by the concerted inhibitory action of the Purkinje cells. When all of them are firing, activity in the loop is suppressed. The low activity state thus acquires a small basin of attraction. Second, and crucial to the ability of the limb premotor neuron to encode a variety of motor commands, the high activity state is not a uniform state in which all units fire at high frequency: the disinhibition of a subset of cerebellar nucleus neurons selected through the inactivation of specific Purkinje cells results in a specific pattern of activity that involves the thalamo-cortical circuits and the pons. The recurrent network sustains the high frequency firing of a subset of neurons while the others remain quiescent or fire at low frequency, baseline levels. The precise location of the high activity attractor in network state space depends on the inputs to the cerebellar nucleus provided by the Purkinje cells. Different attractor locations represent different subpopulations of neurons involved in high frequency firing; each of these patterns of network activity encodes for a specific motion as it gets exported from the motor cortex into the spinal cord and the brainstem. Motion initiation requires a transition from the low activity attractor to the high activity attractor; the mechanism for this transition is the activation of a subset of motor cortical neurons due to sensory input from other cortical areas. The activity of the cerebello-thalamocorticalponto-cerebellar loop can thus be understood as resulting from the competition between a low activity fixed point with a small basin of attraction and a high activity fixed point with a large basin of attraction. The precise network state associated with the high activity fixed point is selected by the Purkinje cells projections onto the cerebellar nucleus; different patterns of activity encode different sets of motor commands. Sara A. Solla Hua, S. E. and Houk, J. C. (1997). Cerebellar guidance of premotor network development and sensorimotor learning. Learning & Memory 4: Page 11

12 Fig Application of the modular signal processing scheme to the limb premotor network. Diverse sensory inputs, or inputs from the supplementary motor area (SMA) or the premotor cortex (PM), can activate neurons in the motor cortex (M1) or magnocellular red nucleus (RNm). The spread of this activity through the limb premotor network is regulated by inhibitory input from PCs in the intermediate cerebellar cortex, so as to produce a composite voluntary motor command appropriate for controlling the motion of the limb. Closed arrows designate predominantly excitatory projections whereas open arrows designate predominantly inhibitory projections; IP, interpositus nucleus; dd, dorsal zone of dentate nucleus; VL, ventrolateral thalamus; LRN, lateral reticular nucleus; VLo, pars oralis of VL; vgpi, ventral zone of globus pallidus pars interna; GPe, globus pallidus pars externa; ST, subthalamic nucleus. Amplification in the limb premotor attractor network insures that sufficient motor neuron activity is ultimately achieved, so as to move the limb in appropriate directions and to open the hand in preparation for closing around an object that needs to be manipulated. Of course the composite voluntary command needs also to be shaped appropriately, so that the individual commands contribute to the overall accuracy of reach and grasp. To achieve this, the individual commands need to have appropriate intensities and durations of discharge, which is the critical refinement function of well-controlled and wellcoordinated arrays of potent PC inhibitory input to the limb premotor attractor network (Miller et al. 2002). How does the cerebellar cortex learn to perform this complex regulatory function? There is a growing body of evidence, reviewed in a later section, that PCs learn under the guidance of an array of training signals that are transmitted to the cerebellar cortex by CFs. Our presently limited information about climbing fibers is generally consistent with the concept that they transmit relatively specific error information to those PCs that are capable of reducing particular movement errors (Houk et al. 1996; Simpson et al. 1996). Since each PC is innervated by only a single CF, its training information can be quite Page 12

13 specific. In contrast, the PC receives about two hundred thousand inputs conveying state information from its MF PF system. The PF synapses that were activating the PC just before the climbing fiber discharged are weakened. This learning rule utilizes a special mechanism for synaptic plasticity that is discussed in a later section. Computational models have demonstrated that the learning paradigm outlined above is capable of training PCs to control complex movements accurately, even in the presence of the substantial time delays that occur in the neural pathways that control and monitor a movement (Barto et al. 1999). Since the capacity for overcoming time delays requires an ability to predict, one can surmise that the intermediate cerebellum may be capable of functioning as a predictive controller of the spatiotemporal patterns of neural activity in the limb premotor network. Similarly, other parts of the cerebellum should be capable of predictively controlling other output populations. Predictive regulation of neuronal populations is an extremely valuable tool for the postural, gaze and locomotor functions of the medial cerebellum, for the voluntary movement functions of the intermediate cerebellum, and for the movement planning and cognitive functions of the cerebellar hemispheres. Summary The cerebellum is divided into many regional zones. Although each zone receives different inputs and projects to neuronal populations in different parts of the brain, the microcircuitry is similar across the entire cerebellum, suggesting that signal processing operations are modular. The cerebellar contribution to the regulation of voluntary motor commands was used here to introduce modular signal processing principles. ORGANIZATION OF SIGNAL PROCESSING MODULES Mossy fibers bring different kinds of state information to different modules. Mossy fibers originate from: (i) centers, termed precerebellar nuclei, that project exclusively or nearly exclusively to the cerebellum; and (ii) centers that send collaterals to the cerebellum in addition to having major projections outside the cerebellum. The major precerebellar nuclei are the basilar pontine nuclei, the lateral reticular nucleus, and the reticular tegmental pontine nucleus, and the other major centers are the vestibular nuclei, the external cuneate nucleus, and groups of cells in lamina VII of the spinal cord (Clarke s column and border cells). MFs carry diverse state information about the periphery and other brain centers. Because the MFs generally originate from secondorder sensory neurons, some processing of afferent information occurs before that information is sent to the cerebellum. MFs carrying state information from different parts of the nervous system project to different parts of the cerebellum (Fig. 32.6). The anterior and posterior portions of the vermis and the adjacent hemispheral regions are primarily innervated by fibers from the spinal cord and are termed the spinocerebellum. The lateral portions of the hemispheres and the central folia of the vermis (the visual vermal area: folium and tuber vermis) are primarily innervated by fibers from the basilar pontine nuclei and are termed the Page 13

14 pontocerebellum or cerebrocerebellum. The pontine nucleus has an elaborate representation of input from widespread areas of the cerebral cortex (Brodal & Bjaalie, 1992). The flocculonodular lobe is primarily innervated by fibers from the vestibular ganglion and from the vestibular nuclei and is termed the vestibulocerebellum. Important MF systems, arising in the reticular formation and the nucleus reticularis tegmenti pontis, provide the vestibulocerebellum with optokinetic information. The distribution of spinal, basilar pontine, and vestibular MF systems is in accord with functional subdivisions of the feline and primate cerebellum based on different behavioral abnormalities that result when each was each part is damaged or subjected to pharmacological blockade (Voogd & Glickstein, 1998). Upon reaching the cerebellum, the MFs branch extensively. They generally distribute bilaterally, with either an ipsilateral or contralateral predominance. They terminate either in multiple, symmetrically arranged, parasagittal zones or in patches. The few studies of the subject indicate that different mossy fiber systems remain segregated in the granular layer. A detailed study in the rat showed that each patch contains a representation of a small body part, but the same body part can have multiple representations (Bower et al. 1981). Neighboring patches can have representation of different body parts that are functionally related, for example, perioral region and paw. The patchy pattern is called fractured somatotopy. Because the mossy fiber granule cell-purkinje cell pathway is a widely divergent system, which may influence Purkinje cells belonging to different zones in different regions of the cerebellum more or less simultaneously, each Purkinje cell may receive information about sensory conditions, internal states, external states, and the plans of the organism. Page 14

