Procedural Learning: VOR

3.20 Procedural Learning: VOR K. E. Cullen, McGill University, Montreal, QC, Canada ª 2008 Elsevier Ltd. All rights reserved.

3.20.1 3.20.2 3.20.2.1 3.20.2.2 3.20.3 3.20.3.1 3.20.3.2 3.20.3.3 3.20.4 3.20.4.1 3.20.4.2 3.20.4.3 3.20.4.3.1 3.20.4.3.2 3.20.4.4 3.20.5 3.20.5.1 3.20.5.2 3.20.6 3.20.6.1 3.20.6.2 3.20.6.3 3.20.6.4 3.20.7 3.20.7.1 3.20.7.2 3.20.7.3 3.20.8 References

Introduction Why Do We Need to Adapt the Gain of the VOR? A Brief Introduction to the VOR The Adaptive Capabilities of the VOR Historical and Current Models of VOR Adaptation The Cerebellum and Motor Learning Two Historically Influential Models of Motor Learning in the VOR More Recent Evidence and the Emergence of the Multisite Hypothesis of Motor Learning Neuronal Networks and Single-Unit Recording Studies Review of Direct VOR Pathways Changes in Neural Responses in the Adapted State: Vestibular Afferents Changes in Neural Responses in the Adapted State: Vestibular Nuclei PVP neurons Floccular target neurons Changes in Neural Responses in the Adapted State: Flocculus and Ventral Paraflocculus Current Models of Long-Term VOR Modulation Support for a Multiple-Site Hypothesis The Role of the Flocculus versus Ventral Paraflocculus in VOR Learning Cellular Mechanisms of VOR Motor Learning: Evidence for LTD versus LTP Cellular Mechanisms for VOR Motor Learning in the Flocculus Cellular Mechanisms for VOR Motor Learning in the Vestibular Nuclei Cellular Mechanisms Underlying Increases versus Decreases in VOR Gain Cellular Mechanisms: Open Questions Context-Dependent VOR Motor Learning Stimulus-Dependent VOR Motor Learning: Behavior Stimulus-Dependent VOR Motor Learning: Neuronal Pathways Context-Specific Changes in VOR Gain Conclusions

3.20.1 Introduction Humans can learn skilled motor tasks, such as riding a bike, playing the piano or even hitting an accurate topspin serve in tennis. This long-term ‘motor memory’ is referred to as procedural memory. Although practice can improve performance, memories of these learned movements remain remarkably intact, even after years of disuse. Procedural or ‘motor’ learning also serves an important role in calibrating simpler movements such as eye movements and reflexes. One class of eye movements, the vestibuloocular reflex (VOR), is a particularly useful model

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system. The VOR produces compensatory eye movements that are required to stabilize gaze and ensure clear vision during the head movements that are generated during everyday activities such as walking and running. The VOR shows impressive adaptation in response to environmental requirements. Furthermore, the relative simplicity of the neural circuit that mediates this reflex has proven to be well suited to linking systems and cellular levels of analyses of motor learning. Procedural memory is generally contrasted with declarative memory, which is the memory of facts or experiences. Over the past decade, work on learned 383

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reaching movements has provided evidence to support the idea that procedural memory, like declarative memory, passes through multiple stages before becoming stable, including encoding, consolidation, and retrieval (see a recent review by Robertson, 2004). Similarly, the findings of recent behavioral, single-unit recording and lesion studies have established that VOR motor learning passes through distinct stages. Moreover, neural substrates underlying the progression of learning in this model system have been localized, and significant progress has been made in understanding the cellular mechanisms that control their formation. In addition, the commonly held idea that procedural learning is characterized by the transformation of a memory from a fragile state to a new permanent memory has been challenged. Recent studies of the VOR, in particular, have emphasized the importance of contextual cues in guiding the retrieval of learned responses. This chapter will review the findings of behavioral, single-unit recording and lesion studies of VOR motor learning. First, the current understanding of the neural mechanisms that underlie motor learning in the VOR will be reviewed. Then recent evidence supporting the idea that VOR motor learning is characterized by a progression of changes in multiple brain areas will be discussed. Finally, these findings will be integrated in relation to recent experiments that have characterized context-dependent learning in the VOR.

3.20.2 Why Do We Need to Adapt the Gain of the VOR? 3.20.2.1

A Brief Introduction to the VOR

The simplicity of the three-neuron arc that produces the VOR is reflected in its fast response time (Figure 1(a)); compensatory eye movements lag head movements by only 5 6 ms in the primate (reviewed in Cullen and Roy, 2004). This reflex produces eye movements in response to both the angular and linear components of head movement and functions to move the eyes in the opposite direction of the concurrent head motion. For example, if a subject undergoes passive head rotation in darkness, the gain of the VOR, which is defined as compensatory eye velocity divided by head velocity, is 1.0. The VOR initiates eye movements at much shorter latencies than those of visually mediated eye

movements. As a result, the VOR is fast enough to stabilize gaze during common activities such as locomotion. Bilateral loss of vestibular function is extremely debilitating because without a functional VOR, simple activities such as walking or driving are accompanied by oscillopsia – the illusion that the environment is moving when we move our heads.

3.20.2.2 The Adaptive Capabilities of the VOR The VOR is capable of impressive adaptation in response to environmental requirements. To date, perhaps the most dramatic illustration of the adaptive capabilities of this reflex was provided by a study in which participants wore prisms, which reverse the world such that left was right and vice versa (Gonshor and Jones 1976; Figures 1(b)–1(c)). Within minutes of wearing the prisms, the gain of the VOR substantially declined. Moreover, when reversing prisms were worn for extended periods (3–4 weeks), the response of the VOR actually reversed; head movements induced an eye movement in the same rather than opposite direction. This change was appropriate to account for the new demands that were imposed on the reflex by the spectacles and accordingly produced improved stabilization of the world on the retina during head movements. In more commonly encountered situations, the demands on the VOR are less challenging. Nevertheless, the adaptive capabilities of the VOR are essential to guarantee gaze stability throughout life. In humans the VOR must be continuously adjusted in the first years of life to compensate for significant changes in head circumference (30% in the first year). Later in life, adaptive changes in VOR performance are required to compensate for the magnification of corrective lenses that are worn for common visual conditions. For example, the VOR gain in myopic individuals who wear convex lenses will be lower than for individuals with normal vision. The adaptability of the VOR is also critical to compensate for the effects of aging, disease, and trauma on the nervous system. Notably, the VOR shows remarkable recovery following the loss of unilateral labyrinthine input as a result of injury. Similarly, the reflex shows robust adaptation to the incremental loss of the receptor cells that occur naturally during aging.

