A tale of two species: Neural integration in zebrafish and monkeys

Selection of a model organism creates tension between competing constraints. The recent explosion of modern molecular techniques has revolutionized the analysis of neural systems in organisms that are amenable to genetic techniques. Yet, the non-human primate remains the gold-standard for the analysis of the neural basis of behavior, and as a bridge to the operation of the human brain. The challenge is to generalize across species in a way that exposes the operation of circuits as well as the relationship of circuits to behavior. Eye movements provide an opportunity to cross the bridge from mechanism to behavior through research on diverse species. Here, we review experiments and computational studies on a circuit function called "neural integration" that occurs in the brainstems of larval zebrafish, primates, and species "in between". We show that analysis of circuit structure using modern molecular and imaging approaches in zebrafish has remarkable explanatory power for details of the responses of integrator neurons in the monkey. The combination of research from the two species has led to a much stronger hypothesis for the implementation of the neural integrator than could have been achieved using either species alone.

Internal models of eye movement in the floccular complex of the monkey cerebellum

Internal models are a key feature of most modern theories of motor control. Yet, it has been challenging to localize internal models in the brain, or to demonstrate that they are more than a metaphor. In the present review, I consider a large body of data on the cerebellar floccular complex, asking whether floccular output has features that would be expected of the output from internal models. I argue that the simple spike firing rates of a single group of floccular Purkinje cells could reflect the output of three different internal models. (1) An eye velocity positive feedback pathway through the floccular complex provides neural inertia for smooth pursuit eye movements, and appears to operate as a model of the inertia of real-world objects. (2) The floccular complex processes and combines input signals so that the dynamics of its average simple spike output are appropriate for the dynamics of the downstream brainstem circuits and eyeball. If we consider the brainstem circuits and eyeball as a more broadly conceived "oculomotor plant," then the output from the floccular complex could be the manifestation of an inverse model of "plant" dynamics. (3) Floccular output reflects an internal model of the physics of the orbit where head and eye motion sum to produce gaze motion. The effects of learning on floccular output suggest that it is modeling the interaction of the visually-guided and vestibular-driven components of eye and gaze motion. Perhaps the insights from studying oculomotor control provide groundwork to guide the analysis of internal models for a wide variety of cerebellar behaviors.

Partial ablations of the flocculus and ventral paraflocculus in monkeys cause linked deficits in smooth pursuit eye movements and adaptive modification of the VOR

The vestibuloocular reflex (VOR) generates compensatory eye movements to stabilize visual images on the retina during head movements. The amplitude of the reflex is calibrated continuously throughout life and undergoes adaptation, also called motor learning, when head movements are persistently associated with image motion. Although the floccular-complex of the cerebellum is necessary for VOR adaptation, it is not known whether this function is localized in its anterior or posterior portions, which comprise the ventral paraflocculus and flocculus, respectively. The present paper reports the effects of partial lesions of the floccular-complex in five macaque monkeys, made either surgically or with stereotaxic injection of 3-nitropropionic acid (3-NP). Before and after the lesions, smooth pursuit eye movements were tested during sinusoidal and step-ramp target motion. Cancellation of the VOR was tested by moving a target exactly with the monkey during sinusoidal head rotation. The control VOR was tested during sinusoidal head rotation in the dark and during 30 degrees/s pulses of head velocity. VOR adaptation was studied by having the monkeys wear x2 or x0.25 optics for 4-7 days. In two monkeys, bilateral lesions removed all of the flocculus except for parts of folia 1 and 2 but did not produce any deficits in smooth pursuit, VOR adaptation, or VOR cancellation. We conclude that the flocculus alone probably is not necessary for either pursuit or VOR learning. In two monkeys, unilateral lesions including a large fraction of the ventral paraflocculus produced small deficits in horizontal and vertical smooth pursuit, and mild impairments of VOR adaptation and VOR cancellation. We conclude that the ventral paraflocculus contributes to both behaviors. In one monkey, a bilateral lesion of the flocculus and ventral paraflocculus produced severe deficits smooth pursuit and VOR cancellation, and a complete loss of VOR adaptation. Considering all five cases together, there was a strong correlation between the size of the deficits in VOR learning and pursuit. We found the strongest correlation between the behavior deficits and the size of the lesion of the ventral paraflocculus, a weaker but significant correlation for the full floccular complex, and no correlation with the size of the lesion of the flocculus. We conclude that 1) lesions of the floccular complex cause linked deficits in smooth pursuit and VOR adaptation, and 2) the relevant portions of the structure are primarily in the ventral paraflocculus, although the flocculus may participate.

Shifts in the population response in the middle temporal visual area parallel perceptual and motor illusions produced by apparent motion

We recorded behavioral, perceptual, and neural responses to targets that provided apparent visual motion consisting of a sequence of stationary flashes. Increasing the flash separation degrades the quality of motion, but for some separations evoked larger smooth pursuit responses from both humans and monkeys than did smooth motion. The same flash separations also produced an increase in perceived speed in humans. Recordings from single neurons in the middle temporal visual area (MT) of awake monkeys revealed a potential basis for the illusion in the population response. Apparent motion produced diminished neural responses relative to smooth motion. However, neurons with slow preferred speeds were more affected than were those with fast preferred speeds. Increasing the flash separation thus caused the population response to become diminished in amplitude and to shift so that the most active neurons had higher preferred speeds. The entire constellation of effects of apparent motion on the magnitude and latency of the initial pursuit response was accounted for if the MT population response was decoded by (1) creating an opponent motion signal for each neuron by treating its preferred and opposite direction responses as those of a pair of oppositely tuned neurons and (2) computing the vector average of these opponent motion signals. Other ways of decoding the population response recorded in MT failed to account for one or more aspects of behavior. We conclude that the effects of apparent motion on both pursuit and perception can be accounted for if target speed is estimated from the MT population response by a neural computation that implements a vector average based on opponent motion.

Experimental and computational analysis of monkey smooth pursuit eye movements

Smooth pursuit eye movements are guided by visual feedback and are surprisingly accurate despite the time delay between visual input and motor output. Previous models have reproduced the accuracy of pursuit either by using elaborate visual signals or by adding sources of motor feedback. Our goal was to constrain what types of signals drive pursuit by obtaining data that would discriminate between these two modeling approaches, represented by the "image motion model" and the "tachometer feedback" model. Our first set of experiments probed the visual properties of pursuit with brief square-pulse and sine-wave perturbations of target velocity. Responses to pulse perturbations increased almost linearly with pulse amplitude, while responses to sine wave perturbations showed strong saturation with increasing stimulus amplitude. The response to sine wave perturbations was strongly dependent on the baseline image velocity at the time of the perturbation. Responses were much smaller if baseline image velocity was naturally large, or was artificially increased by superimposing sine waves on pulse perturbations. The image motion model, but not the tachometer feedback model, could reproduce these features of pursuit. We used a revision of the image motion model that was, like the original, sensitive to both image velocity and image acceleration. Due to a saturating nonlinearity, the sensitivity to image acceleration declined with increasing image velocity. Inclusion of this nonlinearity was motivated by our experimental results, was critical in accounting for the responses to perturbations, and provided an explanation for the unexpected stability of pursuit in the presence of perturbations near the resonant frequency. As an emergent property, the revised image motion model was able to reproduce the frequency and damping of oscillations recorded during artificial feedback delays. Our second set of experiments replicated prior recordings of pursuit responses to multiple-cycle sine wave perturbations, presented over a range of frequencies. The image motion model was able to reproduce the responses to sine wave perturbations across all frequencies, while the tachometer feedback model failed at high frequencies. These failures resulted from the absence of image acceleration signals in the tachometer model. We conclude that visual signals related to image acceleration are important in driving pursuit eye movements and that the nonlinearity of these signals provides stability. Smooth pursuit thus illustrates that a plausible neural strategy for combating natural delays in sensory feedback is to employ information about the derivative of the sensory input.

