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Howard Hughes Medical Institute, W. M. Keck Foundation Center for Integrative Neuroscience, Department of Physiology, University of California, San Francisco, California
Submitted 21 April 2008; accepted in final form 20 June 2008
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Smooth pursuit eye movements are subject to learning when an ongoing target motion changes either speed (Kahlon and Lisberger 2000
) or direction (Boman and Hotson 1992; Medina et al. 2005). Under typical pursuit learning conditions, a change in target motion provides a large visual motion signal because the tracked target suddenly moves at a different speed or in a different direction relative to the eye. Approximately 100 ms later, the image motion drives a rapid change in eye velocity. If the same target motion, and therefore the same instructive signal, is provided repeatedly, then a learned response gradually appears at a time that anticipates changes in target motion. In a recent paper, our laboratory showed that learning was instructed when sensory stimulation was replaced by microstimulation in the sensory input to the pursuit circuit from extrastriate visual area MT, indicating that sensory signals were sufficient to instruct learning (Carey et al. 2005). To examine the necessity of sensory errors for instructing pursuit learning, we now ask whether learning occurs when we attempt to instruct learning with electrical stimulation in motor parts of the pursuit circuit.
There are likely to be multiple sites of learning in the pursuit system, and the floccular complex of the cerebellum has been implicated as one of them (Kahlon and Lisberger 2000). Purkinje cells in the floccular complex show strong modulation of simple spike firing rate during pursuit, and inputs to the floccular complex converge (via the pontine nuclei) from both the visual motion pathways of MT and MST and the motor-related outputs from the smooth eye movement region of the frontal eye fields (FEFSEM) (Leichnetz 1989; Robinson and Fuchs 2001). Available evidence does not point toward MT or the FEFSEM as likely loci of learning. However, stimulation of MT instructs learning (Carey et al. 2005), and learning is expressed in the eye movements that result from stimulation of the FEFSEM (Chou and Lisberger 2004). These data imply that outputs from both MT and the FEFSEM are transmitted through a locus of learning. Thus the motor signals that arise from the FEFSEM could instruct learning, as do the sensory signals that emanate from MT (Carey et al. 2005).
We tested the roles of sensory and motor error signals in pursuit learning by replacing the usual instructive change in target motion with electrical stimulation in either the cerebellum or the FEFSEM. Although no sensory error signal was provided, stimulation in the floccular complex (Belknap and Noda 1987; Lisberger et al. 1994a; Ron and Robinson 1973) and the FEFSEM (Gottlieb et al. 1993, 1994; Tanaka and Lisberger 2001) produced a change in eye velocity at a consistent time. Even when we prevented conflicting sensory signals during electrical stimulation by stabilizing the target with respect to the moving eye, stimulation in either the floccular complex or the FEFSEM failed to instruct learning. Our data suggest, with caveats related to the uncertainties of interpreting negative results from electrical stimulation experiments, that sensory error signals are necessary to instruct learning in pursuit eye movements.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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). Two monkeys had recording chambers placed stereotaxically over the right frontal eye fields; the other two monkeys had stimulating electrodes implanted chronically in the right floccular complex of the cerebellum. The methods for implanting floccular electrodes were the same as used by Lisberger et al. (1994b), and the monkeys also were used for brain stem recording experiments that are currently under preparation for publication. In one monkey (W), the stimulating electrode had been stable for 2 yr before our pursuit learning experiments were performed; in the other monkey (H), pursuit learning experiments were performed in the first 2 mo after stimulating electrode implantation. All procedures were approved by the Institutional Animal Care and Use Committee of the University of California, San Francisco, and were in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. Tracking stimuli and behavioral methods
Monkeys had been trained to sit in a primate chair with their head restrained while they fixated and tracked spots of light projected onto a screen in front of them in exchange for droplets of fluid. We used different experimental rigs and different visual displays for experiments performed in the FEFSEM versus in the floccular complex of the cerebellum. For the FEFSEM, targets were presented on an analog oscilloscope (Hewlett-Packard HP1304A) with a refresh rate of 250 Hz. The visual target was a small (0.3°) bright square. The display subtended 49° horizontally by 38° vertically at a viewing distance of 30 cm. Nominal spatial resolution of 216 pixels across the screen was achieved by driving the oscilloscope with 16-bit digital-to-analog converters on a digital signal processing board in our experimental control computers. For the cerebellum, the target was a bright circle of diameter 
0.5°, created by focusing the light beam from a fiber optic light source onto a pair of moveable mirrors and projecting the beam onto the back of a large tangent screen. The screen subtended 50 x 40° at a distance of 114 cm from the monkeys' eyes. The positions of the mirror galvanometers were controlled by the D/A converters in our experimental control computer. Both the fiber optic and oscilloscope target types have been used previously in studies of pursuit learning in this laboratory (Carey et al. 2005; Chou and Lisberger 2002), and no difference was noted with target type.