Procedural Learning: VOR

(b) 1.0 Normalized VOR gain

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Figure 1 (a) Eye response following a transient head perturbation. Following the onset of head rotation, the eye begins to counterrotate after a latency of 5–6 ms. The gain of the reflex is eye velocity divided by head velocity. Note that eye velocity has been inverted to facilitate comparison. (b) Changes of VOR gain after wearing reversing prisms for 8 days. (c) Example of the VOR in a subject who continuously wore reversing prisms for 49 days. By day 18, the mean response phase was nearly inverted (i.e., 140 deg phase shift) relative to the correct nonreversed compensatory response. From (a) Marko Huterer M and Kathleen E. Cullen KE (2002) Vestibuloocular reflex dynamics during high-frequency and high- acceleration rotations of the head on body in rhesus monkey. J Neurophysiol. 88: 13–28; 10.1152/jn.01034.2001. (b, c) Gonshor A and Jones G (1976) Extreme vestibulo-ocular adaptation induced by prolonged optical reversal of vision. J. Physiol 256: 381–414.

3.20.3 Historical and Current Models of VOR Adaptation 3.20.3.1 The Cerebellum and Motor Learning The cerebellum is required for VOR motor learning; new gains cannot be learned after the vestibular cerebellum is removed. The basic circuitry of the cerebellum is highly organized and consists of repeating motifs of five primary cell types: Purkinje cells, granule cells, basket cells, stellate cells, and Golgi cells which are organized into the same basic circuit all across the cerebellum (Eccles et al. 1976). The Purkinje cells are the only neurons whose axons

leave the cerebellum, and it is noteworthy that these cells send inhibitory projections to their targets within the vestibular and deep cerebellar nuclei. The other cell types are local circuit neurons whose axons make synaptic connections within the cerebellar cortex. There are two main input pathways to the cerebellum – mossy fibers and climbing fibers. Mossy fiber inputs arise from many regions of the brainstem and spinal cord, including those from the vestibular system via direct projections from the vestibular nerve and vestibular nuclei. Mossy fibers affect the discharges of Purkinje cells through cerebellar interneurons called granule cells. These latter neurons

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send projections to Purkinje cells via parallel fibers. Climbing fiber inputs arise from the inferior olive and make powerful excitatory synaptic connections with Purkinje cells. Typically each Purkinje cell receives only one climbing fiber input, but each climbing fiber spike evokes a powerful EPSP, which causes repetitive discharge in Purkinje cells. The Purkinje cell discharge is then followed by a prolonged pause in its firing rate due to additional climbing fiber synapses on inhibitory interneurons (Figure 2(a)). Mossy fiber and climbing fiber inputs to the cerebellum each shape the discharge patterns of

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Purkinje cells in a very specific way. Inputs from the climbing fibers result in generation of complex spikes (or alternatively climbing fiber responses) in the Purkinje cells. In contrast, mossy fiber inputs are responsible for the simple spike activity of Purkinje cells. Simple spikes (SS) occur much more frequently (discharge rates reaching up to 300 sp/s) as compared to complex spike activity (1 sp/s). In addition SSs are shorter in duration than complex spikes, which can last as long as 2–5 ms. The conceptual framework put forth by Marr (1969) and Albus (1971) more than three decades ago has been extremely influential in shaping our current view of the role of the cerebellum in motor learning. In this framework, the role of the climbing fiber input to the cerebellum is to modify the response of Purkinje cells to mossy fiber inputs. The specific hypothesis is that climbing fibers signal errors in motor performance and alter parallel fiber (i.e., mossy fiber-related) Purkinje cell synaptic efficacy. There is considerable evidence to support this idea: Lesions of the cerebellum abolish several types of motor learning, climbing fibers can carry signals that are related to motor performance error, and lesions of the inferior olive abolish some types of motor learning (reviewed in Boyden et al., 2004).

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3.20.3.2 Two Historically Influential Models of Motor Learning in the VOR

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Figure 2 (a) Extracellular recording from an example floccular Purkinje cell showing its high-frequency simple spike (SS) activity as well as complex spike activity (CS) which is due to the climbing fiber input. (b) Two pathways control the gain of the VOR. The main reflex path of gain is paralleled by an inhibitory side branch through the vestibulocerebellum with a gain (beta) so that total gain is proportional to (alpha-beta). Abbreviations: CF, climbing fibers; GC, granule cells; IO, inferior olive; MF, mossy fibers; OMN, oculomotor nuclei; PC, Purkinje cells; VN, vestibular nuclei; aot, accessory optic tract; SCC, semicircular canal; _ head velocity. From (a) Courtesy of _ eye velocity; H, E, Simpson J and Maruta J. (b) Modified from Robinson DA (1976) Adaptive gain control of vestibuloocular reflex by the cerebellum. J. Neurophysiol. 39:954–969.

The results of single recording and more confined lesion studies have more precisely established that the flocculus and ventral paraflocculus (herein called the floccular complex) of the vestibulocerebellum mediate motor learning in the VOR (e.g., Ito et al., 1974, 1982; Robinson, 1976; Nagao, 1983; Lisberger et al., 1984). Mossy fiber projections from the vestibular nuclei provide a source of head movementrelated information to the floccular complex. In turn, the Purkinje cells of the neurons of the floccular complex send monosynaptic inhibitory projections back to neurons in the vestibular nucleus that mediate the VOR (Fukuda et al., 1972; Highstein, 1973; Ito et al., 1977; Sato et al., 1988). Effectively, this vestibular–cerebellar–vestibular pathway provides a parallel inhibitory side loop that can modulate the gain of the direct VOR pathway (Figure 2(b)). To change the gain of the VOR response, there must be adaptive adjustment(s) of the synaptic efficacy between the neuronal elements that mediate the reflex. The question of where and how this adaptation occurs has been debated, and in

Procedural Learning: VOR

particular two hypotheses of motor learning in the VOR have dominated the literature. The principal difference between these two models is the location of the modified synapses that underlie motor learning. First, in 1972, Ito introduced an influential theory of VOR adaptation based on the Marr–Albus model of cerebellar motor learning. In Ito’s adaptation of the Marr–Albus model to VOR learning, the climbing fiber input from the inferior olive provides an error