Reconstruction of target speed for the guidance of pursuit eye movements

We studied how object speed is reconstructed from the responses of motion-selective cells for the generation of a behavior that is tightly linked to the speed of visual motion. In theory, the speed of an object could be estimated either from the speed tuning of the active population of motion-selective cells or from the rate of displacement of activation across the cortical map of visual space. We measured the pursuit eye movements evoked by stimuli containing two conflicting motion components: a local component designed to excite motion-selective cells with a particular speed tuning and a displacement component designed to excite cells with a sequence of spatial receptive fields. Pursuit eye movements were driven primarily by the local-motion component and were affected to only a small degree by the rate of target displacement across visual space. Extracellular single-unit recordings using the same stimuli revealed that the responses of cells in the middle temporal visual area (MT) depended primarily on the local-motion component but were influenced by the displacement component to the same degree as were pursuit eye movements. We conclude that the initiation of pursuit is consistent with a reconstruction of target speed based on the speed tuning of the active population of MT cells.

Linked target selection for saccadic and smooth pursuit eye movements

In natural situations, motor activity must often choose a single target when multiple distractors are present. The present paper asks how primate smooth pursuit eye movements choose targets, by analysis of a natural target-selection task. Monkeys tracked two targets that started 1.5 degrees eccentric and moved in different directions (up, right, down, and left) toward the position of fixation. As expected from previous results, the smooth pursuit before the first saccade reflected a vector average of the responses to the two target motions individually. However, post-saccadic smooth eye velocity showed enhancement that was spatially selective for the motion at the endpoint of the saccade. If the saccade endpoint was close to one of the two targets, creating a targeting saccade, then pursuit was selectively enhanced for the visual motion of that target and suppressed for the other target. If the endpoint landed between the two targets, creating an averaging saccade, then post-saccadic smooth eye velocity also reflected a vector average of the two target motions. Saccades with latencies >200 msec were almost always targeting saccades. However, pursuit did not transition from vector-averaging to target-selecting until the occurrence of a saccade, even when saccade latencies were >300 msec. Thus, our data demonstrate that post-saccadic enhancement of pursuit is spatially selective and that noncued target selection for pursuit is time-locked to the occurrence of a saccade. This raises the possibility that the motor commands for saccades play a causal role, not only in enhancing visuomotor transmission for pursuit but also in choosing a target for pursuit.

Regulation of the gain of visually guided smooth-pursuit eye movements by frontal cortex

In studies of the neural mechanisms giving rise to behaviour, changes in the neural and behavioural responses produced by a given stimulus have been widely reported. This 'gain control' can boost the responses to sensory inputs that are particularly relevant, select among reflexes for execution by motoneurons or emphasize specific movement targets. Gain control is also an integral part of the smooth-pursuit eye movement system. One signature of gain control is that a brief perturbation of a stationary target during fixation causes tiny eye movements, whereas the same perturbation of a moving target during the active state of accurate pursuit causes large responses. Here we show that electrical stimulation of the smooth-pursuit eye movement region in the arcuate sulcus of the frontal lobe ('the frontal pursuit area', FPA) mimics the active state of pursuit. Such stimulation enhances the response to a brief perturbation of target motion, regardless of the direction of motion. We postulate that the FPA sets the gain of pursuit, thereby participating in target selection for pursuit.

Changes in the responses of Purkinje cells in the floccular complex of monkeys after motor learning in smooth pursuit eye movements

We followed simple- and complex-spike firing of Purkinje cells (PCs) in the floccular complex of the cerebellum through learned modifications of the pursuit eye movements of two monkeys. Learning was induced by double steps of target speed in which initially stationary targets move at a "learning" speed for 100 ms and then change to either a higher or lower speed in the same direction. In randomly interleaved control trials, targets moved at the learning speed in the opposite direction. When the learning direction was the ON direction for simple-spike responses, learning was associated with statistically significant changes in simple-spike firing for 10 of 32 PCs. Of the 10 PCs that showed significant expressions of learning, 8 showed changes in simple-spike output in the expected direction: increased or decreased firing when eye acceleration increased or decreased through learning. There were no statistically significant changes in simple-spike responses or eye acceleration during pursuit in the control direction. When the learning direction was in the OFF direction for simple-spike responses, none of 15 PCs showed significant correlates of learning. Although changes in simple-spike firing were recorded in only a subset of PCs, analysis of the population response showed that the same relationship between population firing and eye acceleration obtained before and after learning. Thus learning is associated with changes that render the modified population response appropriate to drive the changed behavior. To analyze complex-spike firing during learning we correlated complex-spike firing in the second, third, and fourth 100 ms after the onset of target motion with the retinal image motion in the previous 100 ms. Data were largely consistent with previous evidence that image motion drives complex spikes with a direction selectivity opposite that for simple spikes. Comparison of complex-spike responses at different times after the onset of control and learning target motions in the learning direction implied that complex spikes could guide learning during decreases but not increases in eye acceleration. Learning caused increases or decreases in the sensitivity of complex spikes to image motion in parallel with changes in eye acceleration. Complex-spike responses were similar in all PCs, including many in which learning did not modify simple-spike responses. Our data do not disprove current theories of cerebellar learning but suggest that these theories would have to be modified to account for simple- and complex-spike firing of floccular Purkinje cells reported here.

Context-dependent smooth eye movements evoked by stationary visual stimuli in trained monkeys

The appearance of a stationary but irrelevant cue triggers a smooth eye movement away from the position of the cue in monkeys that have been trained extensively to smoothly track the motion of moving targets while not making saccades to the stationary cue. We have analyzed the parameters that regulate the size of the cue-evoked smooth eye movement and examined whether presentation of the cue changes the initiation of pursuit for subsequent steps of target velocity. Cues evoked smooth eye movements in blocks of target motions that required smooth pursuit to moving targets, but evoked much smaller smooth eye movements in blocks that required saccades to stationary targets. The direction of the cue-evoked eye movement was always opposite to the position of the cue and did not depend on whether subsequent target motion was toward or away from the position of fixation. The latency of the cue-evoked smooth eye movement was near 100 ms and was slightly longer than the latency of pursuit for target motion away from the position of fixation. The size of the cue-evoked smooth eye movement was as large as 10 degrees /s and decreased as functions of the eccentricity of the cue and the illumination of the experimental room. To study the initiation of pursuit in the wake of the cues, we used bilateral cues at equal eccentricities to the right and left of the position of fixation. These evoked smaller eye velocities that were consistent with vector averaging of the responses to each cue. In the wake of bilateral cues, the initiation of pursuit was enhanced for target motion away from the position of fixation, but not for target motion toward the position of fixation. We suggest that the cue-evoked smooth eye movement is related to a previously postulated on-line gain control for pursuit, and that it is a side-effect of sudden activation of the gain-controlling element.

