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Cerebellum and Activation of the Cerebellum IO ST During Nonmotor Tasks

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Cerebellum and Activation of the Cerebellum IO ST During Nonmotor Tasks Cerebellum (Kandel & Schwartz & Jessell, 4th ed.) Granule186 cells are irreducibly smallChapter (6-8 7 μm) stellate cell basket cell outer synaptic layer PC rs cap PC layer grc Go inner 6 μm synaptic layer Figure 7.15 Largest cerebellar neuron occupies more than a 1,000-fold greater volume than smallest neuron. Thin section (~1 μ m) through monkey cerebellar cortex. Purkinje cell body (PC) and nucleus are far larger than those of granule cell (grc). The latter cluster to leave space for mossy fiber terminals to form glomeruli with grc dendritic claws and space for Golgi cells (Go). Note rich network of capillaries (cap). Fine, scat- tered dots are mitochondria. Courtesy of E. Mugnaini. brain ’ s most numerous neuron, this small cost grows large (see also chapter 13). Much of the inner synaptic layer is occupied by the large axon terminals of mossy fibers (figures 7.1 and 7.16). A terminal interlaces with multiple (~15) dendritic claws, each from a different but neighboring granule cell, and forms a complex knot (glomerulus ), nearly as large as a granule cell body (figures 7.1 and 7.16). The mossy fiber axon fires at an unusually high mean rate (up to 200 Hz) and is therefore among the brain’ s thickest (figure 4.6). To match the axon’ s high rate, a terminal expresses 150 active zones, 10 per postsynaptic granule cell (figure 7.16). These sites are capable of driving … and most expensive. 190 Chapter 7 10 4 8 3 9 19 10 10 × 6 × 2 2 4 ATP/s/cell ATP/s/cell ATP/s/m 1 2 0 0 astrocyte astrocyte Golgi cell Golgi cell basket cell basket cell stellate cell stellate cell granule cell granule cell mossy fiber mossy fiber Purkinje cell Purkinje Purkinje cell Purkinje Bergman glia Bergman glia climbing fiber climbing fiber Figure 7.18 Energy costs by cell type. Left : Purkinje cell is the most expensive neuron, and gran- ule cell is cheapest. Right : Granule cell array is the most expensive, and Purkinje cell array is far cheaper. Glial cells are cheap individually and as arrays. Reprinted with permission from Howarth et al. (2012). a granule cell’ s output synapse is structured to reliably deliver a precisely timed message — privately (Nahir & Jahr, 2013). All 150,000 parallel fiber synapses onto an individual Purkinje cell tend to be wrapped by the same glial cell ( Bergman glia), whose form mimics that of the Purkinje cell ’ s exten- sive dendritic tree (figure 7.1). The different tasks of inner and outer cerebellar layers and their conse- quent different designs illustrate why there can be no generic neuron. In the inner layer, high-rate synapses improve S/N by pooling excitatory responses and sharpen timing precision with feedback inhibition— to allow a burst of information-rich spikes (figure 7.16). In the second case, spikes deliver this information by a synaptic design that facilitates to a burst (fig- ure 7.17). The first design reduces glial wrapping to enhance synaptic spill- over; the second design does the opposite. Now we can ask: what are the costs of these two designs? Costs of different neuron designs Energy costs by cell type When the various energy costs are totaled, the individual Purkinje cell proves to be the most expensive neuron, and granule cell proves to be the Cerebellum stores sensorimotor contingency between vestibular signals and oculomotor response (VOR) 366 THE CENTRAL NERVOUS SYSTEM Granule cell Flocculus + Purkinje cell + Climbing Fiber Mossy Fiber Inferior olive fi gure 25.4 Main structural elements of the Pretectal nuclei vestibulo-ocular refl ex. Only excitatory connec- + tions are shown, even though there are inhibitory neurons in the vestibular nuclei that infl uence the - motoneurons of the antagonists. The refl ex arc consists of three neurons from the semicircular duct to the extraocular muscles. The cerebellar fl occulus receives signals from the labyrinth and from the retina, and the output of the Purkinje cells can adjust the sensitivity of the vestibular neurons, Labyrinth Vestibular Eye muscle if necessary, to avoid retinal slip. (Based on Ito (semicircular ducts) nucleus nucleus 1984.) reflex is three-dimensional in the sense that all direc- “functional” words. Native readers of English perceive tions of head rotation elicit specific compensatory eye about 4 letters to the left and 15 to the right of the point movements.1 of fixation. 