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signal that alters the parallel fiber (i.e., mossy fiberrelated) Purkinje cell synaptic efficacy. This error signal modifies the head velocity-related modulation of Purkinje cells to change the gain of this cerebellar loop of the VOR circuitry so that the VOR is compensatory (Figure 3(a); red star). Consistent with this theory, climbing fiber inputs to the floccular complex chiefly encode visual slip information, which provides an indication of the reflex performance (Maekawa and Simpson, 1973; Simpson and Alley,

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Figure 3 Two models of VOR motor leaning. (a) In Ito’s model, climbing fibers encode a visual error signal, which induces learning at the synapses of vestibular parallel fibers onto the Purkinje cells. (b) In the Miles–Lisberger model, floccular Purkinje cells encode an error signal, which supports the modification of synapses in the target neurons of the vestibular nuclei. See text for additional details. From Kandel ER, Schwartz JH, and Jessell TM. Principles of Neural Science, 4th edn. Copyright ª 2000 by The McGraw-Hill Companies; Chapter 41.

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1974; Ghelarducci et al., 1975; Graf et al., 1988). According to Ito’s theoretical framework, learning continues until the visual slip signal (which is a measure of performance error) encoded by the climbing fibers becomes zero. At this point, the VOR would be fully compensatory and so no further adaptation would be required. Alternatively, Miles and Lisberger (1981) proposed that the floccular complex provided an instructive signal to the vestibular nuclei, to guide plastic changes that took place exclusively in the brainstem (Figure 3(b); green star). This hypothesis incorporated the finding that the Purkinje cells of the floccular complex receive significant eye as well as head movement-related information from their mossy fiber inputs via projections from the vestibular, reticular, raphe, and perihypoglossal nuclei. These investigators hypothesized that when the VOR is in the normal state (i.e., when there is no retinal slip during head movements), eye and head movement signals would be equal and opposite and thus would cancel each other out. As a result, no net drive would be encoded by Purkinje cells, and thus no instructive signal would be sent to the vestibular nuclei. However, when retinal slip is present, as would be the case after donning magnifying or minimizing lenses, visual tracking responses (i.e., pursuit) would be recruited to adjust the eye movement response. As a result a significant eye movement signal would be sent back to the floccular complex, and so the output of the Purkinje cells would code an error signal that represents the difference between eye and head movement. In this schema, the error signal guides plastic changes at the level of neurons in the vestibular nuclei, so that the modified VOR pathways will produce stable gaze.

3.20.3.3 More Recent Evidence and the Emergence of the Multisite Hypothesis of Motor Learning More recently, substantial evidence has accumulated to support an alternative view, namely that the site of motor learning is not exclusively restricted to either the cerebellar cortex of the floccular complex nor to the vestibular nuclei. Evidence for this proposal has been provided by the results of single-unit recording experiments as well as lesion and transgenic studies. These findings are discussed in the sections titled ‘Neuronal networks and single-unit recording studies’ and ‘Current models of long-term VOR

modulation’ in relation to the Ito and Miles– Lisberger models of motor learning in the VOR.

3.20.4 Neuronal Networks and Single-Unit Recording Studies 3.20.4.1

Review of Direct VOR Pathways

The three-neuron arc responsible for mediating the direct VOR pathway consists of projections from vestibular afferents to interneurons in the vestibular nuclei, which in turn project to extraocular motor neurons. Because it is experimentally less challenging to rotate an alert subject in the yaw axis than in the pitch or roll axes, the circuit that mediates the horizontal VOR has been best characterized. Hair cells within the horizontal semicircular canals are activated by ipsilaterally directed head rotations. In turn these receptor cells excite the vestibular afferents, which project via the VIII nerve to neurons within the vestibular nuclei. In particular, neurons in the rostral medial and the ventrolateral subdivisions of the vestibular nuclei receive direct inputs from horizontal semicircular afferents (Fuchs and Kimm, 1975; Keller and Daniels, 1975; Chubb et al., 1984; Scudder and Fuchs, 1992; Cullen et al., 1993). These neurons in the vestibular nuclei in turn project to the extraocular motor neurons that project to the lateral and medial recti. To date, single-unit studies have focused on the responses of vestibular afferents and neurons in the vestibular nuclei, but not the motor neurons. 3.20.4.2 Changes in Neural Responses in the Adapted State: Vestibular Afferents In addition to their centrally projecting connections, vestibular receptors receive innervation from centrifugally projecting efferent neurons located near the abducens nucleus (Rasmussen and Gacek, 1958; Gacek and Lyon, 1974; Goldberg and Fernandez, 1980). Electrical activation of the vestibular efferent pathway results in an increase in resting discharge and decrease in sensitivity of vestibular afferents in toad fish and squirrel monkeys (Goldberg and Fernandez, 1980; Highstein and Baker, 1985). Thus, in theory, the vestibular efferent system could be used to alter the dynamic range of the input that is available at the level of the nerve to guide changes in VOR gain. Miles et al. (1980a) investigated this possibility in monkeys following VOR learning. No change in

Procedural Learning: VOR

afferent responses was observed after motor learning was induced by having the animals wear magnifying or minimizing prisms for more than a month. Neuronal responses were tested over a limited range of frequencies 0.1–1 Hz (peak velocity of 20 deg/s). A more recent study (Sadeghi et al., 2006) has extended these findings to show that the responses of vestibular afferents are similarly not altered following contralateral vestibular damage. In this latter study rotational frequencies up to 15 Hz were used, thus extending the range of rotational frequencies to match those produced during natural head movements. Taken together, these investigations show that changes in responses of vestibular afferents do not appear to play a significant role in supporting long-term adjustments of the VOR gain.