Apparent motion produces multiple deficits in visually guided smooth pursuit eye movements of monkeys

We used apparent motion targets to explore how degraded visual motion alters smooth pursuit eye movements. Apparent motion targets consisted of brief stationary flashes with a spatial separation (Deltax), temporal separation (Deltat), and apparent target velocity equal to Deltax/Deltat. Changes in pursuit initiation were readily observed when holding target velocity constant and increasing the flash separation. As flash separation increased, the first deficit observed was an increase in the latency to peak eye acceleration. Also seen was a paradoxical increase in initial eye acceleration. Further increases in the flash separation produced larger increases in latency and resulted in decreased eye acceleration. By varying target velocity, we were able to discern that the visual inputs driving pursuit initiation show both temporal and spatial limits. For target velocities above 4-8 degrees /s, deficits in the initiation of pursuit were seen when Deltax exceeded 0.2-0.5 degrees, even when Deltat was small. For target velocities below 4-8 degrees /s, deficits appeared when Deltat exceeded 32-64 ms, even when Deltax was small. Further experiments were designed to determine whether the spatial limit varied as retinal and extra-retinal factors changed. Varying the initial retinal position of the target for motion at 18 degrees /s revealed that the spatial limit increased as a function of retinal eccentricity. We then employed targets that increased velocity twice, once from fixation and again during pursuit. These experiments revealed that, as expected, the spatial limit is expressed in terms of the flash separation on the retina. The spatial limit is uninfluenced by either eye velocity or the absolute velocity of the target. These experiments also demonstrate that "initiation" deficits can be observed during ongoing pursuit, and are thus not deficits in initiation per se. We conclude that such deficits result from degradation of the retino-centric motion signals that drive pursuit eye acceleration. For large flash separations, we also observed deficits in the maintenance of pursuit: sustained eye velocity failed to match the constant apparent target velocity. Deficits in the maintenance of pursuit depended on both target velocity and Deltat and did not result simply from a failure of degraded image motion signals to drive eye acceleration. We argue that such deficits result from a low gain in the eye velocity memory that normally supports the maintenance of pursuit. This low gain may appear because visual inputs are so degraded that the transition from fixation to tracking is incomplete.

Vector averaging occurs downstream from learning in smooth pursuit eye movements of monkeys

How are sensory-motor transformations organized in a cortical motor system? In general, sensory information is transformed through a variety of signal processing operations in the context of distinct coordinate frameworks. We studied the interaction of two distinct operations in pursuit eye movements, learning and vector-averaging, to gain insight into their underlying coordinate frameworks and their sequence in sensory-motor processing. Learning was induced in the initiation of pursuit eye movements by targets that moved initially at one speed for 100 msec and then increased or decreased to a sustained final speed. Vector averaging was studied by comparing the initial eye acceleration evoked by the simultaneous motion of two targets with that evoked by each target singly. Learning caused specific effects on the direction of the vector-averaged responses to two-target stimuli that included one target moving in the direction used to induce learning. Learned increases or decreases in eye acceleration caused the direction of the responses to two-targets to rotate toward or away from the learning direction. Learning also caused nonspecific changes in the responses to two-target stimuli. After any learning protocol, two-target responses usually became smaller, and their directions rotated away from the axis of the target motion used for learning. Quantitative analysis showed that the specific effects of learning were predicted most closely by a model in which vector averaging occurs downstream from the site(s) of learning. We suggest that the pursuit system creates parallel commands for potential movements to each of the targets in two-target stimuli, and that learning occurs in the coordinates of the potential movements.

Visual motion analysis for pursuit eye movements in area MT of macaque monkeys

We asked whether the dynamics of target motion are represented in visual area MT and how information about image velocity and acceleration might be extracted from the population responses in area MT for use in motor control. The time course of MT neuron responses was recorded in anesthetized macaque monkeys during target motions that covered the range of dynamics normally seen during smooth pursuit eye movements. When the target motion provided steps of target speed, MT neurons showed a continuum from purely tonic responses to those with large transient pulses of firing at the onset of motion. Cells with large transient responses for steps of target speed also had larger responses for smooth accelerations than for decelerations through the same range of target speeds. Condition-test experiments with pairs of 64 msec pulses of target speed revealed response attenuation at short interpulse intervals in cells with large transient responses. For sinusoidal modulation of target speed, MT neuron responses were strongly modulated for frequencies up to, but not higher than, 8 Hz. The phase of the responses was consistent with a 90 msec time delay between target velocity and firing rate. We created a model that reproduced the dynamic responses of MT cells using divisive gain control, used the model to visualize the population response in MT to individual stimuli, and devised weighted-averaging computations to reconstruct target speed and acceleration from the population response. Target speed could be reconstructed if each neuron's output was weighted according to its preferred speed. Target acceleration could be reconstructed if each neuron's output was weighted according to the product of preferred speed and a measure of the size of its transient response.

Neural learning rules for the vestibulo-ocular reflex

Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies from 0.5 to 10 Hz. A comparison of simple-spike and vestibular signals contained the information required to guide learning only at low stimulus frequencies, and a comparison of climbing-fiber and simple-spike signals contained the information required to guide learning only at high stimulus frequencies. Learning could be guided by comparison of climbing-fiber and vestibular signals at all stimulus frequencies tested, but only if climbing fiber responses were compared with the vestibular signals present 100 msec earlier. Computational analysis demonstrated that this conclusion is valid even if there is a broad range of vestibular signals at the site of plasticity. Simulations also indicated that the comparison of vestibular and climbing-fiber signals across the 100 msec delay must be implemented by a subcellular "eligibility" trace rather than by neural circuits that delay the vestibular inputs to the site of plasticity. The results suggest two alternative accounts of learning in the VOR. Either there are multiple mechanisms of learning that use different combinations of neural signals to drive plasticity, or there is a single mechanism tuned to climbing-fiber activity that follows activity in vestibular pathways by approximately 100 msec.

Physiologic basis for motor learning in the vestibulo-ocular reflex

The vestibulo-ocular reflex has been used extensively for study of the neural mechanisms of learning that is dependent on an intact cerebellum. Anatomic, physiologic, behavioral, and computational approaches have revealed the neural circuits that are used to generate the vestibulo-ocular reflex and have identified two likely sites of plasticity within those circuits. One site of plasticity is in the vestibular inputs to floccular target neurons, which are located in the vestibular nuclei and receive monosynaptic inhibition from Purkinje cells in the floccular complex of the cerebellar cortex. The other site of plasticity is in the vestibular inputs to Purkinje cells in the floccular complex, possibly in the cerebellar cortex. After reviewing the evidence that supports these conclusions, I consider a number of observations showing that the dynamics of neural circuits or cellular mechanisms play important roles in learning in the vestibulo-ocular reflex.

Postsaccadic enhancement of initiation of smooth pursuit eye movements in monkeys

Step-ramp target motion evokes a characteristic sequence of presaccadic smooth eye movement in the direction of the target ramp, catch-up targets to bring eye position close to the position of the moving target, and postsaccadic eye velocities that nearly match target velocity. I have analyzed this sequence of eye movements in monkeys to reveal a strong postsaccadic enhancement of pursuit eye velocity and to document the conditions that lead to that enhancement. Smooth eye velocity was measured in the last 10 ms before and the first 10 ms after the first saccade evoked by step-ramp target motion. Plots of eye velocity as a function of time after the onset of the target ramp revealed that eye velocity at a given time was much higher if measured after versus before the saccade. Postsaccadic enhancement of pursuit was recorded consistently when the target stepped 3 degrees eccentric on the horizontal axis and moved upward, downward, or away from the position of fixation. To determine whether postsaccadic enhancement of pursuit was invoked by smear of the visual scene during a saccade, I recorded the effect of simulated saccades on the presaccadic eye velocity for step-ramp target motion. The 3 degrees simulated saccade, which consisted of motion of a textured background at 150 degrees/s for 20 ms, failed to cause any enhancement of presaccadic eye velocity. By using a strategically selected set of oblique target steps with horizontal ramp target motion, I found clear enhancement for saccades in all directions, even those that were orthogonal to target motion. When the size of the target step was varied by up to 15 degrees along the horizontal meridian, postsaccadic eye velocity did not depend strongly either on the initial target position or on whether the target moved toward or away from the position of fixation. In contrast, earlier studies and data in this paper show that presaccadic eye velocity is much stronger when the target is close to the center of the visual field and when the target moves toward versus away from the position of fixation. I suggest that postsaccadic enhancement of pursuit reflects activation, by saccades, of a switch that regulates the strength of transmission through the visual-motor pathways for pursuit. Targets can cause strong visual motion signals but still evoke low presaccadic eye velocities if they are ineffective at activating the pursuit system.