In some experiments, we applied an image stabilization technique (Morris and Lisberger 1987) in an attempt to eliminate retinal image motion resulting from small tracking errors or from driving the eye off the target with electrical stimulation in the brain. Stabilization was enabled selectively on stimulation trials in the learning block with the goal of exploring whether learning could be unmasked by eliminating visual instructive signals for pursuit learning at times when they might be competing with electrically induced signals. Our experimental control program allowed us to enable target stabilization selectively during electrical stimulation. To stabilize the target with respect to the moving eye, we drove target position with electronic feedback of eye position on a millisecond time scale. Because stabilization is only as good as the calibration of the eye coil, we endeavored to obtain excellent calibration in every experiment. In addition, we imposed stabilization in a few trials without electrical stimulation and used the absence of consistent eye accelerations or staircases of saccadic eye movements (Morris and Lisberger 1987) as independent verification of the accuracy of the calibration. Stabilization is never perfect, but we think that any stabilization errors were small and therefore were not likely to have any impact on the analyses presented here.
Experiments were divided into a series of trials, where each trial began with an interval of randomized duration from 600 to 1,800 ms when the monkey was required to fixate within 1–2° of a target at the center of the screen. The initial target motion then was provided by a standard "step-ramp" pursuit task (Rashbass 1961). The stationary target was displaced in one direction by 1–3° and then moved back toward the position of fixation at 10°/s (for floccular stimulation experiments) or 20°/s (for experiments in FEFSEM). Target velocity was chosen to optimize the initiation of pursuit and to ensure excellent tracking at the time the potentially instructive stimulus was delivered in each monkey. Target step size was adjusted for each monkey to minimize early catch-up saccades. During pursuit, the monkey was required to keep its eye within 5° of the target, or the trial was aborted and was not subjected to further analysis.
We used an electrical-stimulation version of the directional learning paradigm described in detail in prior papers (Carey et al. 2005; Medina et al. 2005). In each experiment, the monkey first completed a "preinstruction" block of 
100 trials to establish a control level of performance. In this block, 80% of trials provided target motion in the direction of target motion that would be used for subsequent instruction blocks; 5–20% of trials provided target motion in the opposite direction. In addition, 5–10% of the trials in this preinstruction block sometimes delivered electrical microstimulation to document the evoked eye movements before stimulation was delivered repeatedly in attempts to instruct learning.