3.20.4.3 Changes in Neural Responses in the Adapted State: Vestibular Nuclei The second-order neurons in the rostral medial and ventral lateral subdivisions of the vestibular nuclei can be grouped into distinct classes based on idiosyncratic constellations of discharge properties in response to voluntary eye movements and passive whole-body rotations. Of these, two neuron classes contribute to the direct three-neuron arc that mediates the VOR, namely: (1) position-vestibular-pause (PVP) neurons, and (2) eye-head (EH), which are also called floccular target neurons (FTNs). 3.20.4.3.1

PVP neurons PVP neurons are thought to constitute most of the intermediate leg of the direct VOR pathway; they receive a strong monosynaptic connection from the ipsilateral semicircular canal afferents and project directly to the extraocular motor neurons (McCrea et al., 1987; Cullen et al., 1991; Scudder and Fuchs, 1992; Cullen and McCrea, 1993). These neurons derive their name from the signals they carry during head-restrained head and eye movement paradigms; their firing rate increases with contralaterally directed eye position; they are modulated in response to ipsilaterally directed head velocity during passive whole-body rotations; and they stop firing or pause during ipsilaterally directed saccades and vestibular quick phases. To address whether changes in the direct VOR pathway mediate motor learning, single-unit recordings were made from PVP neurons in monkeys before and after they had worn magnifying or

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minimizing spectacles (Lisberger and Miles, 1980, Lisberger et al., 1994a, b). After wearing these spectacles, head movements will evoke larger/smaller eye movements (i.e., an adapted VOR) relative to control conditions to facilitate stabile vision. Thus, it is important to differentiate changes in neuronal modulation that result from the altered movement from those that genuinely reflect changes in a neuron’s sensitivity to head movement. To explicitly address this concern, neuronal responses were characterized using a paradigm in which the monkey ‘cancels’ its VOR by tracking a target that moves with the head. The resulting vestibular stimulation does not lead to eye motion in the opposite direction to the head motion because trained subjects can accurately follow the target at frequencies < 1.5 Hz. Because the PVP responses to VOR cancellation were comparable before and after motor learning, it was concluded that the vestibular nerve synapse on the PVP neurons is not a primary site of plasticity during visually induced motor learning. Taken together these results have been taken as evidence that PVP neurons receive feedback signals that are related to the adapted eye movements. It is important to note, however, that cancellation of the VOR is largely accomplished via visual pathways that drive a pursuit signal (reviewed in Cullen and Roy, 2004). These pathways are of cerebellar origin and function to cancel the input from the vestibular nerve at the level of the vestibular nuclei. Because PVP neurons are sensitive to smooth pursuit eye movements as well as head velocity, it is important to note that the strength of PVP responses during VOR cancellation will not provide a completely unbiased estimate of their actual sensitivity to vestibular nerve inputs.

3.20.4.3.2

Floccular target neurons Integration of the results of more recent studies support the idea that changes occur in pursuit as well as VOR pathways after VOR learning (Miles et al., 1980a, b; Lisberger et al., 1994b; Blazquez et al., 2003, 2006). A subset of neurons in the rostral medial and ventral lateral subdivisions of the vestibular nuclei receive direct inhibitory projections from the floccular complex (Lisberger and Pavelko, 1988; Broussard and Lisberger, 1992; Lisberger et al., 1994a, b). These neurons are distinct from PVP neurons and are called floccular target neurons. Their responses largely correspond with those of a distinct physiological subclass of cells, termed

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eye-head (EH) neurons, which have been well characterized during eye and head movements in the head-restrained monkey (Tomlinson and Robinson, 1984; McFarland and Fuchs, 1992; Scudder and Fuchs, 1992; Cullen et al., 1993; McCrea et al., 1996; Chen-Huang and McCrea, 1999; Gdowski and McCrea, 1999, 2000; Gdowski et al., 2001; Roy and Cullen, 2003). EH neurons are the most significant premotor input to the extraocular motor neurons of the abducens nucleus during smooth pursuit eye movements (McFarland and Fuchs, 1992; Scudder and Fuchs, 1992; Cullen et al., 1993; Lisberger et al., 1994a, b). The primary characteristic of EH neurons is that they respond to eye and head movements in the same direction during horizontal smooth pursuit and cancellation of the VOR, respectively. Many EH

neurons receive monosynaptic projections from the ipsilateral vestibular nerve (Broussard and Lisberger, 1992; Scudder and Fuchs, 1992), as well as from the floccular complex. EH neurons that show increased firing for eye and head movements away from the side of recording (cEH neurons) can also send direct projections to extraocular motor neurons (Scudder and Fuchs, 1992). Thus, cEH neurons work together with PVP neurons to support the intermediate leg of the direct VOR pathways. Single-unit recordings, made from EH neurons in the brainstems of monkeys before and after wearing magnifying or minimizing spectacles, show that changes in the VOR gain are accompanied by corresponding changes in the head-velocity related modulation of FTNs during cancellation of the VOR (Figure 4, Lisberger et al., 1994b). These changes in response gain are more

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Figure 4 Responses of FTN (a,b) and PVP (c,d) neuron to rapid changes in head velocity after motor learning. Typical response are shown for ipsiversive head motion when the gain was high (a and c) and low (b and d). Upward deflections of the eye and head velocity traces indicate ipsiversive motion. On average the modulation of FTN neuron was significantly different for the two gain states (2.0 versus 0.8 sp/s per deg/s, respectively). In contrast, the modulation of PVP neurons was unchanged. From Lisberger SG, Pavelko TA, and Broussard DM (1994) Neural basis for motor learning in the vestibuloocular reflex of primates. I. Changes in the responses of brain stem neurons. J. Neurophysiol. 72: 928–953.

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marked for neurons that are activated by the contraversive eye during head-restrained pursuit (i.e., the cEH cells, which contribute to the direct VOR pathway). EH neurons are sensitive to orbital eye position, as well as smooth-pursuit eye movements and head movement. Thus, as discussed earlier in relation to PVP neurons, changes in an EH neuron’s modulation during the VOR or even during cancellation of the VOR do not provide an unbiased estimate of neuronal sensitivity to vestibular nerve inputs. Nevertheless, comparison of the results of the analyses of different groups of brainstem neurons during these conditions does indicate that VORrelated modulation of the cEH neurons is the most altered following motor learning. Furthermore, the responses of these neurons cannot be fully explained by the changes that are seen in the flocculus following learning. In particular their response latencies, unlike those of the floccular Purkinje cells, are appropriate to cause the earliest component of motor learning in the VOR (Lisberger et al., 1994a, b). More recently, the idea that changes at the level of the EH neurons underlie VOR motor learning in the horizontal VOR has been furthered by the finding that the responses of FTNs in the subdivisions of the vestibular nuclei that mediate the vertical VOR (i.e., the y group) are similarly modified during learning in the vertical VOR (Blazquez et al., 2005). 3.20.4.4 Changes in Neural Responses in the Adapted State: Flocculus and Ventral Paraflocculus Floccular Purkinje cells show both short-term and long-term changes in their responses following VOR learning (Miles et al., 1980a; Watanabe, 1984, 1985; Nagao, 1989; Lisberger, 1994; Raymond and Lisberger, 1996, Blazquez et al., 2003). Work by several laboratories, using different time courses of gain adaptation, demonstrated that changes in Purkinje cell responses are appropriate to induce VOR adaptation either over the course of hours (Watanabe, 1984, 1985; Raymond and Lisberger, 1997; Hirata and Highstein, 2001) or weeks (Miles et al., 1980a; Lisberger et al., 1994a; Blazquez et al., 2003). Because Purkinje cells, like neurons in the vestibular nuclei, are sensitive to eye as well as head movements, these results are difficult to interpret. VOR adaptation will alter the eye movements that are produced in response to head movement, and so it follows that

