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1Cognitive Neurology, Hertie-Institute of Clinical Brain Research, University of Tübingen, Tübingen; and 2Section for Experimental Anesthesiology, Department of Anesthesiology and Critical Care Medicine, University of Freiburg, Freiburg, Germany
Submitted 15 March 2006; accepted in final form 19 October 2006
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ABSTRACT |
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INTRODUCTION |
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; Ilg et al. 2004; Kawano et al. 1994; Newsome et al. 1988; Thier and Erickson 1992) and in motion perception (Britten and van Wezel 1998, 2002; Celebrini and Newsome 1994, 1995; Heuer and Britten 2004; Ilg and Churan 2004) are well documented.
Area MST receives input from the middle temporal area (MT) (Maunsell and van Essen 1983; Ungerleider and Desimone 1986), which is believed to carry retinal image motion signals (Lisberger and Movshon 1999). Area MST consists of two subareas: a dorsal subarea and a lateral subarea (Komatsu and Wurtz 1988). The dorsal part (MST-d) is essential for decoding optic flow (Duffy and Wurtz 1991). The decoding of optic flow is of special relevance for differentiating self-induced and external induced retinal image motion (Zemel and Sejnowski 1998) as well as for estimating heading direction (Hamed et al. 2003; Page and Duffy 2003). On the other hand, the lateral part (MST-l) is important for decoding object motion in space. To recover object motion in space, extraretinal information related to ongoing eye and head movements is added to retinal image motion signals of the tracked target (Ilg and Thier 2003; Ilg et al. 2004; Kawano et al. 1994; Newsome et al. 1988; Thier and Erickson 1992). As a result, the neuronal activity of a group of neurons in area MST-l represents target movement within an external frame of reference (Ilg et al. 2004).
Based on the results of oculomotor and manual tracking of human subjects in two dimensions, it was earlier hypothesized that manual tracking and smooth-pursuit eye movements use similar control signals and depend on a common neural resource (Engel and Soechting 2000; Engel et al. 1999). In addition, the control strategies for directing the hand and the eyes toward moving targets shared similar dependencies on target predictability (von Donkelaar et al. 1992). The common neural resource might include area MST because it was previously shown that the population vector recorded from area MST represents the target trajectory during a manual-tracking task (Kruse et al. 2002). Taken together, an obvious question is whether area MST is a specific preprocessor for visual motion used exclusively for the execution of smooth-pursuit eye movements or, alternatively, whether MST processes visual motion guiding eye and hand movements.
The approach taken here is to initially replicate earlier findings on the role of MST-l for smooth-pursuit eye movements. Based on these results, we then investigate whether MST-l is also important for generating goal-directed hand movements.
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METHODS |
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), they were implanted with a head post, recording chambers, and a search coil beneath the conjunctiva. All animal procedures were carried out in accordance with the guidelines established by the National Institutes of Health and German law and were approved by the local ethics committee. The center of each recording chamber was aimed at the lateral parts of area MST (stereotactic coordinates: lateral 19, posterior 3.5, and dorsal 16 mm). The axis of the chamber was tilted 30° upward with respect to the horizontal in a parasagittal plane. The first penetrations in each hemisphere were performed in the center of the chamber. Well-established single-unit response properties were used to further refine the location of area MST and its two major subdivisions, the dorsal one (= MST-d) and the lateral one (= MST-l) in the individual hemisphere as well as the boundary with neighboring area MT (Komatsu and Wurtz 1988). Details of the single-unit responses recorded from MST of these monkeys were published in an earlier work (Ilg et al. 2004). Experimental setup
VISUAL STIMULATION. The visual stimulation was generated by a PC (1,280 x 1,024 pixels, 60-Hz refresh rate) and back-projected (NEC XG-1101G) onto the touch screen (width 49°, height 30°) that was mounted at a reachable distance (0.33 m) for the monkeys. Targets for eye movements were red dots (luminance 0.5 cd/m2, diameter 0.5°) and targets for hand movements were white dots (same luminance and diameter). The stimulation computer was synchronized with a second personal computer for data acquisition. All experiments were performed in a completely dark chamber. The monkeys could see neither the borders of the screen nor the screen itself. To prevent dark adaptation of the monkeys, bright light-emitting diodes (LEDs) were switched on when the liquid reward was provided at the end of each correct trial.
EYE MOVEMENT RECORDINGS.