15 Fig Organization of mossy fiber input. Schematic representation of the mossy fiber input to the anterior, posterior, and flocculonodular cerebellar lobes, that roughly define the spinocerebellar, cerebrocerebellar (pontocerebellar), and vestibulocerebellar regions. (Adapted from Dow, R.S The evolution and anatomy of the cerebellum. Biol. Rev. 17: ) Climbing fibers are organized in parasagittal zones. All CFs arise from the inferior olive, which is a complex of larger and smaller subnuclei located in the ventral medulla oblongata (Fig. 32.7). The largest of these subnuclei, the principal olive is greatly expanded in humans and is configured as a folded sheet of cells, resembling the expanded and folded lateral cerebellar nucleus with which it is connected. The olivocerebellar projection is strictly modular (Armstrong & Hawkes, 2000; Voogd & Glickstein, 1998). Subdivisions of the inferior olive project to specific subdivisions of the cerebellar and vestibular nuclei that underlie 0.5 mm wide, parasagittally oriented zones of the cerebellar cortex. The same subdivisions of the cerebellar and vestibular nuclei loop back to the subnuclei of the inferior olive from which the olivocerebellar projection originated (note the matching colors in Fig. 32.7). Moreover, the projections from the Page 15

16 cerebellar cortex to the cerebellar and vestibular nuclei and the projections from the cerebellar and vestibular nuclei to the inferior olive form closely corresponding loops. Page 16

17 Fig Organization of climbing fiber input and cerebellar output zones. Diagram of the zonal organization in the corticonuclear and olivocerebellar projections in the cat. (a) the flattened cerebellar cortex with the parasagittal zones; (b) the cerebellar and vestibular nuclei; and (c) profile of the inferior olive in the horizontal plane. The longitudinal corticonuclear and olivocerebellar projection zones are indicated with capitals (A, X, B, C1-3, D1,2). The zones, their target nuclei and the subnuclei of the inferior olive which project to these zones are indicated with the same colors. The diagram applies equally to the monkey cerebellum, with the exception of the floccular zones, the most medial one of which is lacking in the monkey. Asterisks: areas without cortex. Abbreviations: ANS, ansiform lobule; ANT, anterior lobe; D, dorsomedial cell column; Dc, caudal dentate nucleus; DC, dorsal cap; dl, dorsal leaf of principal olive; FLO, flocculus; I, intermediate cell group; IA, anterior interpositus nucleus; IP, posterior interpositus nucleus; LV, lateral vestibular nucleus; MAO, medial accessory olive; N, nodulus; PFLD, dorsal paraflocculus; PFLV, ventral paraflocculus; PMD, paramedian lobule; PO, principal nucleus of the inferior olive; PY, pyramis; SI, lobulus simplex; UV, uvula; vl, ventral leaf of principal olive; VLO, ventrolateral outgrowth; VII, lobule VII. (Courtesy of Voogd, J., 2001). Specialized zones of CF projection to the cerebellar cortex have been identified across mammals. The vermal cerebellar cortical zone comprises three parasagittal projection zones, termed A, X and B; the intermediate zone comprises parasagittal zones C 1, C 2, and C 3 ; and the hemispheral zone comprises parasaggittal zones D 1 and D 2. Several subnuclei of the inferior olive contain a detailed somatotopic map, and this somatotopy is reproduced in the corresponding climbing fiber zone as a pattern of so-called microzones. The receptive fields of PC responses to MF input appear to be specifically influenced by the receptive fields of their CFs (Ekerot & Jörntell, 2001). Contrary to the systematic divergence in the MF-PF system, the climbing fiber system is a highly focused onto microzones, and each microzone projects to a small cluster of nuclear neurons. The olivary axons cross the midline in the ventral medulla at the level of their site of origin. After entering the cerebellum, an individual climbing fiber leaves collaterals in the cerebellar nucleus that provide the reciprocal nucleo-olivary projection to the parent olivary neuron, and then ascends towards the cortex branching repeatedly in the sagittal plane to make contact with up to 10 Purkinje cells. Each Purkinje cell, however, receives input from only one climbing fiber. With more than a thousand synapses of a single fiber with an individual cell, the climbing fiber-purkinje cell pathway represents an example of a giant synapse and has powerful excitatory and metabolic effects. The inferior olive shows several unifying structural features: 1) it contains a homogeneous population of spiny projection neurons and rare interneurons; 2) within a subnucleus, all projection neurons are electrically coupled to each other by gap junctions, most of which link together dendritic spines and may serve to share postsynaptic currents; 3) all olivary projection neurons use glutamate as a neurotransmitter and corticotropin releasing factor (CRF) as a modulatory neuropeptide; 4) all olivary projection neurons receive excitatory and inhibitory inputs, mostly on the spines and Page 17

18 stems of peripheral dendrites; 5) all olivary subnuclei receive a strong GABAergic innervation. CRF is generally expressed by neurons involved in stress signaling throughout the brain. Outflow engages motor, autonomic and cognitive parts of the brain. The cerebellar outflow ultimately reaches all motor nuclei (Brodal, 1998), structures within the autonomic nervous system (Dietrichs et al. 1994), and many areas of the cerebral cortex (Middleton & Strick, 1998), with topically organized connections. The outflow from neurons occupying discrete subdivisions of the cerebellar nuclei targets specific neuronal populations in the thalamus, hypothalamus, red nucleus, tectum, pons, medulla, and cervical spinal cord. The outflow also loops back to the cerebellum via several nuclei, primarily the pontine tegmental reticular nucleus, the basilar pontine nuclei, the lateral reticular nucleus, and the inferior olive. Individual excitatory neurons residing in each cerebellar nucleus have axons that form discrete patches of synaptic terminals in a primary target nucleus, and the axons also often send collaterals to other target nuclei. Collaterals of the individual cerebellar nuclear neurons are hypothesized to terminate on functionally congruent groups of neurons in the target nuclei. The functional congruency would be achieved by stabilization of effectual connections during maturation of the sensory-motor circuits. The small inhibitory neurons of the cerebellar nuclei have axons projecting in a similarly discrete manner, but they do not collateralize; they project to specific regions of the inferior olive, the source of all CF input to PCs. It is generally assumed, therefore, that cerebellar connections are organized in a complex, but detailed topical order. The zonal organization of the cortical maps is well correlated with physiological findings. In the vestibulocerebellum different zones exert a plane-specific control of the external muscles of the eye. A similar specification may be present in the zones of the corpus cerebelli, with the A zone regulating the inhibitory vestibulospinal tracts, the B zone regulating the excitatory lateral vestibulospinal tract and the intermediate C 1 C 2 and C 3 zones regulating the rubrospinal system. A portion of the A zone in the central vermis (visual vermis: folium and tuber) is able to adapt the amplitude of saccades. The functions of the D 1 and D 2 and other as yet undefined hemispheral zones are not as well known. The D 1 and D 2 zones probably regulate movements of individual digits, and other regions may regulate visual smooth-pursuit tracking, eye-hand coordination and higher aspects of motor planning and cognitive function. For many years, the cerebellum was thought to be involved only in the generation of movement. This belief was based on the fact that cerebellar projections had been traced only to motor areas and cerebellar lesions in humans seemed to cause only motor deficits. Initial suggestions that the cerebellum participates in cognition arose from anatomic connections that were postulated to exist due to the parallel expansion of the frontal lobe, lateral cerebellum, and dentate nucleus. Then retrograde transneuronal transport of special virus strains in monkeys demonstrated many specifics of these connections (Middleton & Strick, 1998). These transneuronal studies have suggested the following general principles: 1) cerebral cortical areas that project to the cerebellum (motor, Page 18