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changes in Purkinje cell responses can be a consequence of the altered eye movement-related inputs that are sent to the flocculus. A number of different approaches have been used in an effort to isolate the vestibular input to the Purkinje cells so that their head velocity sensitivity could be measured following VOR adaptation. First, as described earlier for the vestibular nuclei, neuronal responses were compared during cancellation of the VOR before and after VOR motor learning. Using this approach, changes in Purkinje cell modulation appeared to be in the wrong direction to support the current VOR gain state (Miles et al., 1980a; Lisberger et al., 1994a; Hirata and Highstein, 2001). Accordingly, this finding was originally used in support of the proposal that the floccular complex was not the site of plasticity in VOR motor learning, but instead that changes in the vestibular nuclei were responsible for VOR adaptation (i.e., see Miles et al., 1980a). More recently, it has been established that models of VOR learning that incorporate gain changes at the level of both the brainstem and cerebellum can account for the results of these singleunit recording experiments. In particular, the results of systems identification-based analyses, which incorporate the feedforward and feedback connectivity of the visual and vestibular pathways in the brainstem and floccular complex, indicate that Purkinje cells not only change their head velocity sensitivities, but also their eye position and eye velocity sensitivities after chronic learning (Blazquez et al., 2003). The resultant responses of these combined effects at the level of floccular Purkinje cells provide a modulation of the brainstem pathways (see earlier section titled ‘Changes in neuronal responses in the adapted state: vestibular afferents’) that is appropriate to support the new VOR gains.

3.20.5 Current Models of Long-Term VOR Modulation 3.20.5.1 Support for a Multiple-Site Hypothesis As reviewed earlier, evidence from single-unit recording experiments indicates that the site of VOR motor learning is not exclusively restricted to the floccular complex or the vestibular nuclei. Immediately following learning, changes in the simple and complex spike activity of Purkinje cells are appropriate to drive this learning in both the horizontal (Raymond and Lisberger, 1997) and vertical

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(Hirata and Highstein, 2001) systems. Moreover, the responses of floccular neurons (Miles et al., 1980a; Watanabe, 1984; Lisberger et al., 1994b; Partsalis et al., 1995a, b; Hirata and Highstein, 2001) as well as FTNs in the vestibular nuclei (Lisberger et al., 1994a; Blazquez et al., 2005) remain modified once a new VOR gain state has been firmly established. Analytical solutions of simple models of the brainstem and cerebellar pathways further indicate that gain changes at the levels of both the cerebellum and vestibular nuclei are required to ensure that the eye movements produced by both the visual tracking (pursuit and optokinetic) and VOR pathways remain accurate after VOR motor learning (Lisberger and Sejnowski, 1992; Lisberger et al., 1994a,b; Blazquez et al., 2003, 2006). The results of lesion studies have furthered the proposal that the site of VOR motor learning is not restricted to either the floccular complex or the vestibular nuclei. These studies provide strong evidence that the gain changes required for VOR adaptation are initially stored in the floccular complex and in turn drive the formation of long-term synaptic changes at the level of the vestibular nuclei such that long-term memory is chiefly consolidated in the brainstem rather than the cerebellum (reviewed in Broussard and Kassardjian, 2004). This process has been termed the transfer or consolidation hypothesis (Galiana, 1986; Peterson et al., 1991; Raymond and Lisberger, 1996; Broussard and Kassardjian, 2004). Consistent with this proposal is the finding that learned changes in VOR gain are completely abolished by inactivation of the floccular complex immediately following learning (McElligott et al., 1998; Nagao and Kitazawa, 2003), while inactivation of the floccular complex does not completely abolish long-term changes in VOR gain (Luebke and Robinson, 1994; Partsalis et al., 1995a; Broussard and Kassardjian, 2004; Shutoh et al., 2006). Behavioral and single-unit recording studies have provided further evidence for the proposal that memory storage is transferred from the cerebellum to the vestibular nuclei, but only in the long term. This is consistent with the recent observation that chronically acquired VOR gain changes are better retained than acutely acquired VOR gain changes (Kuki et al., 2004). In addition, the relationship between the head velocity sensitivity of floccular Purkinje neurons and VOR gain after learning differs following short-term versus long-term training (Figure 5; Hirata and Highstein, 2001; Blazquez et al., 2003). The cellular

mechanisms that are thought to mediate short-term versus long-term changes in VOR gain are considered in more detail in the section titled ‘Cellular mechanisms of VOR motor learning: evidence for LTD versus LTP.’ 3.20.5.2 The Role of the Flocculus versus Ventral Paraflocculus in VOR Learning In primates, the flocculus proper is defined as the four most medial lobules caudal to the posterolateral fissure. Adjacent to the fissure is a lobule that constitutes a transition zone termed the medial extension, which is then followed by the five to six more rostral lobules, which constitute the ventral paraflocculus. The ventral paraflocculus is particularly well developed in primates, and most singleunit recording experiments have focused on it rather than the flocculus proper. Selective lesions of these different portions of the floccular complex suggest differences in their relative contributions to the generation of smooth-pursuit eye movements and VOR adaptation (Rambold et al., 2002; Nagao and Kitazawa, 2003). Surgical or irreversible chemical lesions of the ventral paraflocculus results in deficits in both behaviors (Rambold et al., 2002). On the other hand, permanent bilateral lesions, which remove only the flocculus proper, do not produce major deficits in smooth pursuit or changes in gain after long-term VOR motor learning (Rambold et al., 2002). In contrast, acute bilateral inactivation of the flocculus proper immediately following VOR short-term adaptation impairs learned VOR gains (Nagao and Kitazawa, 2003; Shutoh et al., 2006). Taken together, these findings have led to the suggestion that the flocculus makes a greater contribution to the acquisition of VOR motor learning than to its long-term consolidation or retention.