Next, we ran an "instruction" block of 300–1,000 trials to assess whether electrical stimulation in the cerebellum or the FEFSEM could instruct learning. Now 80% of the trials were "instruction trials" that delivered electrical stimulation during step-ramp target motion in the direction chosen for the particular experiment, 10% of the trials were "probe" trials comprising the same target motion without electrical stimulation, and 2–10% of trials were catch trials in the opposite direction. Probe trials were identical to the trials presented in the preinstruction block. The potential instructive signal for learning was provided by microstimulation that began 200–300 ms after the onset of target motion and lasted for 75–300 ms, depending on animal and stimulus conditions. Fixation requirements were relaxed during the stimulation period for the instruction trials and during the corresponding epoch of the probe trials. Thus the monkey had an equal likelihood of obtaining a reward in all trials and was not punished for the imposition of electrical stimulation that drove his eyes off target albeit only by a small amount. In a few of the experiments where the target was stabilized during stimulation, we also included a small percentage of trials that delivered electrical stimulation during pursuit in the probe direction, but without target stabilization. We ran the instruction block for 
800–1,000 trials as long as the monkey continued to perform well and the stimulation evoked eye movements remained consistent. If the monkey completed 800–1,000 trials, then we transitioned to an "extinction" block consisting of 100–200 probe trials; otherwise, the extinction block was performed prior to the next experimental session. Extinction blocks were a luxury in the sense that we didn't observe any learning that needed to be extinguished, but we ran them at convenient times as a precaution. Within each block, all trial types were interleaved in pseudorandom order by our experimental control program. For all experiments, 80 preinstruction trials were used in calculating control performance; a minimum of 200 instruction and 20 postinstruction probe trials were averaged for evaluating learning.
For experiments with microstimulation in the FEFSEM, electrodes were introduced daily, and we chose the direction of target motion for instruction and probe trials on the basis of the eye movements evoked at the stimulation site. The goal was to select the direction of pursuit so that microstimulation caused eye movement orthogonal to the ongoing pursuit eye velocity. Due to the variable nature of the sites, some experiments were performed using stimulation evoked eye movements along the same axis as the ongoing pursuit. For experiments with stimulation in the floccular complex, the electrodes were implanted surgically so that the evoked eye movements were very similar from day to day. Again, the direction of target motion was chosen so that stimulation caused an orthogonal smooth eye movement. In addition, a few experiments used target motions along a cardinal axis not necessarily orthogonal to the eye movements evoked by floccular stimulation.
Electrical stimulation
All electrical stimulation was performed using a Grass S-88 stimulator controlling two constant-current SIUs configured to provide biphasic current pulses where each pulse was 0.2 ms in duration and the frequency of the stimulus train was 200 Hz. For floccular stimulation, we implanted a bipolar stimulating electrode (Peter Rhodes Medical Instruments, Woodland Hills, CA) at a location chosen on the basis of stereotaxic coordinates and refined by evaluating the horizontal eye movements evoked by stimulation as we drove the electrode through the cerebellum. The stimulus train duration was 300 ms and current amplitude was 30 µA. For monkey H, the stimulation was initiated 300 ms after target motion onset for both normal and target-stabilized conditions. For monkey W, stimulation occurred at 200 and 250 ms for normal and target-stabilized conditions. Because of the size of the stimulating electrode, we do not consider this to represent "microstimulation." Indeed the eye movements evoked by stimulation in the floccular complex with bipolar stimulating electrodes have proven to be remarkably consistent from monkey to monkey, whereas true microstimulation through a recording microelectrode evokes only small eye movements that are quite variable from site to site (Belknap and Noda 1987; Lisberger, unpublished observations). It seems likely that stimulation through the larger electrodes activates Purkinje cell axons strongly, whereas stimulation through the recording microelectrodes may be activating local elements in the cerebellar cortex, many of which inhibit Purkinje cells.
For microstimulation in the FEFSEM, electrodes were introduced daily. A transdural guide tube was inserted at known locations within a plastic coordinate grid system in the frontal recording chamber (Crist et al. 1988), and a tungsten microelectrode (Frederick Haer, impedance: 800–1,500 k/
) was advanced through the guide tube and into the arcuate sulcus using a hydraulic microdrive (Kopf Instruments). Because of the challenge of finding good smooth eye movement sites, we explored the relevant area of the arcuate sulcus quite thoroughly, and we are confident that our results reflect the organization of sites throughout the FEFSEM. Sites were selected for learning experiments when electrical microstimulation elicited a smooth pursuit eye motion of a consistent direction and speed. For both monkeys, stimulation occurred 250 ms after target motion onset and the stimulus current was set at 50 µA. For monkey L, train duration was 200 ms for both normal and target-stabilized conditions; for monkey D, trains longer than 75 caused a characteristic saccade back toward the target under normal tracking conditions. Therefore train duration was set to 75 and 150 ms for normal and target-stabilized pursuit in this animal. The times of electrical stimulation were chosen to maximize the chance of instructing learning: with natural stimuli, a change in target direction 200–300 ms after the onset of target motion is optimal for inducing directional learning in pursuit eye movements (Medina et al. 2005).