Vector averaging for smooth pursuit eye movements initiated by two moving targets in monkeys

The visual input for pursuit eye movements is represented in the cerebral cortex as the distributed activity of neurons that are tuned for both the direction and speed of target motion. To probe how the motor system uses this distributed code to compute a command for smooth eye movements, we have recorded the initiation of pursuit for 150 msec presentations of two spots moving at different speeds and/or in different directions. With equal probability, one of the two spots continued to move at the same speed and in the same direction and became the tracking target, whereas the other disappeared and served as a distractor. We measured eye acceleration in the interval from 110 to 206 msec after the onset of spot motion, within both the open-loop interval for pursuit and the interval during which eye motion was affected by the two spots. Our results demonstrate that weighted vector averaging is used to combine the responses to two moving spots. We found only a minute number of responses that were consistent with either vector summation or winner-take-all computations. In addition, our data show that it is difficult for the monkey to defeat vector averaging without extended training on the use of an explicit cue about which spot will become the target. We argue that our experiment reveals the computations done by the pursuit system in the absence of attentional bias and that vector averaging is normally used to read the distributed code of image motion when there is only one target.

Neuronal responses in visual areas MT and MST during smooth pursuit target selection

We recorded the activity of single neurons in the middle temporal (MT) and middle superior temporal (MST) visual areas in two macaque monkeys while the animals performed a smooth pursuit target selection task. The monkeys were presented with two moving stimuli of different colors and were trained to initiate smooth pursuit to the stimulus that matched the color of a previously given cue. We designed these experiments so that we could separate the component of the neuronal response that was driven by the visual stimulus from an extraretinal component that predicted the color or direction of the selected target. We found that for all cells in MT and MST the response was primarily determined by the visual stimulus. However, 14% (8 of 58) of MT neurons and 26% (22 of 84) of MST neurons had a small predictive component that was significant at the P < or = 0.05 level. In some cells, the predictive component was clearly related to the color of the intended target, but more often it was correlated with the direction of the target. We have previously documented a systematic shift in the latency of smooth pursuit that depends on the relative direction of motion of the two stimuli. We found that neither the latency nor the amplitude of neuronal responses in MT or MST was correlated with behavioral latency. These results are consistent with a model for target selection in which a weak selection bias for the intended target is amplified by a competitive network that suppresses motion signals related to the nonintended stimulus. It is possible that the predictive component of neuronal responses in MT and MST contributes to the selection bias. However, the strength of the selection bias in MT and MST is not sufficient to account for the high degree of selectivity shown by pursuit behavior.

Multiple subclasses of Purkinje cells in the primate floccular complex provide similar signals to guide learning in the vestibulo-ocular reflex

The neural "learning rules" governing the induction of plasticity in the cerebellum were analyzed by recording the patterns of neural activity in awake, behaving animals during stimuli that induce a form of cerebellum-dependent learning. We recorded the simple- and complex-spike responses of a broad sample of Purkinje cells in the floccular complex during a number of stimulus conditions that induce motor learning in the vestibulo-ocular reflex (VOR). Each subclass of Purkinje cells carried essentially the same information about required changes in the gain of the VOR. The correlation of simple-spike activity in Purkinje cells with activity in vestibular pathways could guide learning during low-frequency but not high-frequency stimuli. Climbing fiber activity could guide learning during all stimuli tested but only if compared with the activity present approximately 100 msec earlier in either vestibular pathways or Purkinje cells.

The effect of a moving distractor on the initiation of smooth-pursuit eye movements

As a step toward understanding the mechanism by which targets are selected for smooth-pursuit eye movements, we examined the behavior of the pursuit system when monkeys were presented with two discrete moving visual targets. Two rhesus monkeys were trained to select a small moving target identified by its color in the presence of a moving distractor of another color. Smooth-pursuit eye movements were quantified in terms of the latency of the eye movement and the initial eye acceleration profile. We have previously shown that the latency of smooth pursuit, which is normally around 100 ms, can be extended to 150 ms or shortened to 85 ms depending on whether there is a distractor moving in the opposite or same direction, respectively, relative to the direction of the target. We have now measured this effect for a 360 deg range of distractor directions, and distractor speeds of 5-45 deg/s. We have also examined the effect of varying the spatial separation and temporal asynchrony between target and distractor. The results indicate that the effect of the distractor on the latency of pursuit depends on its direction of motion, and its spatial and temporal proximity to the target, but depends very little on the speed of the distractor. Furthermore, under the conditions of these experiments, the direction of the eye movement that is emitted in response to two competing moving stimuli is not a vectorial combination of the stimulus motions, but is solely determined by the direction of the target. The results are consistent with a competitive model for smooth-pursuit target selection and suggest that the competition takes place at a stage of the pursuit pathway that is between visual-motion processing and motor-response preparation.

Behavioral analysis of signals that guide learned changes in the amplitude and dynamics of the vestibulo-ocular reflex

We characterized the dependence of motor learning in the monkey vestibulo-ocular reflex (VOR) on the duration, frequency, and relative timing of the visual and vestibular stimuli used to induce learning. The amplitude of the VOR was decreased or increased through training with paired head and visual stimulus motion in the same or opposite directions, respectively. For training stimuli that consisted of simultaneous pulses of head and target velocity 80-1000 msec in duration, brief stimuli caused small changes in the amplitude of the VOR, whereas long stimuli caused larger changes in amplitude as well as changes in the dynamics of the reflex. When the relative timing of the visual and vestibular stimuli was varied, brief image motion paired with the beginning of a longer vestibular stimulus caused changes in the amplitude of the reflex alone, but the same image motion paired with a later time in the vestibular stimulus caused changes in the dynamics as well as the amplitude of the VOR. For training stimuli that consisted of sinusoidal head and visual stimulus motion, low-frequency training stimuli induced frequency-selective changes in the VOR, as reported previously, whereas high-frequency training stimuli induced changes in the amplitude of the VOR that were more similar across test frequency. The results suggest that there are at least two distinguishable components of motor learning in the VOR. One component is induced by short-duration or high-frequency stimuli and involves changes in only the amplitude of the reflex. A second component is induced by long-duration or low-frequency stimuli and involves changes in the amplitude and dynamics of the VOR.