3.20.6 Cellular Mechanisms of VOR Motor Learning: Evidence for LTD versus LTP 3.20.6.1 Cellular Mechanisms for VOR Motor Learning in the Flocculus As described earlier in the section titled ‘Current models of long-term VOR modulation,’ there is now general agreement that the gain changes required for VOR adaptation are initially stored in the floccular complex, and the modulation of the Purkinje cell response in turn drives the formation

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Figure 5 The effects of acute (top row) and chronic (bottom row) training on Purkinje cell responses during VOR for normal (yellow circles), versus low gain (red circles) and high gain (blue circles) adapted animals. Plots on the left show Purkinje cell response sensitivity during head rotation (i.e., (sp/s) per (deg/s)) as a function of VOR gain. Figures on the right are threedimensional representations where the modulation amplitude for each cell is the length of the line running flat along the circle. The phase of modulation is the degree of the circle, where zero degrees is in phase with head velocity. VOR gain is plotted along the vertical axis. Courtesy of Steve Highstein.

of long-term synaptic changes at the level of the vestibular nuclei. Much recent work has focused on the cellular mechanisms that underlie VOR motor leaning at the level of the flocculus and vestibular nuclei. The existence of long-term depression (LTD) at the Purkinje cell-parallel fiber synapse was first established by Ito et al. (1982) using electrophysiological techniques. Stimulation of the climbing fiber input to the flocculus reduced the strength of the Purkinje cell-parallel synapse when parallel fibers were simultaneously activated. Subsequent to Ito’s

original experiments, substantial additional evidence has accumulated in support of the proposal that cerebellar LTD plays a critical role in VOR motor learning. Inhibition of the signaling pathways that are required for induction of cerebellar LTD in normal animals prevents short-term motor learning in the VOR (Nagao and Ito, 1991; Li et al., 1995). Moreover, transgenic mice that express an inhibitor of protein kinase C, an enzyme that is involved in LTD, cannot adapt their VOR gain during shortterm motor learning (de Zeeuw et al., 1998; van Alphen et al., 2002). Similarly, transgenic mice

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lacking the 2 subunit of the glutamate receptor (GluR2), which is required for LTD, do not show VOR motor learning (Katoh et al., 2005). 3.20.6.2 Cellular Mechanisms for VOR Motor Learning in the Vestibular Nuclei The results of recent in vitro experiments have provided insights into the cellular mechanisms that underlie VOR motor learning at the level of the vestibular nuclei. High-frequency stimulation of vestibular nerve can evoke both LTD and long-term potentiation (LTP) in the vestibular nuclei (Caria et al., 1996, 2001; Grassi et al., 2001). The induction of either form of synaptic plasticity requires the activation of N-methyl-D-aspartate (NMDA) (Capocchi et al., 1992; Grassi et al., 1995) as well as metabotropic glutamate (Grassi et al., 1998, 2002, 2005) receptors. Interestingly, an animal’s past visual or vestibular experience can alter the mechanisms that underlie cellular synaptic plasticity in the vestibular nucleus. For example, neurons in the ventral vestibular nuclei normally exhibit a shift from LTD to LTP during development (Grassi et al., 2004). This shift does not occur in animals that have experienced early visual deprivation or limited vestibular stimulation. Moreover, lack of visual input early in maturation alters the balance of mGluR1 versus mGluR5 receptors (Puyal et al., 2003). Accordingly, it is possible that the presence of visual signals such as retinal slip error (Figure 3) might induce changes in the strength of vestibular afferent–vestibular nuclei synapses to facilitate VOR motor learning. 3.20.6.3 Cellular Mechanisms Underlying Increases versus Decreases in VOR Gain

1987; Luebke and Robinson, 1994; Pastor et al., 1994; Partsalis et al., 1995b; McElligott et al., 1998). Ito’s original model of VOR motor learning (1972) assumed that increases and decreases in VOR gain are governed by a single synaptic plasticity mechanism in the cerebellum, namely LTD. Most recently, however, the results of electrophysiological experiments that have shown that LTP as well as LTD can be induced at parallel fiber–Purkinje cell synapses (Coesmans et al., 2004; Lev-Ram et al., 2003). Thus, it has been suggested that cerebellar LTD at the parallel fiber–Purkinje cell synapse mediates increases in VOR gain, whereas LTP of the same synapse mediates decreases in VOR gain (Figure 6; Boyden and Raymond, 2003).

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The results of behavioral analysis of VOR learning provide support for the idea that learned increases versus decreases in VOR gain are achieved by means of different plasticity mechanisms. Following learning, increases in VOR gain decay far more rapidly (Miles and Eighmy, 1980) and can be reversed more easily (Boyden and Raymond, 2003) than decreases in VOR gain. This has been furthered by recent studies that have addressed the underlying mechanisms of these differences using genetic manipulations and pharmacological approaches (reviewed in Boyden et al., 2004). Increases and decreases in VOR gain appear to be mediated by plastic changes in common locations because cerebellar lesions have comparable effects in both directions (Michnovicz and Bennett,

Figure 6 A model that explains differences in gain-up versus gain-down learning in the VOR. Purkinje cells carry only information about the required direction of learning for lowfrequency training, whereas climbing fibers carry instructive signals during both high- and low-frequency training. As a result, during low-frequency training Purkinje cells induce plasticity (open lightning bolts) in the vestibular nuclei. In contrast, climbing fiber activity in the cerebellum (filled lightning bolts) also contributes to plasticity during highfrequency training. Learning in the cerebellum that requires LTD could increase VOR gain (red), whereas that which requires LTP could decrease VOR gain (blue). Abbreviations: cf, climbing fibers; gc, granule cells; io, inferior olive; pf, parallel fibers; Pk, Purkinje cells; mvn, medial vestibular nuclei. From Boyden ES, Katoh A, Pyle JL, Chatila TA, Tsien RW, and Raymond JL (2006) Selective engagement of plasticity mechanisms for motor memory storage. Neuron 51: 823–824.