19 premotor, and lateral intraparietal areas, and some of the non-motor areas of the prefrontal cortex are the target of cerebellar output; 2) cerebral cortical areas that do not project to the cerebellum are themselves not the target of cerebellar output; and 3) the cerebellar output channels to different cortical areas are topically distinct zones of the dentate nucleus (Fig. 32.8). Fig Output channels to four areas of cerebral cortex. Anatomical arrangement of separate output channels in the monkey dentate (DN) and interpositus (IP) nuclei, after virus injections into different cortical areas (M1 arm, PMv arm, area 46, area 9l). Solid dots indicate neurons that were labeled by virus retrogradely transported from the cortex in three adjacent sections at the antero-posterior location indicated below each nuclear outline (P7.5, P8.0, P8.5, P9.5). (D, dorsal; M, medial). (Reproduced from Middleton and Strick, 1998, with permission) Summary The organization of the mossy and climbing fiber input to the cerebellum is appropriate for regulating neuronal populations in other parts of the brain that control movement, autonomic function, and cognitive operations. THE NEURONS AND THEIR SIGNALS The purpose of this section is to relate the cellular properties of cerebellar neurons to their signal processing operations. The diverse constellation of neurons in the cerebellar cortex is summarized in Figure 32.9, which is a perspective drawing of a folium that integrates the transverse and saggital views of the cerebellar cortex given earlier (Fig & 32.3). The 3-D perspective highlights the orthogonal relationship between the flattened PC dendritic trees and the sheet of parallel fibers providing convergent input. The drawing also illustrates the arrangement of the three types of inhibitory interneuron (Golgi, stellate and basket cells) and other factors within this matrix. Page 19

20 Fig Cells and circuitry of the cerebellar cortex. This 3-D representation integrates the simplified transverse and sagittal views of a cerebellar folium shown earlier in Figs and (Adapted from Heimer, L., The Human Brain and Spinal Cord, Springer-Verlag, 1995). Page 20

21 Purkinje cells shape the spatiotemporal patterns of cerebellar outflow. The most remarkable neurons of the cerebellum are the Purkinje cells. The innervation of a PC by an individual climbing fiber is quite exceptional, virtually climbing all over the proximal dendrites and making multiple excitatory synapses (Fig ). Except for the fact that CFs fire at very low rates, this would dominate the discharge of the PC. Instead, PCs have two characteristic types of discharge that can be observed with either extracellular or intracellular recording electrodes, namely the repetitive simple spikes that are mediated by PF input and the occasional complex spikes that are mediated by CF input (Thach, 1998). Recorded near the cell body under quite stable conditions, complex spikes appear as high frequency wavelets (Fig C2), but they are also recorded as a large spike followed by a wave that lasts for a few msec. Fig Climbing Fiber-to-Purkinje Cell Pathway and Synapses. (A) Climbing Fiber-to-Purkinje Cell Pathway. Varicose branches of a single climbing fiber (labeled blue with a lectin) cling to the proximal dendritic domain of an individual Purkinje cell arbor (labeled brown with antiserum to calbindin). (Courtesy of Rossi, F., Borsello, T., Vaudano, E., and Strata, P. Neuroscience 53: , 1993). (B) Climbing fiber-purkinje cell synapses. The electron micrograph shows a climbing fiber varicosity (CF) in synaptic contact with spines (arrows) of the proximal dendritic domain of the Purkine cell arbor (Pd). (Adapted from Larsell O. and Jansen, J. Eds., The Cerebellum. Minneapolis: Minnesota Universtity Press, 1972). Page 21

22 The vast majority of the action potentials generated by PCs are the large negativepositive potentials shown in Figure 32.11C1, called simple spikes. Simple spikes are produced by PF input to the PC. They repeat, with occasional pauses, at relatively high spontaneous rates. The simple spikes recorded from the intermediate cerebellum in the awake animal show either bursts or pauses in association with movement, and the intensities of the responses correlate with the velocity and direction of movement (Ebner, 1998). To set the stage for further discussion of the cellular neurobiology of the cerebellum, we will present a simplified overview of PC and CN signals in the intermediate cerebellum, and how they relate to the control of an arm movement. Fig Spike wave-shapes recorded in the awake monkey. (A) Examples of fast action potentials attributed to mossy fibers. A1: biphasic potential with a negative afterwave (glomerular potential). A2: predominantly positive potential. A3: biphasic potential without a negative afterwave. A4: triphasic potential. (B) Example of a slow negative-positive potential attributed to a Golgi cell. (C) Simple (C1) and complex (C2) spikes recorded from a Purkinje cell. (Adapted from Van Kan, Gibson and Houk, J. Neurophysiology 69: 74-94, 1993). Figure shows schematically four microscopic modules that regulate the activity of four motor cortical neurons. Microscopic modules are loops between small clusters of cortical and CN neurons, a whole array of which comprise the macroscopic module illustrated in Figure Each of the numbered neurons is assumed to command movement in one of 4 directions motor cortical neuron 1 commands upward movement, 2 rightward, 3 downward and 4 leftward. Each of the output neurons is reciprocally Page 22 22

23 connected (via thalamic and pontine neurons) to a CN neuron that is regulated by inhibitory input from a PC (actually a parasaggital row of about 300 PCs). Adjacent to each module are two waveforms, meant to represent the discharge over time of an associated Purkinje cell (upper trace) and the nuclear neuron (lower trace) to which it projects. The lower traces also represent the motor cortical neurons linked to the CNs, since they will be caused to burst simultaneously by the module s reciprocal corticalcerebellar loop. Fig Signals and circuits regulating the direction of an arm movement. The diagram illustrates four motor cortical cells, labeled 1-4, that move the arm upward (1), rightward (2), downward (3) or leftward (4). Each is reciprocally connected with a different microzone of the cerebellum, so as to form a microscopic module. The traces next to each module illustrate how pauses and bursts in Purkinje cell discharge would regulate the nuclear (and motor cortical) cell s activity. Note the high spontaneous discharge of the Purkinje cells (dashed lines reference no discharge). Page 23 23

24 Divergence of fibers within the limb premotor network (arrows between modules) allows activation to spread laterally among adjacent modules. A sensory stimulus (flash of light, or a tone) might produce just a tiny burst of activity in neuron 1. This small activation, while insufficient to drive movement, can initiate an amplification process. Since that loop s PC inhibition is turned off, activity can reverberate around this loop. Positive feedback would enhance the intensity and extend the duration of this reverberating activity, producing a substantial command signal for transmission to an agonist muscle for upward movement. Activity would also tend to spread to the modules controlling neurons 2 and 4, since their PCs are only producing moderate inhibition. This would command a co-contraction of right and left muscles, which would serve to stabilize the limb. In contrast, activity would not spread to the module controlling neuron 3, since its PC is bursting and is producing strong inhibition. Therefore muscles that tend to move the limb downward would be relaxed. In a more realistic model, there would be many more such microscopic modules, each controlling movements in intermediate directions that are distributed throughout the workspace. This example assumes that the PCs have been programmed to discharge with an appropriate time course. The upward movement command is a strong burst because its PC paused completely for the duration of the movement command. There is no downward movement command because its PC fired a strong burst during the period when positive feedback was present in other loops of the limb premotor attractor network. The rightward and leftward movement commands are intermediate in intensity, because their PCs do not stray much from their spontaneous level of activity. While these assumed patterns of PC activity are compatible with current neurophysiological data, the field is still lacking definitive experiments showing that the correct PCs in the cerebellar cortex generate the most appropriate patterns. The motor learning mechanisms discussed at several points in this chapter should be capable of insuring this, but the experimental evidence remains incomplete. There is also increasing evidence that the cerebellum, motor cortex and red nucleus are organized not in terms of preferred directions of hand movement, but rather in terms of functionally useful groups of muscles (Miller et al. 2002). It is easy to see how such a system of preferred muscle synergies could be controlled by interconnected groups of cortical-cerebellar processing modules such as the ones discussed above. Arrays of modules controlling grasp muscles might be adjacent to, and partially interconnected with, modules controlling limb extension muscles. Postural responses could be coordinated by similar interconnections with modules controlling muscles of the neck, trunk and legs. Granule, Golgi and brush cells process the excitatory mossy fiber input. The MF signals that convey state information to the cerebellum excite granule cells within giant synaptic structures called glomeruli. The expanded drawing of a glomerulus in Figure 32.9 shows that its core ingredient is a large expansion of the mossy fiber, which occurs along its branches or at the terminals. The glomerulus is packed with Page 24 24