Coordinate system for learning in the smooth pursuit eye movements of monkeys

Learning was induced in smooth pursuit eye movements by repeated presentation of targets that moved at one speed for 100 msec and then changed to a second, higher or lower, speed. The learned changes, measured as eye acceleration for the first 100 msec of pursuit, were largest in a "late" interval from 50 to 80 msec after the onset of pursuit and were smaller and less consistent in the earliest 30 msec of pursuit. In each experiment, target motion in one direction consisted of learning trials, whereas target motion in the opposite (control) direction consisted of trials in which targets moved at a constant speed for the entire duration of the trial. Under these conditions, the learning did not generalize to the control direction. For target motion in the learning direction, the changes in pursuit generalized to responses evoked by targets moving at speeds ranging from 15 to 45 degrees/sec as well as to targets of different colors and sizes. Although learning was induced at the initiation of pursuit, it generalized to the response to image motion in the learning direction when it was presented during pursuit in the learning direction. However, learning did not generalize to the response to image motion in the learning direction when it was presented during pursuit in the control direction. The results suggest that the learning does not occur in purely sensory or motor coordinates but in an intermediate reference frame at least partly defined by the direction of eye movement. The selectivity of learning provides new evidence for a previously hypothesized neural "switch" that gates visual information on the basis of movement direction. This selectivity also suggests that the locus of pursuit learning is in pathways related to the operation of the switch.

Effects of early-onset artificial strabismus on pursuit eye movements and on neuronal responses in area MT of macaque monkeys

In humans, esotropia of early onset is associated with a profound asymmetry in smooth pursuit eye movements. When viewing is monocular, targets are tracked well only when they are moving nasally with respect to the viewing eye. To determine whether this pursuit abnormality reflects an anomaly in cortical visual motion processing, we recorded eye movements and cortical neural responses in nonamblyopic monkeys made strabismic by surgery at the age of 10-60 d. Eye movement recordings revealed the same asymmetry in the monkeys' pursuit eye movements as in humans with early-onset esotropia. With monocular viewing, pursuit was much stronger for nasalward motion than for temporalward motion, especially for targets presented in the nasal visual field. However, for targets presented during ongoing pursuit, temporalward and nasalward image motion was equally effective in modulating eye movement. Single-unit recordings made from the same monkeys, under anesthesia, revealed that MT neurons were rarely driven binocularly, but otherwise had normal response properties. Most were directionally selective, and their direction preferences were uniformly distributed. Our neurophysiological and oculomotor measurements both suggest that the pursuit defect in these monkeys is not due to altered cortical visual motion processing. Rather, the asymmetry in pursuit may be a consequence of imbalances in the two eyes' inputs to the "downstream" areas responsible for the initiation of pursuit.

The cerebellum: a neuronal learning machine?

Comparison of two seemingly quite different behaviors yields a surprisingly consistent picture of the role of the cerebellum in motor learning. Behavioral and physiological data about classical conditioning of the eyelid response and motor learning in the vestibulo-ocular reflex suggests that (i) plasticity is distributed between the cerebellar cortex and the deep cerebellar nuclei; (ii) the cerebellar cortex plays a special role in learning the timing of movement; and (iii) the cerebellar cortex guides learning in the deep nuclei, which may allow learning to be transferred from the cortex to the deep nuclei. Because many of the similarities in the data from the two systems typify general features of cerebellar organization, the cerebellar mechanisms of learning in these two systems may represent principles that apply to many motor systems.

Directional organization of eye movement and visual signals in the floccular lobe of the monkey cerebellum

The floccular lobe of the monkey is critical for the generation of visually-guided smooth eye movements. The present experiments reveal physiological correlates of the directional organization in the primate floccular lobe by examining the selectivity for direction of eye motion and visual stimulation in the firing of individual Purkinje cells (PCs) and mossy fibers. During tracking of sinusoidal target motion along different axes in the frontoparallel plane, PCs fell into two classes based on the axis that caused the largest modulation of simple-spike firing rate. For "horizontal" PCs, the response was maximal during horizontal eye movements, with increases in firing rate during pursuit toward the side of recording (ipsiversive). For "vertical" PCs, the response was maximal during eye movement along an axis just off pure vertical, with increases in firing rate during pursuit directed downward and slightly contraversive. During pursuit of target motion at constant velocity, PCs again fell into horizontal and vertical classes that matched the results from sinusoidal tracking. In addition, the directional tuning of the sustained "eye velocity" and transient "visual" components of the neural responses obtained during constant velocity tracking were very similar. PCs displayed very broad tuning approximating a cosine tuning curve; the mean half-maximum bandwidth of their tuning curves was 170-180 degrees. Other cerebellar elements, related purely to eye movement and presumed to be mossy fibers, exhibited tuning approximately 40 degrees narrower than PCs and had best directions that clustered around the four cardinal directions. Our data indicate that the motion signals encoded by PCs in the monkey floccular lobe are segregated into channels that are consistent with a coordinate system defined by the vestibular apparatus and eye muscles. The differences between the tuning properties exhibited by PCs compared with mossy fibers indicate that a spatial transformation occurs within the floccular lobe.

Neural recordings and behavioral observations in the monkey vestibulo-ocular reflex constrain the cellular mechanisms for cerebellum-dependent behavioral learning

Recordings from the cerebellum under behavioral conditions that cause learning in the vestibulo-ocular reflex (VOR) constrain the cellular mechanisms that could mediate learning. Analysis of the complex-spike responses of Purkinje cells demonstrates a mismatch between the properties of cerebellar long-term depression (LTD) in vitro and the signals available to guide learning in vivo. To resolve this mismatch, it may be necessary to assume that there are multiple cellular mechanisms of VOR learning, including both depression and potentiation.

Cellular processing of temporal information in medial vestibular nucleus neurons

Quantitative descriptions of the cellular transformations from behaviorally relevant inputs into temporal patterns of firing are crucial for understanding information processing in systems of neurons and for incorporating biological properties of neurons into models of the neural control of behavior. To understand how neurons that mediate vestibulo-ocular behavior transform their inputs into temporal patterns of firing, we examined responses of medial vestibular nucleus (MVN) neurons to current injected intracellularly. MVN neurons recorded from avian brain slices fired spontaneously. Sinusoidal modulation of input current produced precisely sinusoidal modulation of firing rate. The transformation between input current and firing rate was remarkably linear: firing rate scaled linearly as a function of current amplitude, and the responses to steps of input current were predicted accurately from the linear superposition of responses to sinusoidal modulation of input current. Over the physiological range of head movement frequencies, from 0.1 to 10 Hz, peak-to-peak modulation of firing rate was relatively constant or increased slightly in most neurons. In contrast, when hyperpolarizing current was used to keep neurons below threshold for action potentials, the frequency response of the membrane potential behaved like a low-pass filter. These results imply that the membrane conductances that are active when MVN neurons fire compensate for the low-pass characteristics of the membrane to allow faithful transmission of high frequency head movement signals.