Procedural Learning: VOR

3.20.6.4 Cellular Mechanisms: Open Questions Although both LTD and LTP can also be induced in the vestibular nuclei, it is unclear whether the firing of a Purkinje cell induces depression and/or potentiation at these synapses (Babalian and Vidal, 2000). When LTD is induced in floccular Purkinje cells in an isolated whole-brain preparation, traces of flocculus-dependent plasticity cannot be detected in the FTNs within vestibular nuclei (Babalian and Vidal, 2000). Moreover, recent studies in transgenic mice have further shown that LTD is not required for all forms of VOR plasticity. As discussed earlier in the section titled ‘Cellular mechanisms for VOR motor learning in the flocculus,’ when LTD is blocked via inhibition of protein kinase C, neither short- nor long-term learning can be induced by visual-vestibular mismatch training. In contrast, vestibular compensation following unilateral damage to the vestibular sensory organs is not altered by the absence of LTD (Faulstich et al., 2006). Thus it appears that non-LTD-dependant pathways can mediate compensation. One possibility is that the synaptic plasticity of excitatory mossy fiber inputs to cerebellar nuclear neurons (Pugh and Raman, 2006; Zhang and Linden, 2006) contributes to nonLTD-dependent motor learning. Moreover, noncerebellar pathways can make a significant contribution to long-term changes in VOR gain following vestibular compensation (Cullen et al., 2006). Further studies will be required to fully understand the mechanisms that underlie VOR plasticity, particularly for learning that occurs following vestibular damage.

3.20.7 Context-Dependent VOR Motor Learning 3.20.7.1 Stimulus-Dependent VOR Motor Learning: Behavior VOR adaptation can be specific for the stimulus parameters that are used during the induction of motor learning. Numerous studies have established that the amount of adaptive gain change exhibited by the angular VOR is related to the frequency of head rotation that was used to induce motor learning during training (Lisberger et al., 1983; Raymond and Lisberger, 1996; Kramer et al., 1998). The VOR shows the greatest changes at the adapting frequency, and gain changes induced by adaptation at higher

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frequencies are less frequency specific (i.e., more generalized) than those induced using lower frequencies. This idea has been furthered by the demonstration that the dominant linear component of the VOR response and a frequency-dependent nonlinearity (a rise in gain with increasing velocity of rotation at frequencies more than 2 Hz), which is observed only at higher frequencies (Minor et al., 1999) can be differentially adapted (Clendaniel et al., 2002). The nonlinear component of the VOR was only modified by the training protocols that evoked this component of the response. The mechanism underlying these frequencydependent differences in generalization of VOR adaptation are not yet well understood but several possibilities (see discussion by Boyden et al., 2004) can be reconciled with the results of behavioral investigations. On the one hand it is possible that a single plasticity mechanism underlies this frequencyspecific adaptation. This could be the case if most neurons in a given structure (i.e., floccular Purkinje cells and/or vestibular nuclei neurons) respond to high-frequency stimulation, but only a subset of these are also sensitive to lower frequencies of stimulation. In this condition, more generalized plasticity would be induced in the circuit by higher-frequency stimulation because it would recruit most neurons. On the other hand, it is tempting to consider the alternative possibility that the dependence of generalization on training frequency results from the existence of two or more distinct plasticity mechanisms. Evidence that blocking LTD alters the ability to adapt to high- versus low-frequency training protocols is consistent with the latter idea. Knockout mice that lack a protein kinase (CaMKIV) required for LTD (Boyden et al., 2006) show that VOR learning induced by higher-frequency (1 Hz) training is impaired, whereas adaptation induced by lowerfrequency stimulation is not altered (0.5 Hz). The results further suggest that increases in gain induced with high-frequency training are mediated by different cellular/molecular plasticity mechanisms than those recruited by decreases in gain or increases in gain induced with low-frequency training. Findings from previous single-unit recording from floccular Purkinje cells provide additional support that different mechanisms guide learning for high- versus lowfrequency training (Raymond and Lisberger, 1998). Climbing-fiber responses contained the information required to guide learning only at high-stimulus frequencies, whereas at lower frequencies both

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climbing-fiber and simple-spike signals contained the information required to appropriately guide learning. This has led to the proposal that changes in the cerebellum (i.e., changes in the efficacy of the parallel fiber Purkinje cell synapse) specifically induces VOR gain changes at higher frequencies, whereas changes at the level of the vestibular nuclei (driven by the simple spike output of Purkinje cells) can induce gain changes during low-frequency training. 3.20.7.2 Stimulus-Dependent VOR Motor Learning: Neuronal Pathways The VOR is capable of remarkable adjustments in response to environmental challenges that include lesions of the vestibular system as well as the use of magnifying or minimizing optical lenses. Immediately following unilateral labyrinthectomy, there is a marked asymmetry in gain characterized by diminished responses to rotations toward the lesioned side. Although the VOR shows nearly complete functional recovery for head rotations at lower frequencies (<4 Hz) and velocities (<50 deg/s) the VOR never fully compensates in response to rotations with higher frequencies and/or velocities (reviewed in Sadeghi et al., 2006). Previous work in squirrel monkeys has demonstrated the presence of linear and nonlinear components to the horizontal vestibulo–ocular reflex (VOR). The nonlinear component is a velocitydependent gain enhancement (see earlier discussion in the section titled ‘Stimulus-dependent VOR motor learning: behavior’). In normal squirrel monkeys, the nonlinear pathway makes only a small (10–15%) contribution to the overall VOR response. The influence of this pathway, however, increases significantly following adaptation to unilateral vestibular damage or motor learning magnifying spectacles, suggesting it plays an important role in VOR adaptation and compensation (Lasker et al., 1999, 2000). Recent work provides support for this idea in old world monkeys and humans (Della Santina et al., 2001; Sadeghi et al., 2006). Combined in vivo/in vitro studies have shown that neurons in the vestibular nuclei can be roughly separated into two groups (Type A and B) based on the shape of their action potentials and the subsequent after hyperpolarizations (Serafin et al., 1991a, b). Analysis of the intrinsic membrane dynamics of each cell class suggests that Type B neurons function as active filters, which promote high-frequency responses, whereas Type A neurons behave more