Horizontal and vertical eye positions were measured using implanted search coils (Judge et al. 1980; Robinson 1963). These analogue signals were low-pass filtered at 500 Hz and sampled at a rate of 1 kHz.
HAND MOVEMENT RECORDINGS. Accuracy of the goal-directed hand movements was determined by means of a touch screen (AccuTouch, Elo Touch Systems) connected to the serial port of a PC. The temporal resolution of the touch screen was 60 Hz, identical to the refresh rate of the visual stimulation. We determined the horizontal and vertical finger positions on the touch screen in addition to the onset time and offset time of the reaching movement. Because the experiments were performed in total darkness, the monkeys could not see their hands during the pointing movement.
To monitor the monkeys, their actions, and some possible consequences of the mircrostimulation, we used infrared (IR) illumination to enable video control of our monkeys in total darkness.
Experimental paradigms
EYE MOVEMENT STUDY. Various saccade and pursuit paradigms were used in this study. All eye movement paradigms began with a fixation period of 1 s (see Fig. 1 A). To minimize the effect of anticipation (despite this fixed period), we randomized either target position or direction of target movement from trial to trial.
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In the saccade paradigm, a stationary target was displayed at one of eight possible locations (eccentricity 10°) after the fixation target disappeared. The size of the gaze control window was adjusted to the difficulty of the actual task (4–8°). If the monkey's gaze remained within the control window, the animal received a liquid reward (about 0.1 ml/trial) at the offset of each correct trial. If the gaze left the control window, the actual trial was instantly aborted and the data were discarded.
HAND MOVEMENT STUDY. In the hand movement task, the monkey had to touch a sensor in its chair to start the next trial. In other words, each hand movement trial started with the monkey's hand located in a constant, predefined position in space. After a random fixation period of 500 to 1,000 ms, the moving target appeared on the screen (see Fig. 1B). The target appeared at a random position (between center of screen and its border opposite to its direction of movement) and moved at 10°/s along one of the cardinal axes. When the fixation target's color changed from red to blue (randomized 200 to 500 ms after the onset of the moving target), the monkey had to perform a reaching hand movement toward the moving target. Once the monkey's hand left the sensor in its chair, the moving target was switched off. The analysis of our video material revealed that the monkeys usually touched the surface of the screen with the knuckle of their right index finger. The monkey had to maintain fixation throughout the entire trial; violation of fixation yielded instantaneous trial abortion. To instruct the monkeys to perform hand movements as precisely as possible, the amount of reward depended on the size of the pointing error (approximately between 0.1 and 0.6 ml/trial), which was computed as the difference between current target and finger position. The monkeys never received feedback information related to target and finger position.
Microstimulation protocol
Microstimulation was applied with the same electrode used for the single-unit recordings. We never observed a change of the electrode impedance as a consequence of the stimulation. In the eye movement study, we applied microstimulation (WPI Stimulus Isolator A365) for 200 ms (200-Hz, bipolar pulse length 200 µs, strength from 50 to 
80 µA), 200 ms after target movement onset. During microstimulation, the target for eye movements was either switched off or remained visible. For the hand movement study, microstimulation (with the same parameters as in the eye movement study) began in synchrony with the GO signal and ended when the monkey touched the screen (or after a maximum period of 500 ms). Note that there was a temporal overlap between microstimulation and target presentation during the manual reaction time of every individual trial.
In pilot hand movement experiments (see Fig. 2), we observed no effects of microstimulation on the hand movements if the target was visible during the reaching period. Therefore we switched off the target as soon as the hand left its initial predefined position. As Fig. 2 shows, the mean of the two-dimensional (2D) Gaussian function was not affected by this manipulation. Only the width of this function increased during open-loop pointing.
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To inject small amounts of muscimol into area MST, we replaced the electrode by a stainless steel canula through which a glass pipette (tip diameter of about 50 µm) approached area MST exactly at sites previously explored by single-unit recordings. The pipette was glued onto a Hamilton syringe and was filled with muscimol solution (5 mg/ml in H2O). The Hamilton syringe itself was filled with paraffin. In one experiment per hemisphere, fluorescent latex microspheres (Lumafluor) were added at the tip of the pipette to reconstruct the center of the injection, in which 4 µl was slowly injected over about 30 min. After a delay of 30 min, the pipette was removed. The behavioral testing was performed only after the micropipette had been removed and the chamber had been closed again. To ensure that we did not measure long-lasting effects of the muscimol, we performed these injections only every other day.
Data processing
All data processing was performed using self-written scripts together with the available toolboxes in Matlab.