Inputs from the ipsilateral and contralateral vestibular apparatus to behaviorally characterized abducens neurons in rhesus monkeys

1. We made extracellular recordings from neurons in the abducens nuclei of alert rhesus monkeys during electrical stimulation of the vestibular labyrinths with brief current pulses and during smooth pursuit, steady fixation, and the vestibuloocular reflex (VOR) evoked by passive head turns. The responses to electrical stimuli were compared with quantitative measures of the sensitivity of each neuron to eye position and eye velocity. We also compared the strengths of the vestibular inputs from the labyrinths ipsilateral and contralateral to the side of recording. 2. Abducens neurons showed transient excitation after a current pulse was applied to the contralateral labyrinth and transient inhibition after stimulation of the ipsilateral labyrinth. The latency of excitation had a mean value of 1.7 ms and a median value of 1.5 ms. Latency was unimodally distributed with little variation among neurons. Neurons with large responses showed a second phase of excitation that started 2.5 ms after the stimulus. 3. In two of three monkeys, the excitatory responses of abducens neurons to electrical stimulation of the contralateral labyrinth were approximately 3 times as large as their inhibitory responses to stimulation of the ipsilateral labyrinth. The difference in response size was not observed in the third monkey. The asymmetry in the size of the electrically evoked inputs from the two labyrinths was associated with a smaller asymmetry in responses of abducens neurons during the VOR evoked by passive head turns. The increase in firing rate during head rotation away from the side of the recording was almost always larger than the decrease in firing rate during head rotation toward the side of the recording. 4. The size of the neuronal response to electrical stimulation was correlated with the magnitude of the change in discharge rate during eye movements. Single or multiple regression of measures of response amplitude against eye position threshold, sensitivity to eye position, sensitivity to eye velocity, and baseline discharge rate yielded correlation coefficients that ranged from 0.26 to 0.92 in different monkeys. The existence of positive correlations is consistent with a role of the intrinsic properties of abducens neurons in determining recruitment order. However, the existence of large amounts of variability within most of the samples suggests that the recruitment order of abducens neurons also depends on the discharge properties of the afferents to each abducens neuron.

Attention and target selection for smooth pursuit eye movements

Two rhesus monkeys were trained to track a small moving target in the presence of a moving distractor. The target and distractor were distinguished by their color. Smooth pursuit eye movements were quantified in terms of the latency of the eye movement and the open-loop eye acceleration profile. Smooth pursuit latencies for single targets were on the order of 100 msec. When the target was paired with a distractor moving in the same direction as the target, pursuit latencies decreased to roughly 85 msec. When the target was paired with a distractor moving in the opposite direction, pursuit latencies increased to roughly 150 msec. The motion of the distractor had no significant effect on the eye acceleration profile. Experiments were performed to dissociate visual search for the target from pursuit initiation by providing a spatial cue rather than the color cue. These experiments showed that visual search necessarily preceded pursuit initiation only when the distractor moved in the opposite direction relative to the target. In this case, visual search contributed about 25 msec to the overall latency of pursuit. Control experiments showed that the monkey need not attend to the distractor in order for it to influence the latency of pursuit. A network model was developed in which units that represent the motions of the target and distractor compete against one another. Attention serves to bias the outcome of this competition toward the direction of the selected target. The performance of this network exhibits a striking parallel to the effect of the distractor on smooth pursuit latency.

Membrane and firing properties of avian medial vestibular nucleus neurons in vitro

The intrinsic membrane and firing properties of medial vestibular nucleus (MVN) neurons were investigated in slices of the chick brainstem using intracellular recording and current injection. Avian MVN neurons fired spontaneous action potentials with very regular interspike intervals. The rapid repolarization of all action potentials was followed by an after-hyperpolarization. Intracellular injection of steps of hyperpolarizing current revealed both an inward rectification of the membrane potential during the step and a rebound depolarization following the offset of the step. In some neurons, the rebound depolarization resulted in bursts of action potentials. Steps of depolarizing current applied to spontaneously active neurons evoked increases in firing rate that were higher at the onset of the step than during the steady-state response. The relationship between current and firing rate was linear. The membrane and firing properties of avian MVN neurons were distributed continuously across the population of recorded neurons. These properties appear identical to those of rodent MVN neurons, suggesting that the composition and distribution of ion channels in the MVN neuronal membrane has been highly conserved across vertebrate species.

Learning. A mechanism of learning found?

Synaptic plasticity in the cerebellar cortex is abolished and cerebellum-dependent motor learning is decreased in mice lacking a metabotropic glutamate receptor. Is the receptor involved in learning?

A model of visually-guided smooth pursuit eye movements based on behavioral observations

We report a model that reproduces many of the behavioral properties of smooth pursuit eye movements. The model is a negative-feedback system that uses three parallel visual motion pathways to drive pursuit. The three visual pathways process image motion, defined as target motion with respect to the moving eye, and provide signals related to image velocity, image acceleration, and a transient that occurs at the onset of target motion. The three visual motion signals are summed and integrated to produce the eye velocity output of the model. The model reproduces the average eye velocity evoked by steps of target velocity in monkeys and humans and accounts for the variation among individual responses and subjects. When its motor pathways are expanded to include positive feedback of eye velocity and a "switch", the model reproduces the exponential decay in eye velocity observed when a moving target stops. Manipulation of this expanded model can mimic the effects of stimulation and lesions in the arcuate pursuit area, the middle temporal visual area (MT), and the medial superior temporal visual area (MST).

Simple spike responses of gaze velocity Purkinje cells in the floccular lobe of the monkey during the onset and offset of pursuit eye movements

1. We recorded the simple spike firing rate of gaze velocity Purkinje cells (GVP-cells) in the flocculus/ventral paraflocculus of two monkeys during the smooth pursuit eye movements evoked by a target that was initially at rest, started suddenly, moved at a constant velocity, and then stopped. 2. For target motion in the preferred direction, GVP-cells showed a large transient increase in firing rate at the onset of pursuit, a smaller but sustained increase during the maintenance of pursuit, and a smooth return to baseline firing with little undershoot at the offset of pursuit. For target motion in the nonpreferred direction, GVP-cells showed a small decrease in firing rate at the onset of pursuit, a similar sustained decrease during the maintenance of pursuit, but a large transient increase in firing rate at the offset of pursuit before returning to baseline firing. 3. We pooled the data in our sample of horizontal GVP-cells by subtracting the population average of firing rate recorded during pursuit in the nonpreferred direction from the population average recorded during pursuit in the preferred direction. We transformed this net population average by passing it through a model of the brain stem final common pathway and the oculomotor plant. This yielded a signal that closely matched the observed trajectory of eye velocity during pursuit. We conclude that the transient overshoots exhibited in the firing rate of GVP-cells can provide appropriate compensation for the lagging dynamics of the oculomotor plant.

Neural basis for motor learning in the vestibuloocular reflex of primates. II. Changes in the responses of horizontal gaze velocity Purkinje cells in the cerebellar flocculus and ventral paraflocculus

1. We made extracellular recordings from Purkinje cells in the flocculus and ventral paraflocculus of awake monkeys before and after motor learning in the vestibuloocular reflex (VOR). Three samples were recorded 1) after miniaturizing spectacles had reduced the gain of the VOR (eye speed divided by head speed) to 0.4; 2) when the gain of the VOR was near 1.0; and 3) after magnifying spectacles had increased the gain of the VOR to 1.6. 2. We studied Purkinje cells that showed stronger modulation of simple-spike firing rate during horizontal than during vertical pursuit. These cells corresponded to the previously identified "horizontal gaze velocity Purkinje cells" or HGVP-cells. During pursuit of smooth target motion with the head stationary, HGVP-cells showed strong modulation of firing rate with increases for ipsiversive eye motion (toward the side of recording). When the monkey canceled his VOR by tracking a target that moved exactly with him during sinusoidal head rotation in the horizontal plane, HGVP-cells again showed strong modulation of firing rate with increases for ipsiversive head motion. 3. The responses of HGVP-cells during pursuit with the head stationary and during cancellation of the VOR reveal separate components of firing rate related to eye and head velocity. We used these two behavioral conditions to test for effects of motor learning on the head and eye velocity components of the simple-spike firing of HGVP-cells. Our data confirm the previous observation that motor learning causes the sensitivity to head velocity to be larger when the gain of the VOR is high and smaller when the gain of the VOR is low. Thus we agree with the previous conclusion that changes in the vestibular sensitivity of HGVP-cells, measured during sinusoidal head motion at low frequencies, are in the wrong direction to cause changes in the gain of the VOR. 4. To determine whether the simple-spike output from the HGVP-cells plays a role in the VOR after motor learning, we recorded simple-spike firing during the VOR evoked by transient, rapid changes in head velocity in darkness. When the gain of the VOR was low, firing rate increased during the VOR evoked by ipsiversive head motion and decreased during the VOR evoked by contraversive head motion. When the gain of the VOR was high, the direction selectivity of the responses was reversed.(ABSTRACT TRUNCATED AT 400 WORDS)