Data analysis
Eye position signals from the scleral search coil were differentiated by an analog circuit to obtain signals proportional to horizontal and vertical eye velocity. The circuit also served as a filter, differentiating frequencies <25 Hz and rejecting higher frequencies with a roll-off of 20 db/decade. Eye velocity and position signals were digitized at 1 kHz and stored for later analysis.
For each completed trial, eye position and velocity traces were displayed on a computer screen. The start and ending times of each saccade were marked using a combination of automated detection and visual inspection. The automated detection algorithm determined when a saccadic deflection of radial eye velocity rose above and fell below 50°/s and then defined saccade onset and offset as 15 ms before the first crossing and 15 ms after the second crossing. After automated detection, each trace was checked visually and saccade detection was corrected if necessary. Trials were discarded from further analysis if a saccade occurred either during the initiation of pursuit or in the first 100 ms after the onset of electrical stimulation, if there were excessive saccades (generally 3/ trial) or if a saccade occurred during the analysis window for responses to electrical stimulation. Remaining saccades, which were rare, were replaced by smooth segments of eye velocity that had been interpolated linearly between saccade onset and offset separately for horizontal and vertical velocities. Generally, <5% of trials were discarded for any experiment.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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As previously demonstrated (Lisberger et al. 1994a); Ron and Robinson 1973, microstimulation in the right floccular complex of the cerebellum induced eye velocity to the right, even during fixation of a stationary target. In the examples in Fig. 1, a 300-ms train of 30 µA pulses at 200 Hz produced 3°/s of horizontal eye velocity (top) toward the side of recording in both monkeys. Floccular stimulation also evoked upward eye velocity in both monkeys, although the vertical response was more pronounced for monkey H and smaller in monkey W. Because the electrodes were cemented in place for floccular stimulation, the responses to a given current remained consistent within each monkey over a period of months or even years. In both monkeys, we also knew from prior or subsequent recordings that stimulation through the same electrodes with single shocks caused monosynaptic inhibition of a group of neurons in the vestibular nucleus known as "floccular target neurons" (Lisberger et al. 1994a).
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) and stimulation in area MT (Carey et al. 2005) both cause changes in eye velocity that persist in postinstruction probe trials.
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To present the data in a way that we find intuitive and that unifies the separate horizontal and vertical eye velocity traces, we also created two-dimensional plots that show vertical versus horizontal eye position or velocity. For eye position, Fig. 3C shows that the eye started at straight ahead gaze (0,0) and moved upward and to the left under all conditions. However, because of the small effects of stimulation on eye position, there are only tiny differences among preinstruction (black), instruction (red), and postinstruction (blue) trials. For eye velocity, Fig. 3D shows that the initial trajectory was upward and to the left and was the same for preinstruction, instruction, and postinstruction trials. At the point indicated by the arrow, the eye velocity in the instruction trials (red trace) deviated substantially from the other two traces. However, the postinstruction trials (blue trace) and preinstruction trials (black trace) were the same throughout the response. If the instructional stimulus had been a change in target direction, then the postinstruction trace (blue) would have deviated from the preinstruction trace (black) even sooner than did the instruction trace (red) because the learned eye velocity anticipates the time of the stimulus that instructs learning (Medina et al. 2005). The two-dimensional plots have the advantage of showing the results of our experiments in a single view, along with the disadvantage that time is not represented explicitly. Temporal information can be gleaned from the eye velocity records in Fig. 3, A and B.