EYE MOVEMENTS. We obtained single trial eye velocity by differentiating and low-pass filtering the eye position profiles. Saccades were automatically detected according to an acceleration threshold algorithm. Saccade parameters such as latency, duration, amplitude, and peak velocity were determined. Eye velocity profiles of single trials were kept empty over the duration of the saccade (i.e., the eye velocity values were replaced by the arithmetic representation of not-a-number) to guarantee that saccades did not influence any other parameter.
In addition to saccade detection, presaccadic pursuit initiation was determined based on the eye velocity profiles of single trials. At the time of the initial saccade, the initiation of pursuit is complete and eye velocity is very precisely matched to target velocity (Carl and Gellman 1987; Lisberger 1998). Therefore we decided to use postsaccadic eye velocity to quantify the effect of microstimulation.
We aligned single trials (10 per condition) to the offset of the initial saccade. Subsequently, we averaged eye velocity over a period of 50 ms immediately after the offset of the initial saccade. The vector difference between postsaccadic eye velocity in stimulated and control trials was used to determine the stimulation effect for a given pursuit direction. The stimulation vector was computed by adding the vectors obtained from pursuit along cardinal axes.
Steady-state pursuit velocity was computed by averaging desaccaded eye velocity from the onset of pursuit until the end of trial. Subsequently, averages were computed for all trials with a given target velocity (from 5 to 30°/s).
Single-trial pursuit onset latencies were determined by a threshold algorithm applied to the eye acceleration profiles.
HAND MOVEMENTS.
Hand movements were quantified by the following parameters: the time the monkey's hand left the initial sensor (hand movement latency), the time the finger hit the touch screen (movement duration, taken as the difference between hit and latency), and the position of the finger on the touch screen. From this position, we calculated the pointing error as the difference between the actual target position and the landing position. The histogram of this pointing error, based on 160 single trials in which the target moved in one of the four cardinal directions, was fitted using the Matlab function lsqnonlin to a 2D Gaussian function
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COMPARISON OF DIRECTIONS.
To compare the preferred direction of the pursuit-related activity at a given stimulation site and the direction of the stimulation vector on eye and hand movements, we performed two analyses. First, we computed the angle between the preferred direction and the stimulation vector and built a histogram of the angles. Second, we calculated the circular correlation (Fisher 1995) between preferred direction and stimulation vector using the Oriana2 software package (Kovach Computing Services, Anglesey, Wales) and determined whether this correlation was significant.
Anatomy
After execution of these experiments, the monkeys were killed and their brains were cut frontally into 50-µm sections. Among others (in total eight series), the sections were stained for cell bodies (cresyl violet) or myelin (Gallyas), the latter to delineate the borders of area MT in the posterior wall of the superior temporal sulcus (STS), resulting in a spacing between two adjacent stained sections of 400 µm. The reconstruction of both stimulation and muscimol injection sites was based on relating microdrive readings to the locations of fluorescent beads and visible traces of the electrode tracks. This confirmed that the manipulations in all three hemispheres were directed toward the lateral part of area MST, located in the fundus of the STS anterior to area MT.
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RESULTS |
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A typical effect of microstimulation in MST-l on pursuit eye movements is shown in Fig. 4 at the site where the pursuit response presented in Fig. 3 was recorded. If we stimulated during the execution of smooth-pursuit eye movements, we observed an increase of eye speed whenever the monkey performed pursuit in the preferred direction (rightward and downward, –25°) of the stimulated site (see red arrow in Fig. 4B). Latencies of the eye movement were not affected by the microstimulation. In the example shown, the pursuit onset latencies without stimulation were 145 and 153 ms (SD 11 and 19 ms, respectively) in stimulated trials (n.s., t-test, P = 0.2967). The latency of the initial saccades was 372 ms (SD 36 ms) without stimulation and 377 ms (SD 25 ms) in stimulated trials (n.s., t-test, P = 0.77). After the cessation of stimulation, the monkey corrected for the stimulation-induced offset in eye position by backward-directed saccades (see black arrow in Fig. 4B).
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On average, the absolute value of the stimulation vectors for all 93 sites with a significant effect was 0.85°/s (SD 0.39°/s) if the target was switched off during stimulation and 0.67°/s (SD 0.45°/s) if the target was continuously visible (see Fig. 7). In other words, in the transient absence of the pursuit target, microstimulation elicited a 27% larger effect. This difference was highly significant (P = 0.0048, t-test).