5. Vergence movements change the visual axes of the A woman with inborn ophthalmoplegia (inability to eyes in relation to each other when the point of fixation move the eyes) had surprisingly small problems and was moves away from or toward the eyes. This is necessary able to live a normal life. She apparently used quick head to keep the image on corresponding points of the retina. movements to compensate for the lack of saccadic eye Vergence movements are a prerequisite for fusion of the movements (Gilchrist 1997), and was thereby able to two images and for stereoscopic vision. Convergence of scan the visual scene with sufficient speed and accuracy. the visual axes, which takes place when an object is approaching the eyes, depends primarily on the activity The Cerebellum Can Adjust the Vestibulo-Ocular of the medial rectus muscles, with some contribution Refl ex to Changing External Conditions also from the superior and inferior recti (Fig. 15.2). Accommodation and pupillary constriction accompany The magnitude of the reflex response (not the response convergence movements.2 itself) to a certain rotational stimulus depends on signals to the vestibular nuclei from the cerebellum (Fig. 25.4). The Purkinje cells of the vestibulocerebellum receive More about Voluntary Saccades and Scanning primary vestibular fibers (ending as mossy fibers) that When reading we fixate a point on the line for an aver- provide information about direction and velocity of the age of 250 msec (60–500) before the gaze is moved on head movement. In addition, the same Purkinje cells by a saccade. How far the gaze moves before reaching a receive information, via the inferior olive and climbing new point of fixation varies greatly. There is a tendency fibers, about whether the image is stationary or slips on to fixate on long “content” words rather than on short the retina. A retinal slip indicates that the velocity of the compensatory head movement is too high or too 1 The VOR described here—the rotational VOR or RVOR—is not the only low. The cerebellum is then capable of adjusting the vestibulo-ocular refl ex. Translatory (linear) accelerations of the head (stimulat- excitability (the gain) of the neurons in the vestibular ing the sacculus and utriculus) also elicit compensatory eye movements (trans- nuclei—that is, in the reflex center of the vestibulo- lational VOR, or TVOR; otolith-OR, or OOR). In real life, both kinds of head movement occur, and the different sensory inputs from the labyrinth must be ocular reflex. Such adaptive change of gain of the reflex integrated centrally to yield a motor command that ensures a stable retinal is presumably needed continuously during growth and image. in situations of muscular fatigue. Experiments in which 2 Gaze holding is sometimes included among the kinds of eye movement. It is the ability to stabilize the eye position (and the image on the retina) after a shift animals wear optic prisms that deflect the light so that of gaze. Premotor neurons controlling gaze holding appear to rely on a partly it appears to come from another direction than it really separate premotor network, although located close to the paramedian pontine does, show the remarkable capacity for adaptation reticular formation (PPRF) and the rostral interstitial nucleus of the medial longitudinal fasciculus (riMLF). (learning) in this system. (Kandel & Schwartz & Jessell, fourth edition, Figure 42-7) Traditional random-access memory (RAM) KANERVA / SDM AND RELATED MODEL S /02/02/0 2 /Fig. 3.3 ADDRESS REGISTER WORD-IN REGISTER 20 bits 32 bits x 000••• 011w 010 ••• 110 y N U 000 000 0 001 001 000 001 0 111 111 000 010 0 100 010 000 011 1 010 110 000 100 0 000 111 000 101 0 001 100 A C ADDRESS MATRIX CONTENTS MATRIX ••• 1,000,000 locations 1,000,000 M addresses M ×U bits 20 111 100 0 010 000 2 111 101 0 111 100 111 110 0 110 011 M 111 111 0M 000 000 select z 010••• 110 WORD-OUT REGISTER 32 bits Figure 3.3. Organization of a random-access memory. The selected memory location is shown by shading. Sparse, distributed memory (SDM) KANERVA / SDM AND RELATED(Kanerva, MODEL S /02/02/0 2 /Fig. 3.4 1988) ADDRESS REGISTER WORD-IN REGISTER 1,000 bits 1,000 bits x 100••• 101w 010 ••• 110 N d y U 010 101501 0 022400 101 001444 1 1 1 1131 010 011550 0 113 111 000 101447 1 242 020 111 001493 0 111 3 1 1 000 110531 0 204020 A C ADDRESS MATRIX CONTENTS MATRIX M hard addresses ••• ••• M ×U counters 111 000480 0 131335 1,000,000 hard locations hard 1,000,000 100 100446 1 111111 100 010512 0 204064 M 011 011498 0M 000 000 select Hamming distances ••• 77 611 379 s 201 517 445 Activations (d 447) Sums z 010••• 110 WORD-OUT REGISTER 1,000 bits Figure 3.4. Organization of a sparse distributed memory. The first selected memory location is shown by shading. KANERVA / SDM AND RELATED MODEL S /02/02/0 2 /Fig. 3.5 A5 A 4 AM 2 x H A M A 1 A 2 A M 3 AM 1 A3 A 6 Figure 3.5.
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