25 synaptic vesicles, and with mitochondria that fuel the manufacturing of the vesicles. The dendrites of nearby granule cells send claw-like protrusions into the glomerulus where they form multiple small synaptic junctions (Fig ). Because of the large size and glial surround of the glomerulus, extracellular electrodes are able to record the signals transmitted by MFs, in one of several ways illustrated in Figure 32.11A. The full fledged glomerular potential (A1) has a biphasic presynaptic component, produced when the action potential invades the glomerulus, followed by a slower negative wave, produced when excitatory postsynaptic current flows through the numerous excitatory synaptic junctions. When the negative wave is missing, the presynaptic component takes on one of the three other configurations shown in Figure 32.11A2, A3 & A4. MFs in the intermediate cerebellum discharge at frequencies that are graded over a broad range, and different fibers signal a variety of sensory and efference copy information. Fig Mossy fiber-to-granule cell synapses in a cerebellar glomerulus. The electron micrograph shows the central mossy fiber terminal (MF) forming asymmetric synaptic junctions (circled) with surrounding granule cell dendrites. The granule cell dendrites form symmetric synaptic junctions (boxed) with terminals of the Golgi cell axon (Ga), which are labeled by immunogold particles (small solid dots) using Page 25 25

26 antiserum to GABA. Arrow indicates astrocytic lamellar processes forming the peripheral glial sheath. Asterisk marks the shaft of a granule cell dendrite entering the glomerulus. (Adapted from Heimer, L., The Human Brain and Spinal Cord, Springer-Verlag, 1995). While MF activation of a glomerulus can be recorded in awake behaving animals with extracellular microelectrodes, our knowledge of synaptic integration by the granule cell depends mostly on intracellular recordings from brain slices (Hansel et al. 2001), due to the fact that the small extracellular spikes produced by their tiny axons are obscured by electrical noise. MF input activates both AMPA and NMDA receptors and, due to the latter, exhibits excellent temporal summation. Excitatory transmission is moderated by the GABAergic inhibition sent to the glomerulus by Golgi cells. The latter neurons produce slower and larger extracellular action potentials than MFs (Fig B). Their dendrites branch broadly, mainly in the molecular layer, and they discharge at relatively steady rates that reflect the overall level of PF activity in the overlying molecular layer. The computational ideas originated by Marr and Albus in the 70 s appear to be reasonably valid (Houk et al. 1996). Golgi-cell inhibition appears to function like an automatic gain control, normalizing the amount of PF input, so as not to overwhelm PCs, but at the same time allowing the PF state vector to express many diverse patterns which can then be selectively detected by individual PCs. Because the granule cells receive input from about 4 different MFs, the MF-granule cell system should create an expanded representation of state that is kept sparse by Golgi inhibition. Unipolar brush cells (Fig. 32.9) are found in the granular layer of the vermal and intermediate zones and the vestibulocerebellum (Nunzi et al. 2001). They are strongly excited by individual MF inputs, or by other brush cells, and they strongly excite nearby granule cells. This circuit serves to amplify the intensity and duration of MF input. This is probably important for the enhancement and short-term storage of state information about the orientation of the organism that is characteristic of the vestibulocerebellum. Climbing fibers transmit training information via the inferior olive. The CF pathway originates in the inferior olive of the brainstem. These cells display electrical activity analogous to that present in the heart -- action potentials with long plateaus followed by long refractory periods -- causing CFs to fire at very low rates (irregular at about 1/sec). Many olivary neurons detect sensory events, but are inhibited by GABAergic inputs from the CN. This combined excitatory and inhibitory input helps to signal the occurrences of errors. When the same sensory event occurs in a context that does not signify error, the small CN neurons can inhibit their responses. Olivary cells are electrotonically coupled to each other and show a slight tendency to oscillate at approximately 10 Hz (Welsh et al. 1995). The diversity of the receptive fields of olivary neurons insures a relatively private training signal that is then transmitted to parasaggital rows of about 10 PCs. The best current examples of error detection are the CFs that project to PCs in the flocculonodular lobe. They signal the slip of visual information across the retina, which is indicative of an improperly regulated eye movement command (Simpson et al. 1996). Page 26 26

27 Non-laminar afferents bring neuromodulatory influences. In addition to MFs and CFs, the cerebellum receives several types of afferents that have non-laminar distributions of their terminals. These non-laminar afferents orginate from neurons in the locus ceruleus, the raphe nuclei, or from widely distributed choline acetyltransferase(chat)-positive brainstem neurons, and from the hypothalamus. These afferents innervate the cerebellar nuclei and all layers of the cerebellar cortex, with some preference for the molecular layer. Afferent fibers from the locus ceruleus arrive via the superior cerebellar peduncle and release norepinephrine in the cerebellar cortex, fibers from the raphe nuclei release serotonin (5HT), fibers from ChAT-positive neurons release acetylcholine (ACh), and fibers from the hypothalamus are in part histaminergic. The non-laminar fiber systems modulate the excitability of PCs and other cerebellar neurons. Non-laminar afferents and their synapses are best identified with the help of cytochemical markers and tract tracing molecules. These afferents have active zones and postsynaptic densities, although it is likely that they may also release their transmitters at nonspecialized regions of their terminal branches. Molecular layer interneurons dampen Purkinje cell excitability. The stellate and basket cells in the molecular layer inhibit PCs via GABAergic synapses. Stellate cells, which are scattered throughout the molecular layer, provide a moderating influence that dampens large fluctuations of excitatory PF input. The dendrites of basket cells are longitudinally oriented and their axonal trees innervate parasaggital rows of PCs, forming basket-like terminations that surround the PC bodies and form paint brush extensions around their initial axon segments. Since PCs have high spontaneous discharge rates, the basket cell s specializations seem appropriate for initiating the pauses that punctuate their spontaneous activity. The extracellular potentials of basket cells have not yet been definitively identified in awake animals, but the bi-phasic potentials recorded just above the PC layer are appropriate candidates. These units show bursts and pauses analogous to those recorded from PCs. Basket and stellate cells have dendrites carrying a low density of spines and receive most of the excitatory synapses on their cell bodies and dendritic shafts from both PFs and collaterals of CFs. These contacts are intermixed with inhibitory synapses from other basket and stellate cells. Basket cells are also inhibited by recurrent collaterals of PC axons. Purkinje cells have special computational features. The ionic currents that influence PC discharge are numerous. However, the calcium P- currents underlying plateau potentials in PC dendrites (Llinas & Sugimori, 1980) are especially important from two functional perspectives: (1) promoted by excitatory input from PFs, P-current mediated plateau potentials are responsible for the relatively high spontaneous firing rates ( 50 imp/s) of PCs and (2) the influx of calcium resulting from these currents is one of the factors that contributes to the motor learning mediated by the synaptic plasticity of PF PC synapses, as will be elaborated in the following section. PC dendrites are forced, by the balance between their excitatory and inhibitory synaptic input, to make transitions in their internal state transitions back and forth between a hyperpolarized state of low excitability and a depolarized plateau state of high excitability (Houk et al. 1996). Inhibitory synaptic input from molecular layer Page 27 27