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In contrast to the effect on postsaccadic eye velocity, microstimulation did not affect the latency of the initial saccade [n = 93; mean control latency 392 ms (SD 28 ms), stimulated latency 412 ms (SD 52 ms), t-test: P = 0.1571]. Pursuit onset latency was also not affected by microstimulation (see Fig. 11, left).
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The errors in hand movements were fit by a 2D Gaussian function as shown earlier (see Fig. 2). When we stimulated during a hand movement trial, the landing position of the finger deviated toward the preferred direction of the stimulated site (see Fig. 8, A and B). Of 39 tested stimulation sites in area MST-l of the two monkeys, we found 28 sites with significant effects on the pointing error (t-test, P < 0.05). The mean of the absolute values of the stimulation-induced shift in pointing was 1.6° (SD 1.7°, n = 28). At these sites, we found significant effects of the microstimulation on the postsaccadic eye velocity. Note that the fixation of the eye was not affected by microstimulation in this condition (t-test of eye position, n.s., P > 0.05 after Bonferroni adjustment). We did not observe a significant effect of microstimulation on hand movement onset latency [stimulation: 245 ms (SD 84 ms); control: 250 ms (SD 87 ms)] or on hand movement duration [stimulation: 267 ms (SD 17 ms); control: 267 ms (SD 18 ms); n.s., P > 0.05 after Bonferroni adjustment for multiple comparisons].
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Finally, we asked whether stimulation in MST triggered any other reaction in our monkeys. Based on the inspection of our video material, we never observed any motor response to the microstimulation other than the effects on eye and hand movements described above.
Specific effects of transient MST inactivation
Having documented the effects of an artificial increase in neuronal activity on goal-directed behavior, we next addressed the effects of an artificial decrease in neuronal activity in area MST-l. We performed transient lesions by injections of small amounts of muscimol (<4 µl) at previously explored sites in area MST-l. Typical examples of prelesion and postlesion pursuit eye movements are shown in Fig. 9. Steady-state pursuit velocity to the left (contraversive) was not affected by the injection of muscimol, whereas steady-state velocity to the right (ipsiversive) was clearly reduced.
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The deficit in steady-state pursuit eye velocity was the only clear and robust effect of the muscimol injections on the monkeys' eye movements. For the other parameters (pursuit onset and initial saccade latency), we observed a rather idiosyncratic pattern of effects after each injection. There was a slight individual difference in pursuit onset latency for our monkeys: the latency of monkey BH was 117 ms (SD 15 ms, average across all control conditions shown in Fig. 11), whereas monkey GH started pursuit after 96 ms (SD 6 ms) after the onset of target movement. When we analyzed the effect of transient lesions (see Fig. 11), we found in two of three injected hemispheres (left hemisphere in BH and right hemisphere in GH) that the pursuit latency increased if the target moved to the contralateral side. Obviously, this increase can be explained by a position effect or scotoma contralateral to the injection, although it cannot be explained by a direction effect. Lesion of the left hemisphere in GH resulted in a significant increase of pursuit latency for both directions of target movement, suggesting the coexistence of a position effect and a direction effect.
We asked whether the changes in pursuit onset latency were also present in the latency of the initial saccades during pursuit initiation. Figure 12 gives the latencies of leftward and rightward saccades after inactivation of the right or left MST, respectively, together with the prelesion control values. Again, there was a slight difference in latency between our monkeys. In contrast to pursuit onset latencies, saccade latency in monkey BH [355 ms (SD 24 ms), average across all control conditions] was slightly shorter than that for monkey GH [452 ms (SD 26 ms)].
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Finally, to see whether these changes in saccadic latencies were linked to target motion or to target position, we also analyzed saccades toward stationary targets. However, the latency as well as the gain of these saccades did not show a clear lesion-dependent behavior, as shown in Fig. 13.
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In contrast to the unspecific effects on saccadic latency and gain, we observed consistent effects of microstimulation on goal-directed hand movements. There was a shift of the landing position toward the left visual field for injections into area MST-l of the right hemisphere (see Fig. 14). The shift in landing position was present and significant (P < 0.0001) for all 14 injection sites. In contrast to the directionally selective deficit in pursuit eye movements, this shift in pointing error toward the contralateral visual field did not depend on the direction of target movement. Figure 14, D and E gives the reaching error for both leftward and rightward moving targets. It is important to note that the prelesion pointing error depends on target movement direction: leftward target motion yielded an error to the left and vice versa. However, the difference in the horizontal component of the pointing error when the target moved ipsiversively compared with when it moved contraversively was not significant (t-test, P = 0.14, all 14 injection sites).