Neural basis for motor learning in the vestibuloocular reflex of primates. III. Computational and behavioral analysis of the sites of learning

1. We have used a combination of eye movement recordings and computer modeling to study long-term adaptive modification (motor learning) in the vestibuloocular reflex (VOR). The eye movement recordings place constraints on possible sites for motor learning. The computer model abides by these constraints, as well as constraints provided by data in previous papers, to formalize a new hypothesis about the sites of motor learning. The model was designed to reproduce as much of the existing neural and behavioral data as possible. 2. Motor learning was induced in monkeys by fitting them with spectacles that caused the gain of the VOR (eye speed divided by head speed) to increase to values > 1.6 or to decrease to values < 0.4. We elicited pursuit by providing ramp motion of a small target at 30 degrees/s along the horizontal axis. Changes in the gain of the VOR caused only small and inconsistent changes in the eye acceleration in the first 100 ms after the onset of pursuit and had no effect on the eye velocity during tracking of steady target motion. Electrical stimulation in the flocculus and ventral paraflocculus with single pulses or trains of pulses caused smooth eye movement toward the side of stimulation after latencies of 9-11 ms. Neither the latency, the peak eye velocity, nor the initial eye acceleration varied as a consistent function of the gain of the VOR. 3. The computer model contained nodes that represented position-vestibular-pause cells (PVP-cells) and flocculus target neurons (FTNs) in the vestibular nucleus, and horizontal gaze-velocity Purkinje cells (HGVP-cells) in the cerebellar flocculus and ventral paraflocculus. Node FTN represented only the "E-c FTNs," which show increased firing for eye motion away from the side of recording. The transfer functions in the model included dynamic elements (filters) as well as static elements (summing junctions, gain elements, and time delays). Except for the transfer functions that converted visual motion inputs into commands for smooth eye movement, the model was linear. 4. The performance of the model was determined both by computer simulation and, for the VOR in the dark, by analytic solution of linear equations. For simulation, we adjusted the parameters by hand to match the output of the model to the eye velocity of monkeys and to match the activity of the relevant nodes in the model to the firing of HGVP-cells, FTNs, and PVP-cells when the gain of the VOR was 0.4, 1.0, and 1.6.(ABSTRACT TRUNCATED AT 400 WORDS)

Neural basis for motor learning in the vestibuloocular reflex of primates. I. Changes in the responses of brain stem neurons

1. We recorded from neurons in the brain stem of monkeys before and after they had worn magnifying or miniaturizing spectacles to cause changes in the gain of the vestibuloocular reflex (VOR). The gain of the VOR was estimated as eye speed divided by head speed during passive horizontal head rotation in darkness. Electrical stimulation in the cerebellum was used to identify neurons that receive inhibition at monosynaptic latencies from the flocculus and ventral paraflocculus (flocculus target neurons or FTNs). Cells were studied during smooth pursuit eye movements with the head stationary, fixation of different positions, cancellation of the VOR, and the VOR evoked by rapid changes in head velocity. 2. FTNs were divided into two populations according to their responses during pursuit with the head stationary. The two groups showed increased firing during smooth eye motion toward the side of recording (Eye-ipsiversive or E-i) or away from the side of recording (Eye-contraversive or E-c). A higher percentage of FTNs showed increased firing rate for contraversive pursuit when the gain of the VOR was high (> or = 1.6) than when the gain of the VOR was low (< or = 0.4). 3. Changes in the gain of the VOR had a striking effect on the responses during the VOR for the FTNs that were E-c during pursuit with the head stationary. Firing rate increased during contraversive VOR eye movements when the gain of the VOR was high or normal and decreased during contraversive VOR eye movements when the gain of the VOR was low. Changes in the gain of the VOR caused smaller changes in the responses during the VOR of FTNs that were E-i during pursuit with the head stationary. We argue that motor learning in the VOR is the result of changes in the responses of individual FTNs. 4. The responses of E-i and E-c FTNS during cancellation of the VOR depended on the gain of the VOR. Responses tended to be in phase with contraversive head motion when the gain of the VOR was low and in phase with ipsiversive head motion when the gain of the VOR was high. Comparison of the effect of motor learning on the responses of FTNs during cancellation of the VOR with the results of similar experiments on horizontal-gaze velocity Purkinje cells in the flocculus and ventral paraflocculus suggests that the brain stem vestibular inputs to FTNs are one site of motor learning in the VOR.(ABSTRACT TRUNCATED AT 400 WORDS)

Responses during eye movements of brain stem neurons that receive monosynaptic inhibition from the flocculus and ventral paraflocculus in monkeys

1. We have identified a group of brain stem cells called "flocculus target neurons" (or FTNs) because they are inhibited at monosynaptic latencies by stimulation of the flocculus and the ventral paraflocculus with single electrical pulses. We report the responses of FTNs, as well as those of other brain stem cells, during horizontal eye movements with the head stationary and during natural vestibular stimulation in monkeys. 2. FTNs discharged primarily in relation to eye movements. The majority (71%) showed increased firing for eye movement away from the side of the recording ("contraversive"), which is consistent with their inhibition by Purkinje cells that show increased firing for eye movement toward the side of recording. However, a significant and surprisingly large percentage (29%) of FTNs showed increased firing for eye movement toward the side of recording ("ipsiversive"). 3. The firing rate of FTNs showed strong modulation during pursuit of sinusoidal target motion with the head stationary and during the compensatory eye movements evoked by fixation of an earth-stationary target with sinusoidal head rotation. In addition, firing rate was related to eye position during steady fixation at different positions. Of the FTNs that showed increased firing for contraversive eye motion during pursuit with the head stationary, most had an infection in the relationship between firing rate and eye position so that the sensitivity to eye position was low for eye positions ipsilateral to straight-ahead gaze and high for eye positions contralateral to straight-ahead gaze. 4. When the monkey canceled the vestibuloocular reflex (VOR) by tracking a target that moved exactly with him during sinusoidal head rotation, the firing rate of FTNs was modulated much less strongly than during pursuit with the head stationary. In the FTNs that showed increased firing for contraversive eye motion during pursuit, firing rate during cancellation of the VOR increased for contraversive head motion during sinusoidal vestibular rotation at 0.4 Hz but was only weakly modulated during rotation at 0.2 Hz. 5. The position-vestibular-pause cells (PVP-cells), previously identified as interneurons in the disynaptic VOR pathways, were not inhibited by stimulation of the flocculus and ventral paraflocculus and had response properties that were different from FTNs. The majority (69%) showed increased firing for contraversive eye motion during pursuit and for ipsiversive head motion during cancellation of the VOR, whereas some (31%) showed the opposite direction preferences under both conditions.(ABSTRACT TRUNCATED AT 250 WORDS)

Temporal properties of visual motion signals for the initiation of smooth pursuit eye movements in monkeys