28 interneurons can initiate transitions from the depolarized to the hyperpolarized state. Such transitions are important since they generate the pauses in PC discharge that remove the spontaneous inhibition of CN neurons that exists spontaneously in the cerebellum. This permits the CNs that they target to fire at very high frequencies ( imp/s). This succession of events accounts for the buildup of intense activity in the reciprocal loop of the module 1 illustrated in Figure The high CN firing rate amplifies the agonist movement command that was initiated in the motor cortex by, for example, a sensory cue. A little later, after the movement is underway, we speculate that module 1 s PC detects the occurrence of a critical pattern in its PF state vector, signifying that the moment has arrived to terminate the movement command. Then, after the conduction delays in the neuromuscular system, the movement can come to a graceful termination, hopefully at the desired endpoint. If the corresponding PF PC synapses have learned to recognize this truly critical state, the PC dendrite will receive appropriately strong excitatory input at the critical moment, thus promoting the transition back to the plateau state of dendritic depolarization, which causes the PC to resume its moderately high spontaneous firing rate. The resumption of potent inhibitory input to the CN neuron turns off its intense firing, thus terminating the module s movement command. A different succession of events may account for the suppression of motor commands to antagonist motor neurons. PCs that regulate module 3 in Figure are shown to substantially increase their discharge at about the same time that the agonist-connected PC in module 1 pauses. The antagonist-connected PC is assumed to have detected the occurrence of a pattern in its state vector calling for the initiation of a movement opposite to the one it promotes if it pauses. Instead, it bursts, which helps to suppress the generation of an antagonist command. Presumably some of its dendrites were sitting in their hyperpolarized states, and some of the corresponding PF PC synapses detected the initiation of movement commands in the movement s agonist muscles. This promotes transitions to depolarized states, which promotes intense firing of that PC. The intense firing inhibits the CN to which the PC projects, preventing it from amplifying discharge in the output neuron(s) that it targets. This helps to suppress movement commands to the antagonist motor neurons. Modules 2 and 4 in Figure are regulated in a less intense fashion. Their PCs exhibit a modest increase in firing at movement onset, which slightly increases the inhibition sent to their CNs. This tends to dampen the buildup of positive feedback in their reciprocal loops, while not entirely inhibiting it. This is because the overall activity of the limb premotor network is strongly enhanced, which brings an excitatory influence to those loops. By tracing through the logic of this simplified example, one can begin to appreciate the critical role played by the large array of Purkinje cells in the intermediate cerebellar cortex. The spatiotemporal pattern in this PC array plays a critical role in regulating the buildup of positive feedback in the limb premotor network, shaping it into a composite movement command that moves the limb toward an object that the organism wants to Page 28 28

29 manipulate. Although all of this PC array s activity is important, a particularly critical feature is the detection of PF states indicating that the time has come to terminate the composite movement command. If this didn t happen, the resultant movement would be hypermetric. In fact, the immediate effect of lesions confined to the cerebellar cortex is hypermetria. However, over the course of functional recovery, other circuitry in the brain (for example, intracortical circuitry and/or the loop through the basal ganglia shown in Figure 32.5) evidently adapts in a manner that suppresses the buildup of positive feedback in the limb premotor network. Long-term depression mediates motor learning. The strategic role of PF PC plasticity in motor learning has been mentioned several times earlier in this chapter. Long-term depression (LTD) is the name given to the synaptic plasticity of PF PC synapses (Ito, 1984; Fig ). While other types of plasticity have also been found in the cerebellum (Hansel et al. 2001), LTD is particularly important. Cerebellar LTD appears to differ from the long-term potentiation (LTP) present in cortical neurons (Chapter 50) in several significant respects: (i) it desensitizes postsynaptic receptors instead of sensitizing them (depression instead of potentiation), (ii) it uses a different set of second messengers, (iii) it appears to be a 3-factor learning rule instead of the predominantly 2-factor Hebbian rule associated with LTP at most other sites in the CNS (Houk & Alford, 1996). The two factors in the Hebbian rule are activity of a particular synapse and activity of the postsynaptic neuron. The three factors associated with cerebellar LTD are discussed below, and Figure summarizes some of the salient steps in this synaptic modification process. Fig A dendritic spine of a Purkinje cell. Electron micrograph of a dendritic spine arising from a spiny branchlet of the Purkinje cell arbor. The spine forms an asymmetric synapse with a parallel fiber varicosity. Actin forms a lattice in the spine head and parallel microfilaments in the spine neck. Dense spots on the membrane of the endoplasmic reticulum of the spine represent the large Page 29 29

30 cytoplasmic domains of InsP 3 receptors. These function as Ca 2+ channels and are extremely abundant in Purkinje cells. Side branches of the astrocytic Bergmann glia fibers (asterisks) surround the synaptic profiles, with the exception of the synaptic apposition. Fig Multi-level principles appropriate for driving motor learning in the cerebellum. The red arrows mark three important factors in the learning rule. At the level of an individual spine, the glutamate released by a PF causes both a depolarizing current, mediated by AMPA receptors, and a metabotropic activation, mediated by mglur1 receptors. The latter is a spine-specific factor. The depolarizing currents produced by several spines along the dendrite may summate sufficiently to produce a plateau potential. This factor signifies the PC dendrite actively participated in a movement. Metabotropic activation of individual spines combines with dendritic depolarization to activate PKC, which then phosphorylates the AMPA receptor to produce a trace of prior coincident synaptic and dendritic activity. Meanwhile, many dendrites and many PCs regulate the composite movement command that, after some time delay, produces a movement. If an error is then detected, the CF fires and that can activate PKG to consolidate any trace of LTD that is present in the spine. Factor 1. When a PF releases glutamate at a particular synaptic spine, like the one illustrated in Figure & 32.15, it activates two types of glutamatergic receptor -- AMPA and mglur1. Activation of the spine s AMPA receptors opens channels that permit depolarizing currents to flow into the spine and out into the dendrite, influencing the postsynaptic depolarization of that dendrite, and the activity of the entire PC. In Page 30 30

31 combination with the currents produced by many other activated spines, this synaptic activation contributes to the internal state of the dendrite and may initiate a plateau potential. If so, the depolarization of the dendrite spreads back into the spine (factor 1, shown by a red arrow in Fig ) to augment spine depolarization. The activity of all of the PC s dendrites combines to control PC discharge. Factor 2. In contrast, activation of the spine s mglur1 receptors initiates chemical changes that are confined to that particular synaptic spine, as summarized in Figure The localization of factor 2 to one spine (shown by another red arrow in Fig ) insures that LTD will be synapse specific (Wang et al. 2000). Only the synaptic weight of this particular PF PC synapse is made eligible for modification by the learning rule. If the synapse is excited at nearly the same time that the dendrite is in its plateau state, factors 1 and 2 synergize. Through second messenger pathways, there is a local increase in the level of calcium in the spine. Then, through relatively slow second messenger pathways, this phosphorylates the spine s AMPA receptors causing them to become desensitized. To summarize this from a computational standpoint, there is a nearly immediate activation of the dendrite and the PC, and a slow phosphorylation of the spine s AMPA receptors. The slowness of the latter process provides a biological basis for a slow rise and decay of an eligibility trace signifying that this synapse is eligible for LTD (Barto et al. 1999). It became eligible because it was just active, and because the dendrite participated (though slightly) in helping to terminate the movement command that this PC helps to regulate. Factor 3. Meanwhile, a composite motor command is being formulated by the regulatory actions of the array of PCs that shape activity in thousands of the microscopic modules analogous to the ones exemplified in Figure The thousands of elemental movement commands, transmitted by thousands of neurons comprising the output population, function in grand combination to collectively control the actual movement that is eventually made. Only then can this action be evaluated by its sensory consequences, so as to provide a training signal transmitted by CFs (third red arrow in Fig ). The corresponding CFs are presumed to detect cases in which there are errors in the endpoint of the movement. Thus, after a time delay of up to a few hundred milliseconds, a particular CF either fires or remains silent. Its firing signifies that a faulty action is being produced, and an adjustment in synaptic efficacy is needed to make the error less likely in the future. The precise mechanism is still being investigated, but there is evidence that CF firing leads to an activation of protein kinase G (PKG in Fig ). Activated PKG prevents the dephosphorylation of recently phosphorylated AMPA receptors. Thus, if the eligibility trace mentioned in the previous paragraph has not yet decayed, this CF discharge could consolidate the desensitization of the AMPA receptors, resulting in a sustained decrement in synaptic weight, which is the definition of LTD. All three factors need to be satisfied to produce a computationally appropriate learning rule (Houk & Alford, 1996). Factor 1 (a postsynaptic factor) signifies that the dendrite and PC actively participated in the impending action. Factor 2 (a synapse-specific factor) signifies that this particular PF PC synapse helped the PC to participate in the action. Factor 3 (a training signal) signifies that the action in which the synapse and PC Page 31 31