Figure 4 shows the course of pursuit responses over a full instruction block in one example experiment. Each line in a graph shows the response for an individual trial and uses a color scale to plot the residual eye velocity defined as the eye velocity in that trial minus the mean for the same target motion in the preinstruction block of trials. The instruction and probe trials were interleaved, but Fig. 4 plots them separately for both horizontal (left) and vertical (right) eye velocity to show the absence of any systematic changes in pursuit responses as the experiment proceeded from the top to the bottom of each graph.
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; Medina et al. 2005) and should appear as white and yellow in the residuals of eye velocity in postinstruction probe trials. Inspection of the plots of horizontal and vertical eye velocity for postinstruction probe trials reveals some variation in responses around the blue, vertical line drawn at 300 ms, but no sign of a consistent learned change.
To evaluate the effects of instruction on pursuit, we performed quantitative analysis only for postinstruction probe trials that occurred 100 trials into the instruction block (below the bold, blue, horizontal lines in each graph). Previous work has shown that pursuit learning emerges within the first 30–50 trials and stabilizes (Carey et al. 2005); limiting our analyses to later trials reduces the possibility that any small learning effects were being obscured by including early, and potentially unaffected, probe trials in the average. We inspected early probe trials as well and saw no indication that learning occurred in the trials prior to our analysis.
The apparent failure of electrical stimulation in the floccular complex to instruct learning in pursuit eye movements could reflect a competition between instructional signals in one direction from the electrical stimulation and instructional signals in the opposite direction from the visual image motion induced when stimulation dragged the eyes along at a velocity different from that of the target. In Figs. 3 and 4, the dip in middle of the eye velocity evoked by stimulation is presumably due to visual feedback, and these sensory signals could be in conflict with any instructive signals provide by electrical stimulation. We tested this possibility by stabilizing the target with respect to the moving eye during the period of electrical stimulation (see Carey et al. 2005; Morris and Lisberger 1987). In general, stimulation of the floccular complex induced somewhat larger eye movements during target stabilization (Fig. 5A) than during normal tracking, presumably because stabilization prevented visual feedback from reducing the stimulation effect. Further, the dip in eye velocity in the middle of the stimulation interval is much less pronounced, supporting our suggestion that the dip results from the use of visual feedback to overcome the retinal image motion created when stimulation drives the eye off target. Even under conditions of target stabilization, however, and even without the dip in eye velocity in the middle of the stimulation period, floccular stimulation still did not instruct learning. As shown in the two-dimensional plot of eye velocity in Fig. 5B, the average eye velocities evoked in postinstruction probe trials (blue) did not differ from those in preinstruction trials (black), even though electrical stimulation of the floccular complex caused a large deviation of eye velocity in instruction trials (red). Although time is not explicitly represented in the two-dimensional plot of Fig. 5B, the large symbols provide some temporal reference points by indicating eye velocity responses on the separate traces at the same times.
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Previous work from our laboratory showed that stimulation in area MT, within the sensory domain of the pursuit pathways, is sufficient to instruct learning in pursuit eye movements (Carey et al. 2005), suggesting that instructive signals may originate early in the pursuit circuit. Therefore we tested whether pursuit learning can be instructed by stimulation of the smooth eye movement region of the frontal eye fields (FEFSEM), which is a motor-related area earlier in the pursuit circuit than the cerebellum. Stimulation in FEFSEM induces smooth eye movements, and those eye movements are modified in parallel with visually instructed learning in pursuit (Chou and Lisberger 2004). Perhaps execution of eye movements induced by microstimulation in the FEFSEM provides sufficient instructive signals to downstream sites of learning.