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DISCUSSION |
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; Groh et al. 1997; Komatsu and Wurtz 1989). The deficit in steady-state eye velocity exclusively for ipsiversive target movement also agrees with earlier findings in monkeys (Dursteler and Wurtz 1988; Yamasaki and Wurtz 1991) and with the description of patients suffering from unilateral lesions of the posterior parietal cortex (Leigh and Tusa 1985; Morrow and Sharpe 1990; Thurston et al. 1988). The similarity between the results from the literature and ours is far from trivial because in the older studies, chronic lesions were made. In the case of chronic lesions, there is a possibility of reorganization and recovery of function (Yamasaki and Wurtz 1991). In case of transient lesions, the recovery is attributed to the disappearance of the lesion itself. Further support of the extraretinal signals in MST
We obtained larger effects of microstimulation on pursuit eye movements in the temporary absence of the target. As previously shown, MST-l neurons respond during the execution of pursuit eye movements to retinal image motion and eye movement (Ilg et al. 2004). Therefore in the transient absence of the target, the artificial, stimulation-induced activity solely competes with the eye movement signal. In contrast, during the presence of the pursuit target, the artificial activity has to compete against retinal image motion and eye movement signals. The fact that the neuronal activity of MST is determined by retinal image motion and by extraretinal signals related to the executed eye movements was recently also documented in humans by means of functional magnetic resonance imaging (fMRI) (Goossens et al. 2006). With respect to goal-directed hand movements, we failed to observe an effect of stimulation when the target was continuously present. In this condition, the monkeys most likely did not produce a ballistic hand movement based on a feedforward mechanism (Ariff et al. 2002); instead they likely used on-line visual feedback to direct their hand (Saunders and Knill 2005).
Phosphenes—attention—general disturbance
One might question whether our stimulation effects can be explained by phosphenes elicited by the microstimulation, i.e., that the monkeys simply directed their gaze and hand toward a phosphene. For stimulation in area V1, there is evidence that phosphenes are generated by microstimulation with parameters similar to those we used in our study (for review see Bradley et al. 2005; Tehovnik et al. 2005). However, there are two strong arguments against the idea that phosphenes played a role in our experiments. First, we never observed an effect during stationary fixation. During execution of pursuit, the sensitivity of the eye movement control system is greater than that during stationary fixation (Schwartz and Lisberger 1994). Second, the latency of the stimulation effects would be much longer if the monkeys reacted to phosphenes.
Microstimulation could have either disturbed mechanisms engaged in the focal direction of attention or generally disturbed the monkey by eliciting some level of discomfort. Neither explanation accounts for our findings because microstimulation did not simply reduce the accuracy of goal-directed behavior, but modified this behavior in a highly directional selective manner. In addition, we did not observe any changes in latency arising from microstimulation, which would be a clear indication of change in attentional state.
Recently, it was reported that microstimulation in MT resembles the learning of consistent changes in target trajectory (Carey et al. 2005). However, there is a clear argument that our results cannot be explained by mechanisms of motor learning: because stimulated and control trials were randomized, there was no consistent drive for learning mechanisms.
Finally, one might also ask whether our effects are explained by a specific impairment of the motion processing or, alternatively, by a more general impairment. The answer to this question is limited by the extent of our experimental data. If the effects arose from an impairment of motion processing, saccades or hand movements elicited by stationary targets should not have been affected by the microstimulation in MST. On the other hand, speed judgments addressed in psychophysical experiments should also have been affected. However, with respect to MST deactivation, gain and latency of saccades directed toward stationary target did not show a clear effect (see Fig. 13). This indicates that we indeed observed a specific impairment of motion processing. Further support of this notion is provided by the similarity of the effects of artificial activation and deactivation of MST on eye and hand movements, together with the clear correlation between the preferred pursuit direction and the stimulation vector.
Differentiation between effective and ineffective sites of microstimulation
The difference between effective and ineffective stimulation sites might be explained by the presence of cortical columns containing neurons with similar response properties (Mountcastle 1957). Effective sites—that is, sites at which microstimulation resulted in significant changes in postsaccadic eye velocity—were found when the position of the microelectrode was centered within a single cortical column or cluster in area MST (see Britten 1998). In this case, only neurons with similar properties were activated and therefore an effect on the ongoing eye or hand movement was detectable. Ineffective sites—that is, sites at which microstimulation did not produce significant changes in eye velocity—resulted from an electrode position close to the border between two columns, thereby stimulating neurons with different response properties. However, because we do not have experimental data supporting the hypothesis of a columnar or clustered structure in MST-l, this explanation remains speculative.