32 participated resulted, after a substantial time delay, in an error. The slow eligibility trace helps to compensate for the time delay. We have only considered processes that depress synaptic efficacy. Learning rules need to work in both directions to train a network effectively. There is evidence for a reversal of LTD when CFs fail to detect errors, but the mechanisms have yet to receive the attention that they deserve. Another important topic is the morphological consolidation of PF PC synaptic plasticity that occurs with long-term training (Kleim et al. 1998). Cerebellar nuclear cells are of two types. The cells of the cerebellar nuclei consist of large excitatory neurons (glutamatergic) and small inhibitory neurons (GABAergic and/or glycinergic). The large nuclear neurons are induced to fire at high frequencies, apparently when activated by MF collaterals, and their firing frequency is reduced when PCs burst intensely (Miller et al. 2002). The nuclear cells also exhibit some spontaneous firing under isolated conditions, which results from a tonic cation current mediated mainly by sodium influx (Raman 2000). Less is known about the electrophysiology of the small nuclear cells. However, their discharge should inhibit the olivary neurons to which they project, and this mechanism appears to cancel out sensory responses during certain phases of behavior, which probable serves to refine the training signals transmitted by CFs. Classical conditioning depends on the cerebellum. One of the first forms of learning to be analyzed neurobiologically is the classically conditioned reflex (Thompson, 1986). It was discovered that the intermediate cerebellum is crucial for expression of the conditioned eyeblink reflex (Chapter 51). To comprehend how these findings relate to the neurophysiology of the cerebellum, it is helpful to relate the modular concept of cerebellar signal processing (Fig. 32.4) to the neural circuitry that is believed to mediate the conditioned eyeblink movement (Houk et al. 1996; Raymond et al. 1996). Conditioned eyeblinks appear to involve the intermediate cerebellum, parts of it that generate the motor commands that are sent to brainstem networks that control eyelid muscles. When the associated circuitry is labeled with an activity-dependent marker, one can visualize two separate networks (Keifer et al. 1995). One links the intermediate cerebellum with the red nucleus -- it is required for well coordinated conditioned reflex responses but not for the basic unconditioned reflex. The latter is controlled by a brainstem network that is required for both conditioned and unconditioned responses. Plasticity in the cerebellum is probably only responsible for adjusting the metrics of the motor responses (Welsh & Harvey, 1989), and not for making the associative link between the conditioned and unconditioned stimulus. The conditioned stimulus functions as a sensory cue (one of the Diverse Inputs in Figure 32.4) for initiating a transition to the active state of the rubrocerebellar attractor network (Fig. 32.5), so the acquisition of a new cue is more likely to be regulated by pathways that pass through the basal ganglia. Page 32 32

33 Summary The neurons of the cerebellum have diverse anatomic and physiologic specializations that appear to facilitate: (1) the creation of input diversity in arrays of parallel fibers, (2) the detection by Purkinje cells of salient patterns that are present in these arrays, and (3) the use of these detection outcomes to regulate the temporal pattern of activity in the cerebellar nuclear neurons to which they project. Purkinje cells learn to do this through a unique form of synaptic plasticity that couples efficacy to regulatory performance, as monitored by climbing fibers. ACTIVATION AND INACTIVATION STUDIES We can also learn about the functions of the cerebellum by studying what happens when parts of it are activated or inactivated. Activation of the cerebellum results naturally when we use our brain networks in the course of appropriately complex behaviors, and particular regions of the cerebellum can be artificially activated by electrical stimulation. Inactivation of the cerebellum can be produced with lesions, which cause permanent changes, or with reversible inactivations produced by microinjections of pharmacological agents. This section summarizes what we have learned about cerebellar function from activation and inactivation studies. Activation studies reveal diverse functions. For many years, the cerebellum was thought to be involved only in the execution of movement, but this appears to be wrong. Human brain imaging studies indicate that the cerebellum also participates the planning of complex movements and in a variety of cognitive and problem solving functions (Frackowiak et al. 1997). For example, the cerebellum is activated when subjects make sequential movements, and even when they imagine or passively observe movement without making movements themselves. Furthermore, the lateral cerebellum is activated in a language task, in which subjects are asked to generate appropriate verbs for visually presented nouns. The observed activity is over and above the activation that occurs when nouns are simply read, indicating that the cerebellum somehow contributes to the generation of appropriate verbs. Interestingly, once a verb generation task has been rehearsed, cerebellar activation diminishes (van Mier et al. 1998). As an additional example, the ventral dentate is activated bilaterally when subjects work to solve a difficult pegboard puzzle, and this activation is three to four times greater in magnitude than during simple peg movements (Kim et al. 1994). Overall, these studies indicate that the newer parts of the cerebellum, the hemispheres and the dentate nucleus, are activated in ways well beyond those required for the execution of movements. Behavioral observations of humans with cerebellar damage supports the conclusion that the cerebellum participates in non-motor aspects of cognition. In one case study, a cerebellar patient showed impaired performance on the verb generation task described earlier; he was unable to detect errors in his performance of the task and did not exhibit normal practice-related learning. Interestingly, this patient performed normally on standard intelligence and memory tests. In another study, cerebellar patients had deficits Page 33 33

34 in both the production and the perception of a timing task. Lateral cerebellar regions contribute to the perception of time intervals, while medial cerebellar regions help to mediate the timing of implemented responses. An older method that was used to activate the cerebellum is electrical stimulation. In the absence of anesthesia, either contractions or relaxations of muscles, and resultant movements, can be elicited by electrical stimulation. The movements affected are diverse, and they depend, as expected, on the zone of the cerebellum that is stimulated. Sometimes the movements elicited are relatively complex sequences, consistent with the complex motor planning functions mentioned earlier. Humans with cerebellar damage exhibit motor deficits. In the early 1900s, Gordon Holmes described the movement deficits associated with discrete cerebellar lesions in humans that were caused by gunshot wounds. His descriptions provide the basis for classifying clinical cerebellar syndromes according to seven basic deficits. 1. Ataxia is a condition that involves lack of coordination between movements of body parts. The term is often used in reference to gait or movement of a specific body part, as in ataxic arm movements. 2. Dysmetria is an inability to make a movement of the appropriate distance or direction. Hypometria is undershooting a target, and hypermetria is overshooting a target. Patients with cerebellar damage tend to make hypermetric movements when they move rapidly and hypometric movements when they move more slowly and wish to be accurate. 3. Dysdiadochokinesia is an inability to make rapid, alternating movements of a limb. It appears to reflect abnormal agonist-antagonist control. 4. Asynergia is an inability to combine the movements of individual limb segments into a coordinated, multisegmental movement. 5. Hypotonia is an abnormally decreased muscle tone. It is manifest as a decreased resistance to passive movement, so that a limb swings freely upon external perturbation. Often, hypotonia is not present in cerebellar patients or is present only during the acute phase of cerebellar disease. 6. Nystagmus is an involuntary and rhythmic eye movement that usually consists of a slow drift and a fast resetting phase. After unilateral cerebellar lesion, the fast phase of nystagmus is toward the side of the lesion. 7. Action tremor, or intention tremor, is an involuntary oscillation that occurs during limb movement and disappears when the limb is at rest. Cerebellar action tremor is generally at a low frequency (3-5 Hz). Titubation is a tremor of the entire trunk during stance and gait. Page 34 34