We began each experiment by searching for a site in the FEFSEM where microstimulation through the electrode evoked consistent smooth eye movements. Sites were excluded if stimulation caused reliable or stereotyped saccades even if smooth pursuit was also evoked or if stimulation evoked eye movement along a direction that the animal pursued poorly (upwards for monkey L); this occurred infrequently. Sites also were discarded if the evoked eye movement drifted substantially in amplitude or direction over the course of the experimental session. To characterize stimulation sites, we used the approach explored thoroughly by Tanaka and Lisberger (2002) and stimulated during ongoing pursuit in different directions. As they reported, different sites had somewhat different patterns of effects, depending on the direction of the pursuit at the time of stimulation. At one extreme, stimulation evoked an increase in the amplitude of the eye velocity in the ongoing direction of pursuit (Fig. 7A) ; this site was in monkey D, for which we had to limit the duration of stimulation to 75 ms to avoid frequent saccades in the opposite direction from ongoing pursuit. The short pulse train generally evoked a distinct, biphasic effect on eye velocity; the initial increase was followed by a short period of slowing. At the other extreme, stimulation in the FEFSEM evoked smooth eye movement toward the side of stimulation (Fig. 7B) without regard for the direction of ongoing pursuit; this site was in monkey L, for whom we used longer pulse trains without eliciting a consistent saccade.
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), the absence of any change in the eye velocity at the time of microstimulation in the instructional trials (Fig. 9, A and D, filled symbols) provides additional evidence that learning did not occur. We also did not observe any change in eye velocity at the time of microstimulation in comparisons of the first and last 200 instruction trials except for some generalized slowing of pursuit responses. We conclude that stimulation of the FEFSEM did not instruct learning in pursuit eye movements.
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The four monkeys used in these experiments were veterans of experiments on pursuit learning and all showed strong learning in conditions where changes in the speed or direction of target motion were used as instructive sensory signals. Importantly, learning tests with natural stimuli employed changes in target motion at the same times as the application of electrical stimulation in the floccular complex and the FEFSEM: 200–300 ms after the onset of target motion, ensuring that the time of potentially instructive electrical stimulation was in a window where learning would normally occur. In addition, we verified in monkey D that stimulation in area MT instructed learning, as our laboratory had reported previously (Carey et al. 2005). The success of these control experiments indicates that our inability to induce learning through electrical stimulation of the cerebellar flocculus or the FEFSEM represents a genuine feature of the organization of the pursuit circuit and is not a consequence of a general failure of any of our monkey subjects to undergo pursuit learning or of an incorrect choice of the time of electrical stimulation.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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). Our goal in the present paper was to evaluate other potential areas and signals that might also have access to the instructive pathways for learning in pursuit. We have found that learning is not instructed by electrical activation of the outputs from either the floccular complex of the cerebellum or the FEFSEM.
Our criteria for results that would constitute learning instructed by electrical stimulation in the floccular complex or FEFSEM are based on the features of learning instructed by changes in the direction of target motion (e.g., Medina et al. 2005). When a target changes direction 200–300 ms after the onset of motion, learning is expressed during postinstruction probe trials in which the target simply moves continuously in its initial direction. The expression of learning starts before and reaches a peak near the time when the target would have changed direction. In the present experiments, we never found any evidence that instruction by electrical stimulation commencing 200–300 ms after the onset of target motion caused changes that persisted in postinstruction probe trials. Thus we conclude that electrical stimulation did not instruct the form of learning that occurs with natural stimuli.
We did see minor changes in eye velocity evoked by floccular stimulation as the monkey went through a sequence of instruction trials, but these changes did not persist in postinstruction probe trials and occurred too late relative to the onset of the instructive stimulus to be classified as the form or learning we have investigated. Thus while electrical stimulation might have been associated with some modest modifications in behavior, these did not fit the previously established criteria for behavioral learning in smooth pursuit eye movements.