1. Our goal was to assess whether visual motion signals related to changes in image velocity contribute to pursuit eye movements. We recorded the smooth eye movements evoked by ramp target motion at constant speed. In two different kinds of stimuli, the onset of target motion provided either an abrupt, step change in target velocity or a smooth target acceleration that lasted 125 ms followed by prolonged target motion at constant velocity. We measured the eye acceleration in the first 100 ms of pursuit. Because of the 100-ms latency from the onset of visual stimuli to the onset of smooth eye movement, the eye acceleration in this 100-ms interval provides an estimate of the open-loop response of the visuomotor pathways that drive pursuit. 2. For steps of target velocity, eye acceleration in the first 100 ms of pursuit depended on the "motion onset delay," defined as the interval between the appearance of the target and the onset of motion. If the motion onset delay was > 100 ms, then the initial eye movement consisted of separable early and late phases of eye acceleration. The early phase dominated eye acceleration in the interval from 0 to 40 ms after pursuit onset and was relatively insensitive to image speed. The late phase dominated eye acceleration in the interval 40-100 ms after the onset of pursuit and had an amplitude that was proportional to image speed. If there was no delay between the appearance of the target and the onset of its motion, then the early component was not seen, and eye acceleration was related to target speed throughout the first 100 ms of pursuit. 3. For step changes of target velocity, the relationship between eye acceleration in the first 40 ms of pursuit and target velocity saturated at target speeds > 10 degrees /s. In contrast, the relationship was nearly linear when eye acceleration was measured in the interval 40-100 ms after the onset of pursuit. We suggest that the first 40 ms of pursuit are driven by a transient visual motion input that is related to the onset of target motion (motion onset transient component) and that the next 60 ms are driven by a sustained visual motion input (image velocity component). 4. When the target accelerated smoothly for 125 ms before moving at constant speed, the initiation of pursuit resembled that evoked by steps of target velocity. However, the latency of pursuit was consistently longer for smooth target accelerations than for steps of target velocity.(ABSTRACT TRUNCATED AT 400 WORDS)

Initial tracking conditions modulate the gain of visuo-motor transmission for smooth pursuit eye movements in monkeys

Smooth pursuit eye movements allow primates to keep gaze pointed at small objects moving across stationary surroundings. In monkeys trained to track a small moving target, we have injected brief perturbations of target motion under different initial conditions as probes to read out the state of the visuo-motor pathways that guide pursuit. A large eye movement response was evoked if the perturbation was applied to a moving target the monkey was tracking. A small response was evoked if the same perturbation was applied to a stationary target the monkey was fixating. The gain of the response to the perturbation increased as a function of the initial speed of target motion and as a function of the interval from the onset of target motion to the time of the perturbation. The response to the perturbation also was direction selective. Gain was largest if the perturbation was along the axis of ongoing target motion and smallest if the perturbation was orthogonal to the axis of target motion. We suggest that two parallel sets of visual motion pathways through the extrastriate visual cortex may mediate, respectively, the visuo-motor processing for pursuit and the modulation of the gain of transmission through those pathways.

Physiological properties of vestibular primary afferents that mediate motor learning and normal performance of the vestibulo-ocular reflex in monkeys

We have used electrical stimulation of the vestibular apparatus to reveal parallels between the physiological responses of the vestibular afferents activated at different currents and the properties of the evoked eye movements before and after magnifying spectacles had been used to cause motor learning in the vestibulo-ocular reflex (VOR). Stimulation with the lowest currents caused little or no eye motion, but activated all the afferents with irregular spontaneous discharge, low sensitivities to head velocity, and highly phasic responses during rapid head turns. Stimulation with moderate currents caused substantial eye motion that was weakly affected by motor learning; these currents activated afferents with a wide range of physiological properties, including many that had intermediate discharge regularity, high sensitivity to head velocity, and clear phasic responses during rapid head turns. Stimulation at still higher currents caused still larger eye movements that were strongly altered by motor learning; these currents activated primarily afferents that had regular spontaneous discharge, lower sensitivities to head velocity, and tonic responses during rapid head turns. Stimulation at the highest currents did not cause any further increment in the amplitude of the evoked eye movement, but activated the afferents with the most regular spontaneous discharge and the lowest sensitivities to head velocity. The data imply that the VOR pathways receive substantial vestibular inputs from afferents with a middle range of thresholds for electrical stimulation. These afferents have a wide range of physiological properties, including a large group that shows substantial phasic responses during rapid head turns. The data also suggest that only a subset of these afferents, primarily those with more regular spontaneous discharge, project into the VOR pathways that are modified in association with motor learning.

Eye movements and brainstem neuronal responses evoked by cerebellar and vestibular stimulation in chicks

The vestibulo-ocular reflex undergoes adaptive changes that require inputs from the cerebellar flocculus onto brainstem vestibular neurons. As a step toward developing an in vitro preparation in chicks for studying the synaptic basis of those changes, we have elucidated the organization of the pathways through which the flocculus influences vestibulo-ocular movements. Electrical stimulation of the vestibular ampulla evoked brief, contralaterally directed movements in both eyes. Although single current pulses to the flocculus elicited no response, conjunctive stimulation of the flocculus and the vestibular apparatus significantly reduced the vestibularly-evoked movement. Trains of current pulses applied to the flocculus and ampulla evoked eye movements directed toward and away from the side of stimulation, respectively. Recordings from the brainstem revealed neurons that were activated by ipsilateral vestibular stimulation and inhibited by ipsilateral floccular stimulation. Our sample included neurons in the lateral vestibular nucleus, the ventrolateral portion of the medial vestibular nucleus, and the superior vestibular nucleus. Similarities between these findings and those of similar studies in mammals indicate that the chick will provide a good model system for cellular studies of adaptive changes in the vestibulo-ocular reflex.

Motor learning in a recurrent network model based on the vestibulo-ocular reflex

Most models of neural networks have assumed that neurons process information on a timescale of milliseconds and that the long-term modification of synaptic strengths underlies learning and memory. But neurons also have cellular mechanisms that operate on a timescale of tens or hundreds of milliseconds, such as a gradual rise in firing rate in response to injection of constant current or a rapid rise followed by a slower adaptation. These dynamic properties of neuronal responses are mediated by ion channels that are subject to modulation. We demonstrate here how a neural network with recurrent feedback connections can convert long-term modulation of neural responses that occur over these intermediate timescales into changes in the amplitude of the steady output from the system. This general principle may be relevant to many feedback systems in the brain. Here it is applied to the vestibulo-ocular reflex, whose amplitude is subject to long-term adaptive modification by visual inputs. The model reconciles apparently contradictory data on the neural locus of the cellular mechanisms that mediate this simple form of learning and memory.

Vestibular inputs to brain stem neurons that participate in motor learning in the primate vestibuloocular reflex

1. Previous studies have described a subpopulation of interneurons in the vestibuloocular reflex (VOR) pathways that express large changes in their responses to head turns in conjunction with motor learning in the VOR. These neurons are called flocculus target neurons (FTNs) because they are inhibited at monosynaptic latencies by stimulation of the flocculus and ventral paraflocculus. 2. Electrical stimulation of the vestibular labyrinth revealed that FTNs receive excitatory monosynaptic inputs from the ipsilateral vestibular labyrinth and longer-latency, excitatory inputs from the contralateral labyrinth. 3. Our data show that commissural inhibition, which has been thought to be an important feature of vestibular processing, does not provide the dominant inputs from the contralateral labyrinth to FTNs. Instead, the inputs from both labyrinths are excitatory and may be functionally antagonistic. Changes in the balance of excitatory inputs from the two horizontal canals to FTNs could contribute to motor learning in the VOR.