35 Cerebellar damage also causes deficits in motor learning. Studies of prism adaptation have shown that some patients with cerebellar damage are unable to adapt their hand-eye coordination to the visual displacement produced by the prism (Fig ). Most of these symptoms can be explained as a basic problem of learning to control the direction and amplitude of a movement (dysmetria), making it necessary use multiple corrective submovements (action tremor). Fig Prism adaptation test. (A) Eye-hand positions after adaptation to base-right prisms in a control subject. The optic path is bent to the subject's right, giving a larger view of right side of her face. Her gaze is shifted left along the bent light path to foveate the target in front of her. Her hand position is ready for a throw at the target in front of her. (B) Horizontal locations of throw hits displayed sequentially by trial number. Deviations to the left are negative values; deviations to the right, positive. While the subject is wearing the prisms (gaze shifted to the left), the first hit is displaced 60 cm left of center. Thereafter, hits tend toward 0. After the prisms are removed, the first hit is 50 cm right of center. Thereafter, hits tend toward 0. Data during and after prism use have been fitted with exponential curves. The decay constant is a measure of the rate of adaptation. The standard deviation of the last Page 35 35

36 eight preprism throws is a measure of performance. Gaze and throw directions are schematized with arrows. Inferred gaze (eye and head) direction assumes the subject is foveating the target. Roman numerals beneath the arrows indicate times during the prism adaptation experiment (see B). (C) Failure of adaptation in a patient with bilateral infarctions in the territory of the posterior inferior cerebellar artery. (Adapted from Martin, T. A., Keating, J. G., Goodkin, H. P., Bastian, A. J. and Thach, W. T. (1996). Throwing while looking through prisms. I. Focal olivocerebellar lesions impair adaptation. Brain 119: ) Reproduced from Bastian, Mugnaini and Thach, in Zigmond M. J. et al. Eds., Fundamental Neuroscience. S. Diego: Academic Press, 1996) Localized inactivations produce modular deficits. Damage to the cerebellar nuclei causes unique behavioral deficits (Thach, 1998). Ablations of the fastigial nucleus in cat and monkey dramatically impair movements requiring control of equilibrium, such as unsupported sitting, stance, and gait. Longitudinal splitting of the cerebellum along the midline also produces very significant and long-lasting disturbances of equilibrium. In humans, lesions in the anterior vermus preferentially impair movements requiring equilibrium control (Timmann & Horak, 1995). Much of the fastigial nucleus seems to be preferentially involved in movements like stance and gait. Ablations of the interpositus nucleus in monkeys cause action tremor as the animals reach for food. Temporary inactivation of the interpositus nucleus and adjacent regions of dentate with cooling probes elicits tremor that is dependent on proprioceptive feedback but is uninfluenced by vision. Focal pharmacological inactivations within the intermediate region disrupt the use of particular synergies related to hand use and limb positioning (Mason et al. 1998). Damage to the cortex and the inferior olive prevents many kinds of motor adaptation, including the acquisition of new and novel muscle synergies. These studies support the ideas reviewed earlier in this chapter, namely that the intermediate cerebellum regulates the composite motor commands that control the metrics of coordinated upper and lower extremity limb movements. Damage to the posterior vermis and floculonodular lobe produce analogous disorders of eye movements (Chapter 33). Summary Activation and inactivation studies of the cerebellum are consistent with the concepts promoted earlier in this chapter. The cerebellum learns how to regulate neuronal populations in different parts of the brain that control different kinds of movement, autonomic function, and cognitive signal processing. PHYLOGENETIC AND ONTOGENETIC DEVELOPMENT There are two kinds of development phylogenetic, in the course of evolution, and ontogenetic, from the embryo to the adult animal. Both involve an enlargement of the Page 36 36

37 cerebellum that parallels the enlargement of other parts of the brain, but there are many exceptions to the concept that ontogeny recapitulates phylogeny. The cerebellum reflects the course of vertebrate evolution. The cerebellum is present in all vertebrates from the primitive myxinoids up through the advanced primates, although its parts show considerable species variation. In the lamprey (agnathans), the cerebellum is a rudimentary structure that assists the functions of the well-developed vestibuloocular, vestibulospinal, and reticulospinal systems, and is equated to the flocculonodular lobe. The cerebellum is much larger in fishes, where a corpus cerebelli distinctly appears. In electric fish (Box 32.3), the cerebellum is extraordinarily developed and includes lobes not present in other vertebrates. The cerebellum increases further in reptiles and birds, although it consists nearly exclusively of the vermal zone of the corpus cerebelli and the flocculonodular lobe. Well developed glomeruli are present in reptiles and birds. Basket cells, however, are absent in reptiles and are well developed in birds, pointing to evolutionary sophistication of inhibitory interneural connections. In birds, the vermis is distinctly foliated and lobules I through X are clearly apparent, but the basilar pontine nuclei are rudimentary and project to small, flattened lateral zones. In mammals, the lateral cerebellar zone expands to form the cerebellar hemispheres, in register with the development of the pontine nuclei and the cerebral cortex. Box 32.3: THE GIGANTOCEREBELLUM OF MORMYRID FISH Weakly electric fish of the family Mormyridae have an enormous cerebellum that covers their brain like our cerebral cortex covers our brain. This gigantocerebellum explains why these fish have a large brain to body ratio of 0.03 and why their brain uses 60% of the oxygen that they take in. For comparison, our brain to body ratio is only 0.02 and our brain uses only 20% of the oxygen we take in. The gigantocerebellum is composed of a ribbon of Purkinje cells, 0.3mm high and 1.0 meter long, that is folded back on itself repeatedly to fit within the skull. Different regions of the cerebellum receive electrosensory, auditory and lateral line input from midbrain structures homologous to the mammalian inferior colliculus. These cerebellar regions project back to the same midbrain sensory structures from which they receive their input. Thus, this cerebellum is more involved in processing sensory input than in generating motor output. Although the type of processing that is done by the fish s cerebellum is still unknown, cerebellum-like structures in another part of these fish brains, the electrosensory lobe and the dorsal octaval nucleus, generate memory-like expectations of sensory input by means of plastic changes at synapses between parallel fibers and Purkinje-like cells (Bell, 2001), analogous to what probably occurs in the cerebellum itself. Curtis C. Bell Bell, C.C. Memory based expectations in electrosensory systems. Current Opinion in Neurobiology., 11, , In evolution, the size of the cerebellar cortex increases more distinctly than that of the cerebellar nuclei, reflecting a greater emphasis on the computational aspects of Page 37 37

