Serial linkage of target selection for orienting and tracking eye movements

Many natural actions require the coordination of two different kinds of movements. How are targets chosen under these circumstances: do central commands instruct different movement systems in parallel, or does the execution of one movement activate a serial chain that automatically chooses targets for the other movement? We examined a natural eye tracking action that consists of orienting saccades and tracking smooth pursuit eye movements, and found strong physiological evidence for a serial strategy. Monkeys chose freely between two identical spots that appeared at different sites in the visual field and moved in orthogonal directions. If a saccade was evoked to one of the moving targets by microstimulation in either the frontal eye field (FEF) or the superior colliculus (SC), then the same target was automatically chosen for pursuit. Our results imply that the neural signals responsible for saccade execution can also act as an internal command of target choice for other movement systems.     

Evidence for object permanence in the smooth-pursuit eye movements of monkeys

We recorded the smooth-pursuit eye movements of monkeys in response to targets that were extinguished (blinked) for 200 ms in mid-trajectory. Eye velocity declined considerably during the target blinks, even when the blinks were completely predictable in time and space. Eye velocity declined whether blinks were presented during steady-state pursuit of a constant-velocity target, during initiation of pursuit before target velocity was reached, or during eye accelerations induced by a change in target velocity. When a physical occluder covered the trajectory of the target during blinks, creating the impression that the target moved behind it, the decline in eye velocity was reduced or abolished. If the target was occluded once the eye had reached target velocity, pursuit was only slightly poorer than normal, uninterrupted pursuit. In contrast, if the target was occluded during the initiation of pursuit, while the eye was accelerating toward target velocity, pursuit during occlusion was very different from normal pursuit. Eye velocity remained relatively stable during target occlusion, showing much less acceleration than normal pursuit and much less of a decline than was produced by a target blink. Anticipatory or predictive eye acceleration was typically observed just prior to the reappearance of the target. Computer simulations show that these results are best understood by assuming that a mechanism of eye-velocity memory remains engaged during target occlusion but is disengaged during target blinks.     

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 °. Other cerebellar elements, related purely to eye movement and presumed to be mossy fibers, exhibited tuning approximately 40 ° 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.     

Relationship between extraretinal component of firing rate and eye speed in area MST of macaque monkeys

We have isolated extraretinal and retinal components of firing during smooth pursuit eye movements in the medial-superior-temporal area (MST) in the extrastriate visual cortex. Awake macaque monkeys tracked spots in total darkness to eliminate image motion inputs from the background. For 300 ms during sustained tracking at different speeds, the target was stabilized on the moving eye, practically eliminating image motion inputs from the tracking target. The extraretinal component of firing rate during image stabilization was direction selective and related to eye speed but sometimes showed a different preferred speed from the retinal component of the same neuron's responses. The highly variable firing rate of individual MST neurons allowed an ideal observer to predict target speed correctly on 25% of trials. Pooling the data from 71 MST neurons improved the correct response rate to 50%. Behavioral experiments imposed brief perturbations of target velocity to assess the gain of visual-motor transmission for pursuit. The average response to perturbations increased as a function of target speed. However, the size of the responses to individual perturbations allowed an ideal observer to predict target speed correctly on only 35% of the trials. The imprecision of MST responses argues that the output of MST may be a poor candidate to drive eye velocity and so may instead regulate another component of pursuit. The good agreement between the eye velocity precision of the behavioral responses to perturbations of target motion and the firing of MST neurons raises regulation of the visual-motor gain of pursuit as one candidate component.     

Vestibular signals carried by pathways subserving plasticity of the vestibulo-ocular reflex in monkeys

The vestibulo-ocular reflex (VOR) is subject to long-term adaptive changes that minimize retinal image slip and keep eye movement equal to and opposite head movement. As a step toward identifying the site of neural changes, we have used a transient vestibular stimulus to study the dynamic response properties of the vestibular signals carried by the modifiable pathways. In normal monkeys, "rapid changes in head velocity" (30 degrees/sec in 50 msec) evoke a VOR that has a slight overshoot and reaches a steady-state gain (eye velocity divided by head velocity) of 1.0. Adaptation to magnifying spectacles causes changes in both the steady-state gain and the degree of overshoot in the eye velocity of the VOR. When the steady-state gain is decreased, the transient overshoot increases, so that peak eye velocity is twice steady-state. When the steady-state gain is increased, the overshoot decreases, so that peak eye velocity is nearly equal to steady-state. The discharge of vestibular primary afferents suggests an explanation for the inverse relationship between the transient overshoot and the steady-state gain of the VOR. In normal monkeys, 73 afferents showed a range of transient responses during rapid changes in head velocity. The afferents with the most regular spontaneous discharge had little overshoot in firing rate. Afferents with less regular discharge had large overshoots in firing; the peak change in firing was 2-6 X the steady-state change. We suggest that the large overshoot in eye velocity when VOR gain is low represents the contribution of vestibular signals from afferents with large transient responses.(ABSTRACT TRUNCATED AT 250 WORDS)     

Responses of neurons in the medial superior temporal visual area to apparent motion stimuli in macaque monkeys

Monkeys fixated a stationary spot during presentation of dot textures that moved in apparent motion defined by the spatial and temporal separations, Deltax and Deltat, between successive flashes of each dot. For each neuron, we assessed the speed tuning for smooth motion (Deltat = 2 or 4 ms) at speeds < or =128 degrees /s and the effect of varying the value of Deltat at speeds of 16 and 32 degrees /s. Many medial superior temporal (MST) neurons, like middle temporal (MT) neurons, were tuned for the speed of smooth motion and showed decreases in firing rate as the value of Deltat increased at a constant speed. A subset of MST neurons, however, showed monotonically increasing firing rates as a function of smooth stimulus speed and responses to apparent motion that paralleled a previously discovered illusion where estimates of target speed increase with the value of Deltat. Opponent firing rate, defined as the difference between responses for motion in the preferred and opposite directions, peaked at values of Deltat that were consistent with the behavioral illusion. Comparison with a new sample of MT neurons recorded with the same stimuli failed to reveal comparable effects. Attempts to map the population responses in MT and MST onto the behavioral illusion of increased speed succeeded by averaging the opponent response across MST neurons, but only by applying vector averaging to determine the preferred speed of the most active MT neurons. We suggest that a vector-averaging computation transforms MT's place code for target speed into the rate code of some MST neurons.     

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.     

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.