Necessity of sensory errors
Previous work on motor learning in the pursuit system has used paradigms in which it was not possible to segregate the sensory and motor signals that might be used to instruct learning. When the learning paradigm involves an instructive change in the direction or speed of target motion, the initial learning stimulus provides sensory signals related to the imposed error as well as evoking an immediate motor response to the error, along with potentially instructive motor signals inside the brain. Motor instructive signals were not excluded even in a related study from our laboratory that used microstimulation in area MT to instruct learning, because activation of MT also caused a small smooth eye movement (Carey et al. 2005) and, again, the associated motor signals inside the brain. Still, we think that microstimulation in MT generates a primarily sensory signal, because it both exerts a directional effect on pursuit eye movements (Groh et al. 1997; Komatsu and Wurtz 1989) and biases perceptual judgments on a motion discrimination task (Salzman et al. 1992). In contrast, stimulation in the FEFSEM and the floccular complex produces motor signals that drive eye motion with quite short latencies of 25 and 10 ms, respectively. The successful instruction of pursuit learning from stimulation in area MT, combined with our failure to instruct learning with stimulation in the FEFSEM and the floccular complex, suggests that sensory signals are necessary, and possibly also sufficient, to instruct learning in pursuit.
We are suggesting that the failure of stimulation in the floccular complex or the FEFSEM to instruct learning reflects the organization of the pursuit pathways that instruct learning. Importantly, the stimulation was successful in evoking movement, showing that the stimulation effectively activated the floccular complex or the FEFSEM. However, negative results from electrical stimulation could have many causes, making it important to consider alternative interpretations. We do not think that the absence of an explicit reward for responding to the electrical stimulation can account for the absence of learning. First, the reward structure of our trials is the same as those that used a change in target direction (Medina et al. 2005) or electrical microstimulation in MT (Carey et al. 2005) to successfully instruct learning. The fixation requirements were suspended whenever the target changed direction or electrical stimulation was delivered, so that the monkeys were never punished for events that were outside their control, and they received rewards at the end of each trial for having eye position close to target position. Second, our attempts to induce learning by providing extra rewards only for larger or smaller eye velocities at a given time have not been very successful in modulating pursuit behavior (K. Bouchard and S. G. Lisberger, unpublished observations). Thus it is hard to imagine how reward contingencies could account for the failure of stimulation in the floccular complex or the FEFSEM to instruct learning.
If sensory signals instruct learning while motor signals do not, then one of the counterintuitive aspects of our results is the absence of learning in the direction opposite the eye movements induced by electrical stimulation. For example, a rightward smooth eye movement evoked by electrical stimulation causes leftward visual motion of the target. We might anticipate that learning would cause a leftward shift in eye velocity on probe trials. For stimulation in area MT, it was possible to segregate the learned component of eye velocity into two temporally distinct components. One component was in the direction of the eye movement instructed by stimulation in MT, and the other was in the opposite direction, instructed by the visual motion signals created when the electrical stimulation drove the eye away from the moving target.
The absence of sensory-instructed learning in the direction opposite to the eye movements evoked by stimulation in the present experiments cannot be attributed to competition with motor-instructed learning because the latter did not emerge when we eliminated sensory signals by stabilizing the target with respect to the moving eye during stimulation. It cannot be attributed to the small size of some of our stimulation effects because learning was instructed successfully in experiments where target speed or direction was altered with similarly small magnitudes either by target manipulation or by microstimulation in area MT (Carey et al. 2005). It also cannot be explained by a complete failure of sensory signals to alter the smooth eye movements evoked by electrical stimulation: at least for stimulation of the floccular complex, sensory signals are able to modulate eye velocity under non-stabilized target conditions, as seen in Figs. 3 and 4, even though the sensory signals do not instruct pursuit learning. Instead we suggest that stimulation of the floccular complex or the FEFSEM drives the system in a way that trumps conflicting sensory error signals, preventing learning from occurring even when appropriate sensory instruction signals are present.
In the floccular complex, electrical stimulation could be trumping sensory error signals by interfering with signal processing in the cerebellar cortex or one synapse downstream in the vestibular nucleus. Prior recording experiments have argued that the locus of learning may be in the floccular cortex (Kahlon and Lisberger 2000). Thus electrical activation of the floccular complex might be preventing any learning that normally occurs in the cerebellar cortex. This explanation fits with our conclusion that cerebellar output signals are not suitable for instructing pursuit learning. By analogy to eyelid conditioning (Mauk 1997) and adaptation of the vestibuloocular reflex (Lisberger 1994), another likely site of pursuit learning would be at the floccular target neurons in the vestibular nucleus. We might expect electrical stimulation in the cerebellar cortex to drive learning at the next synapse, but it might instead prevent learning by causing highly abnormal signals to be delivered to the floccular target neurons. Evidence that pursuit learning occurs in the floccular target neurons would turn this explanation into a plausible explanation for our finding that electrical stimulation of the floccular complex does not instruct pursuit learning.