A second and alternative explanation for the existence of ineffective stimulation sites relates to the fact that extraretinal responses of MST neurons are selective not only for direction, but also for velocity (Churchland and Lisberger 2005b). If the preferred velocity of a given stimulation site would have been close to target velocity (10°/s), stimulation would not have been effective. Otherwise, we can assume that effective sites are characterized by representing higher preferred velocities as 10°/s. Because we did not determine the preferred velocity of each stimulation site, this explanation is similarly speculative as the first explanation.
Size of affected tissue
Microstimulation and injections of muscimol most likely affected different amounts of tissue in area MST-l. Microstimulation at effective sites most likely affected neuronal activity within a single cortical column. Assuming passive spread of current, it can be approximated that stimulation at 80 µA (used at most sites) affected cortical tissue within a radius of 0.1 mm (Stoney et al. 1968). However, a recent study using fMRI to reveal the size of the affected tissue showed that tissue within a radius of up to tenfold greater may have been affected (Tolias et al. 2005). The size of a column in area MST was estimated to be about 0.5 mm (Britten 1998). The amount of tissue affected by the muscimol injection was much larger; autoradiographic estimation of the extent of affected tissue (Martin 1991) suggests a radius of up to about 3 mm. Therefore the effect of the transient lesions on eye movements was a result of the reduction of activity within a large portion of MST-l in the targeted hemisphere, definitively not only of a single cortical column or cluster.
Common substrate of eye and hand movement control
This processing of visual motion is related not only to the generation of smooth-pursuit eye movements, but also to the generation of hand movements directed toward a moving target. As explained in the INTRODUCTION, there are arguments for a common neuronal substrate for eye and hand movements (Engel and Soechting 2000; Engel et al. 1999; von Donkelaar et al. 1992). In the same vein, it was previously shown that the population vector of area MT and MST represents the target trajectory during a manual-tracking task (Kruse et al. 2002). Similar results were obtained in a recent fMRI study addressing brain activity when subjects performed either eye or hand movements (Oreja-Guevara et al. 2004): hMT+ was similarly activated during both tasks. In addition, it was recently shown that disturbing processing in the posterior parietal cortex by transcranial magnetic stimulation (TMS) prevents subjects from adapting to a velocity-dependent force field in a manual-tracking task (Della-Maggiore et al. 2004). These results, together with our own results, indicate that MST plays a role in the generation of goal-directed eye and hand movements. The question that arises here is how does the information from MST in the extrastriate cortex reach the motor cortex? There are two possibilities that need to be considered: first, cortico-cortical projections may enable the information transfer. Projections from MST to the frontal eye field are well documented (Boussaoud et al. 1990; Churchland and Lisberger 2005a). Alternatively, and more plausibly, the cortico-ponto-cerebello-thalamo-cortical pathway might be responsible for the information transfer (Ramnani 2006). There are projections from MST to the pontine nuclei (Hoffmann et al. 2002; Ilg and Hoffmann 1993). Single-unit recordings from pontine nuclei have demonstrated responses to eye and hand movements (Matsunami 1987; Tziridis et al. 2004). Furthermore, Purkinje cells in the cerebellum are driven during manual tracking (Roitman et al. 2005) and during pursuit (Lisberger et al. 1987). Finally, the information could be sent from the cerebellum by thalamic relay to the motor cortex (Kelly and Strick 2003). It remains up to future polysynaptic connectivity studies to prove or disprove this possible scheme of cortico-cortical information transfer.
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GRANTS |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: U. J. Ilg, Cognitive Neurology, Hertie-Institute of Clinical Brain Research, University of Tübingen, Otfried-Müller Str. 27, D 72076 Tübingen, Germany (E-mail: uwe.ilg{at}uni-tuebingen.de)
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I(0,k)] exp{k[cos (x – T)]}. Arrow gives the preferred direction. Gray circle shows spontaneous activity measured during initial fixation of the stationary target.
10 trial repetitions. Width of the gray band gives the SD of prelesion steady-state eye velocity, centered at its mean value. Note that the steady-state pursuit velocity was reduced compared with prelesion data only if the target moved toward the lesioned side.