like low-pass filters (Ris et al., 2001; Sekirnjak and du Lac, 2002; Beraneck et al., 2003). Thus, it has been proposed that Type A and Type B neurons can be considered channels for encoding low- and highfrequency signals, respectively (Av-Ron and Vidal, 1999; Ris et al., 2001). Interestingly, the responses of Type A and B neurons resemble the dynamics of the linear (tonic) and nonlinear (phasic) VOR pathways, respectively, described by Minor and colleagues (1999). In addition, some Type B neurons preferentially receive inputs from the flocculus (Babalian and Vidal, 2000; Sekirnjak et al., 2002). Thus, the Type B cells that have been described in in vitro studies correspond to the FTN/EH neurons that have been shown to play an important role in lens-induced adaptation in in vivo studies (see discussion earlier in the section titled ‘Changes in neural responses in the adapted state: vestibular afferents’). Taken together, these findings provide support for the idea that neurons with more phasic membrane properties play the principal role in mediating vestibular compensation and adaptation at the level of the vestibular nuclei. 3.20.7.3 Context-Specific Changes in VOR Gain A number of recent studies provide firm evidence that subjects can store more than one VOR gain state, where each state is associated with a particular context. Eye position, vergence angle and otolith signals (i.e., head orientation) have all been shown to provide cues that can be used for inducing contextually dependent changes in VOR gain. Shelhamer and colleagues (1992) showed that when the angular VOR was adapted using magnifying and minimizing prisms with subjects’ eyes looking up and down, respectively, the gain of the VOR following the adaptation was consistently reduced or increased when subjects looked downward or upward. Comparable results were shown for the translational VOR by the same group (Patel et al., 1998). Similarly, the angular VOR can be trained to store two different gain states by training that requires different gains for two vergence angles (i.e., diverged versus converged conditions; Lewis et al., 2003). The adapted VOR is characterized by different gain states, which are immediately accessed in a vergence specific manner that corresponds to the training context. Similarly, several studies have shown that static otolith signals can provide strong contextual cues for gating the expression of different VOR gain states.

Procedural Learning: VOR

When the VOR is adapted with the head in a specific orientation relative to gravity, gain changes following adaptation of the angular VOR (Baker et al., 1987; Tiliket et al., 1993; Yakushin et al., 2000) and translational VOR (Shelhamer et al., 2002) are maximal when the head position is in the same position in which the gain had been adapted. These VOR gain changes are stored in a manner that is linked to the context of the head orientation in which changes were induced and fall off to zero when the head is in the opposite position (Figure 7; Yakushin et al., 2005). Gravity-specific adaptation of the VOR, like vergence-specific adaptation, can also be adapted to so that the VOR is adapted to two or even three specific gain states, each of which will be optimal for a

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different specific head position (e.g., Shelhamer et al., 2002, Xiang et al., 2006). The context-specific VOR adaptation described appears to be strongly associated with the specifics of the stimulus parameters that are used during VOR adaptation (e.g., frequency of stimulation or eye movements that are induced during the training, see the section titled ‘Stimulus-dependent VOR motor learning: behavior’). For example, the context-specific adaptation of translational VOR is greatest for head movement stimuli that are similar to those used during training (Shelhamer and Zee, 2003), and this frequency dependency is even more striking than for animals trained to a single gain state (Shelhamer et al., 2000). Other recent studies have

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shown that motor learning can be specific to the particular combination of head motion and evoked eye movement that occurred during training. For example, when one eye is aligned with direction of head movement during adaptation of the translational VOR, it will remain motionless during training (Zhou et al., 2003). In this condition, VOR adaptation is only expressed in the eye that moved during the training.

3.20.8 Conclusions The results of recent behavioral, single-unit recording and lesion studies have established that VOR motor learning induced by visual-vestibular discrepancy passes through distinct stages. Synaptic changes in the floccular complex underlie the initial induction of VOR adaptation. These changes, in turn, drive the formation of long-term synaptic changes at the level of the vestibular nuclei such that long-term memory is, for the most part, consolidated in the brainstem rather than in the cerebellum. Significant progress has also been made toward understanding the cellular mechanisms that underlie VOR adaptation in both the floccular complex and vestibular nuclei. Experiments in in vitro and isolated brain preparations as well as transgenic animals have shown that LTD and LTP can be induced at the parallel fiber–Purkinje cell as well as vestibular afferent–vestibular nuclei synapses. This has been furthered by recent studies that provide support of the idea that different cellular mechanisms induce changes at the parallel fiber–Purkinje cell synapse to induce increases versus decreases in VOR gain. Further investigation will be needed to address many important open questions. For example, we do not yet understand the mechanisms that ultimately drive the formation of long-term synaptic changes at the level of the vestibular nuclei. In addition, the mechanisms that underlie another form of VOR motor learning, namely compensation of the VOR following vestibular damage, are not fully understood. Although we have gained considerable insights into the neural mechanisms that induce and encode gain changes in the VOR circuitry to support its adaptation and compensation, recent findings by several laboratories have highlighted another key feature of VOR adaptation. Current vergence angle or eye position, otolith-derived signals (i.e., head position), as well as attributes of the head velocity stimulus itself provide cues that can be used for

inducing contextually dependent changes in VOR gain. This implies that, at a given instant in time, more than one VOR gain state is stored, and that the particular context will determine which state is retrieved. Context-specific adaptation has similarly been demonstrated in other motor systems, for example, during ocular pursuit (Takagi et al., 2000), as well as reaching (Lewis and Tamargo, 2001), pointing (Welch et al., 1993), and throwing (Martin et al., 1996) movements. The ability to retrieve motor memories in a context-dependent manner is important for everyday activities. For example, during head rotation, the eyes translate as well as rotate relative to space because they cannot both be perfectly aligned with the axis of rotation. Consequently, a larger VOR gain is necessary to stabilize a near than a far earthfixed target as a result of the differences in the translation of the target relative to the eyes. Thus, vergence-specific adaptation of the angular VOR is required to ensure gaze stability over a wide range of viewing conditions. Similarly, people who wear bifocal spectacles require a different VOR gain state for each lens magnification, each of which could be retrieved on the basis of current vertical eye position. It remains a significant challenge to understand the mechanisms that underlie context-specific adaptation; nevertheless, the relative simplicity of the vestibular system and the pathways that mediate the VOR make it an excellent model system for bridging the gap between brain and behavior.

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