In the FEFSEM, it seems unlikely that electrical stimulation trumps visual instructions for learning by disrupting neural signals immediately within the FEFSEM: some, and possibly all, pursuit learning occurs downstream from the FEFSEM, and microstimulation of the FEFSEM transmits some signals through a site of learning (Chou and Lisberger 2004). Thus microstimulation in the FEFSEM fails to instruct learning even though a site of learning receives the signals that arise from stimulation. One concern is that the FEFSEM has been implicated in multiple components of smooth pursuit and its output may not be a true motor command signal. For example, microstimulation in FEFSEM enhances the gain of pursuit eye movements and of the pursuit response to a given visual motion input (Tanaka and Lisberger 2001, 2002). A second concern is that electrical stimulation of the FEFSEM may not provide signals in a natural enough form to instruct pursuit learning. We have some hints that this may be a genuine problem because stimulation of the FEFSEM evokes responses in floccular Purkinje cells that seem to be unnatural in the sense that they cannot be explained simply by the tuning of Purkinje cells for smooth eye velocity (Roitman and Lisberger 2007). Either of these explanations is compatible with our suggestion that the failure of stimulation in the FEFSEM reflects the organization of the pursuit circuit and, in particular, of the pathways that instruct pursuit learning. We think that feedback signals related to eye movement impact the learning system differently than do feedback signals related to image motion.
Doing without learning
From introspection, it seems reasonable to think that we learn a motor skill by doing it and that we perfect it through doing it repeatedly. Although "practice makes perfect" may be true at the level of behavioral performance, our data imply that simply executing a pursuit eye movement is not sufficient to learn it, at least based on motor signals evoked by stimulation of the floccular complex of the cerebellum and the FEFSEM. Sensory error signals seem to be necessary, although concurrent motor activity also may be required. We performed the experiments reported here to better understand learning in pursuit eye movements and not to test any specific hypothesis of learning. Still, it is worth noting that our conclusions are entirely consistent with the cerebellar learning theory, in which signals arising over the climbing fiber system are instructive and cause learning through depression of parallel fiber inputs. Visual error signals are reported to the floccular complex through the climbing fiber system (Alley et al. 1975; Maekawa and Simpson 1972; Stone and Lisberger 1990), while signals related to ongoing motor activity are prominent in mossy fiber inputs (Lisberger and Fuchs 1978; Miles and Lisberger 1981). Climbing fiber inputs seem to be indicators of sensory events and to be unrelated to the motor commands. Thus the necessity of a sensory error signal to instruct learning, and the failure of signals that emanate from motor structures, could reflect the critical importance of the climbing fiber pathways or other purely sensory inputs to the pursuit circuit, in instructing motor learning.
It is worth noting that other forms of motor learning rely predominantly on sensory error signals rather than signals related to motor adjustments. For example, saccadic gain adaptation can be elicited in the absence of corrective saccades (Noto and Robinson 2001; Wallman and Fuchs 1998). Similarly, sensory errors seem to be sufficient to instruct adaptation of visually guided reaching (Tseng et al. 2007); adding corrective motor adjustments in conjunction with visual error during a reaching task did not influence the amount of adaptation. Because of the ease of studying the neural basis for eye movements, pursuit seems like an excellent system for demonstrating the neural mechanisms of the more general phenomenon of motor learning induced by sensory instruction signals.
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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FOOTNOTES |
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Address for reprint requests and other correspondence: H. W. Heuer, Dept. of Physiology, Box 0444, UCSF, 513 Parnassus Ave, San Francisco, CA 94143-0444 (E-mail: heuer{at}phy.ucsf.edu)
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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