38 information processing. While lobulation, in principle, is fairly consistent across mammals despite great variation in hemispheric development, foliation shows great interspecies variation and also substantial intraspecies differences. For example, different mouse strains may show different folial patterns. In aquatic mammals, the vermal and the intermediate zones and the underlying fastigial and posterior interpositus nuclei are large, and the lateral zones relatively small. The vermal and hemispheral portions of the posterior lobe that receive pontine afferents appear mostly expanded in the primate, and especially the human. The cortico-ponto-cerebellar input loops back to many areas of the cerebral cortex. In human, the fibers of the middle cerebellar peduncle vastly outnumber all of the other connections. In the embryo, outputs develop first. Cerebellar neurons develop at different times from two different germinative matrices, the ventricular epithelium of the cerebellar anlage and the cells of the rhombic lip (Fig ). The cerebellar anlage, or primordium, begins as bilateral elevations of the dorsal aspect of the primitive hindbrain and caudal midbrain that grow towards the midline and ultimately fuse (Liu & Joyner, 2001). The ventricular epithelium of this anlage gives rise to all cerebellar neurons, except the granule cells, by a process of outward directed migration. The rhombic lip is an elevation of the rostral hindbrain that extends from the first to the eighth rhombomere. It gives rise to the external granular layer precursors, from which granule cells originate by inward migration. The first cells to be formed in the ventricular zone of the cerebellar anlage are the neurons of the cerebellar nuclei. They are followed soon after by Purkinje cells, which migrate past the developing cerebellar nuclei to their ultimate location in the cortex. Precursors committed to differentiate into unipolar brush cells, Golgi cells, basket cells, stellate cells, and glial cells, which are produced in later waves, migrate to their final positions after the migration of the Purkinje cells, and continue to proliferate on their way to the cortex. At an early stage, small cells migrate from the rhombic lip over the entire external surface of the cerebellum forming the so-called external granular layer, where they remain quiescent till much later in development. Page 38 38

39 Fig Early development of mouse cerebellum. (A) At embryonic day E9-E10, the rhombic lip (blue and orange) is a zone of proliferation at the level of the fourth ventricle. Cells in the blue region give rise to the cerebellar granule neurons and pontine nuclei, whereas cells in the orange region give rise to other rhombic lip derivatives such as the inferior olivary nucleus. (B) At E13, cells from the rhombic lip migrate outwards to cover the cerebellar primordium forming the extrenal granular layer. (C) At early postnatal stages (P1 and further), these committed granule cell precursors continue to proliferate in the outer external granular layer (EGL), then become postmitotic and form the inner EGL, and finally migrate from the inner EGL past the Purkinje cells and into the inner granular layer, where they differentiate into granule cells establishing synaptic connections with mossy fiber terminals. (Reproduced from V.Y. Wang and H.Y. Zoghbi, Nature Reviews, 2: , 2001) Cerebellar input structures develop next. After the Purkinje have reached the cortical plate, climbing fibers enter the cerebellum from the inferior olive and begin to innervate the Purkinje cells (Fig ), each Purkinje cell receiving input from several climbing fibers. Much later, after the Purkinje cells have begun to receive synapses from parallel fibers, most of the climbing fiber contacts with Purkinje cells will be eliminated leaving a private line of one climbing fiber per Purkinje cell. Mossy fibers also enter the cerebellum and grow to the level just below the Purkinje cell layer. They will ultimately synapse on granule cells, which have yet to arrive. Page 39 39

40 Fig Development of the Climbing Fiber-Purkinje Cell Pathway. After the Purkinje cell becomes synaptically competent at postnatal day 5 (P5), branches from two or more climbing fibers establish contact with short processes arising from the soma, and successively grow to occupy first the apical dendritic stem (P10) and then the entire proximal compartment of the dendritic tree (P15). During formation of the spiny branchlets and parallel fiber synapses, supranumerary climbing fibers branches retract, leaving only one climbing fiber branch per Purkinje cell (P20). (based on F. Crepel, J.R. Dupont and R. Gardette In: Gene Expression and Cell-Cell Interactions in the Developing Nervous System. J.M. Lauder and P.G. Nelson, Plenum Publishing Corp.: , 1984) Shortly before and after birth, cells in the external granular layer form two contiguous strata over the developing cerebellum, the proliferative outer external granular layer, and the postmitotic, premigratory inner external granular layer (Fig ). Cells of the inner layer emit axons at opposite poles that run in the coronal plane (the future parallel fibers) and then form a third process that extends towards the underlying Purkinje cells utilizing the radial Bergmann fibers as a scaffold. The third process extends progressively past the Purkinje cell layer, and the cell nucleus translocates into the process and reaches the prospective granular layer, leaving the elongating parallel fiber in place (Fig ). Normally, all external granules abandon the external granular layer. After this surface-todepth migratory process the differentiating granule cell emits short processes, or protodendrites, that search the developing mossy fiber terminals to establish connections. Successively, some of the protodendrites are pruned, while 3-5 of them progressively Page 40 40

41 mature into adult granule cell dendrites. At the same time, the mossy fiber terminals enlarge to accommodate the optimal number of dendritic claws. Concomitantly, the Golgi cell axons establish their synapses at the base of the claws. Ensheathing of the glomeruli by lamellar processes of astrocytes becomes progressively more complete. In rodents, this process of glomerular development takes about six weeks. It is interesting that the "motor" side of the cerebellar circuit (the deep nuclear cells and Purkinje cells) forms first, the "sensory" side (MFs and CFs) then arrives in place, and the "matrix" that connects the two (the granule cells and intrinsic inhibitory neurons) is the last to develop. BOX 32.4: GENES CONTROLLING CEREBELLAR DEVELOPMENT Work on mouse mutant strains with cerebellar abnormalities (eg., weaver, reeler, staggerer, rostral cerebellar malformation) and genetic studies on formation of the hindbrain have uncovered a multitude of genes and signaling pathways that govern development of the brainstem and cerebellum (Wang & Zoghbi, 2001). Moreover, classes of cerebellar neurons, and especially the Purkinje and granule cells have been shown to interact during cerebellar development in regulating cell number and compartmentalization. The complex interplay of several patterning genes (primarily Otx2, Gbx2, and Fgf8) sets up the isthmus organizer. This region of the early neural tube, situated at the junction between mesencephalon and metencephalon, regulates the rostrocaudal patterning of the midbrain-hindbrain and the formation of the cerebellar primordium. Other sets of intracellular and secreted gene products control discrete steps in cerebellar development. Math1 and genes coding numerous zinc finger proteins play major roles in generation, proliferation and movement of granule cell precursors in the germinal matrix of the rhombic lip. Semaphorins, slits, netrins, and TAG1 regulate dorsoventral migration from the rhombic lip and formation of precerebellar nuclei and pathways. Cyclin D2 and Unc5h3 regulate the proliferation and rostral arrest of the external granular layer, respectively. Migration of differentiating granule cells along the glial fibers of the molecular layer is set up by several molecules, including cell-cycle inhibitors, tubulin associated proteins, trombospondin, astrotactinn and neuroregulin. The genes controlling proliferation of Purkinje cell precursors are poorly known, while genes of the reelin signaling pathway and netrin receptors regulate Purkinje cell migration. Genetic mechanisms that control the anterior-posterior compartmentalization and foliation of the cerebellum are beginning to be defined, while little is known about developmental regulation of the parasagittal zones. Several molecules promoting Purkinje cell and granule cell survival have been identified. These include growth factors, ion channels, and neurotransmitters. Proliferation, migration, and survival of the precursors of Golgi cells, unipolar brush cells, and stellate/basket cells are still scarcely known. Wang, V. Y., and Zoghbi, H. Y. (2001) Genetic regulation of cerebellar development Nature Reviews, 2: , 2001 Page 41 41

42 Fig Four dimensional (time and space) developmental reconstruction of the targets of the mossy fiber-parallel fiber-purkinje cell pathway. Granule cell precursors (arrows 1-7) migrate from the external granular layer to the definitive granular layer along the radially oriented Bergmann glial fibers (BGF), leaving in place the parallel fibers (a, stacked thin rods) in a process of appositional growth. Bergman glia fibers are processes of the astrocytic Golgi epithelial cells (GEC) situated in the Purkinje cell (PC) layer. PCD, proximal Purkinje cell dendrite forming spiny branchlets. St, stellate cells oriented perpendicular to the parallel fibers. Pia, pial membrane; EGL, external granular layer; ML, molecular layer; PCL, Purkinje cell layer; GL, granular layer. (Reproduced from Rakic, P., J. Comp. Neurol. 141: , 1972, with permission). Page 42 42