The Smith-Kettlewell Eye Research Institute, San Francisco, California 94115
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ABSTRACT |
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Missal, M. and S. J. Heinen. Facilitation of Smooth Pursuit Initiation by Electrical Stimulation in the Supplementary Eye Fields. J. Neurophysiol. 86: 2413-2425, 2001. The role of the supplementary eye fields (SEF) during smooth pursuit was investigated with electrical microstimulation. We found that stimulation in the SEF increased the acceleration and velocity of the eyes in the direction of target motion during smooth pursuit initiation but not during sustained pursuit. The increase in eye velocity during initiation will be referred to as pursuit facilitation and was observed at sites where saccades could not be evoked with the same stimulation parameters. On average, electrical stimulation increased eye velocity by ~20%. At most sites, the threshold for a significant facilitation was 50 µA with a stimulation frequency of 300 Hz. Facilitation of pursuit initiation depended on the timing of stimulation trains. The effect was most pronounced if the stimulation was delivered before smooth pursuit initiation. On average, eye velocity in stimulation trials increased linearly as a function of eye velocity in control trials, and this function had a slope greater than one, suggesting a multiplicative influence of the stimulation. Stimulation during a fixation task did not evoke smooth eye movements. The latency of catch-up saccades was increased during facilitation, but their accuracy was not affected. Saccades toward stationary targets were not affected by the stimulation. The results are further evidence that the SEF plays a role in smooth pursuit in addition to its known role in saccade planning and suggest that this role may be to control the gain of smooth pursuit during initiation. The covariance between pursuit facilitation and the timing of the catch-up saccade as a result of stimulation suggests that these different eye movements systems are coordinated to achieve a common goal.
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INTRODUCTION |
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Smooth pursuit eye
movements allow primates to follow moving objects with the eyes (for
review, see Krauzlis and Stone 1999). If a target of
interest starts to move, the eyes accelerate after a short delay
(80-100 ms) in the direction of target motion, and eye velocity
increases to match target velocity (in ~200 ms). During this smooth
eye acceleration, a saccade is often generated to reduce the error
between eye and target positions that is introduced by reaction delays
in the oculomotor system. The initial eye acceleration during pursuit
initiation depends on physical factors like target velocity on the
retina and the nature of the visual background (Keller and Khan
1986
; Lisberger et al. 1987
). In addition to retinal factors, smooth pursuit is influenced by extraretinal factors
like attention (Ferrera and Lisberger 1995
) and
expectation of future target motion (Kowler 1989
).
The neural control of visually guided smooth pursuit has been
extensively studied, and the role of different subcortical and cortical
structures containing neurons active before or during pursuit has been
partially elucidated (for reviews, see Keller and Heinen
1991; Krauzlis and Stone 1999
). The smooth
pursuit pathway has its origin in the motion processing pathway
(Beutter and Stone 1998
; Komatsu and Wurtz
1989
; Lisberger et al. 1987
; Tychsen and
Lisberger 1986
; Watamaniuk and Heinen 1999
), a
specialized subdivision of the visual system (Ungerleider and
Mishkin 1982
). This subdivision includes two visual areas in
the region of the superior temporal sulcus, the middle temporal (MT)
(Albright 1984
; Baker et al. 1981
;
Felleman and Kaas 1984
; Maunsell and Van Essen 1983a
; Zeki 1974
) and medial superior temporal
areas (MST) (Desimone and Ungerleider 1986
;
Maunsell and Van Essen 1983b
). Area MT projects to the
frontal oculomotor area or frontal eye field (FEF) located in the
arcuate sulcus (Ungerleider and Desimone 1986
), which is part of a frontal network involved in gaze control (for review, see
Schall 1997
). A region of the FEF located in the
fundus of the arcuate sulcus is involved in the control of smooth
pursuit (referred to as FEFSEM; SEM stands
for smooth eye movements). Indeed, the FEFSEM
contains neurons active before and during smooth pursuit
(Gottlieb et al. 1994
; MacAvoy et al.
1991
). Electrical stimulation in that area has been shown to
evoke smooth eye movements (Gottlieb et al. 1993
;
Tian and Lynch 1996a
) and to increase the gain of smooth
pursuit (Tanaka and Lisberger 2001
).
The involvement of the frontal lobe in smooth pursuit control is
probably not limited to the FEFSEM. Area MST,
which contains neurons active during pursuit (Newsome et al.
1988), projects to the dorsomedial frontal cortex (DMFC)
(Huerta and Kaas 1990
; Maioli et al.
1998
). It has been shown in the macaque monkey that the DMFC
also contains neurons active during smooth pursuit (Heinen 1995
; Heinen and Liu 1997
). The area of the DMFC
where pursuit neurons were found coincides anatomically with the
supplementary eye field (SEF). The SEF contains neurons active before
saccades and low-current electrical stimulation in the SEF evokes these movements (Russo and Bruce 2000
; Schlag and
Schlag-Rey 1987
). In the Telazol-anesthetized Cebus monkey
preparation, Tian and Lynch (1995)
showed that smooth
eye movements could also be evoked by microstimulation in the SEF.
However, Russo and Bruce (2000)
reported that electrical
stimulation in the SEF of the awake macaque monkey does not evoke
smooth eye movements. Therefore the role of the SEF during smooth
pursuit is still questionable.
The aim of this study was to investigate the role of the macaque SEF during smooth pursuit with electrical stimulation. Electrical stimulation was applied during fixation, smooth pursuit initiation and steady-state pursuit. We found that microstimulation of the SEF during fixation did not evoke smooth eye movements. However, if current was applied during pursuit initiation, an increase in initial eye acceleration and eye velocity was observed. This pursuit facilitation was not observed during steady-state pursuit. Evoked saccades and pursuit facilitation were obtained at different sites in the SEF. The latency of catch-up saccades was significantly lengthened when pursuit was facilitated. The results suggest that besides their known role in saccade preparation, the SEF also contributes to the initiation of smooth pursuit.
A preliminary report of these results has been published previously in
abstract form (Missal and Heinen 1999).
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METHODS |
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Surgical procedures
The results reported in the present study were gathered from stimulation made in two adult rhesus monkeys (Macaca mulatta; subsequently referred to as GU and SA). All procedures were approved by the Institutional Animal Care and Use Committee and were in compliance with the guidelines set forth in the United States Public Health Service Guide for the Care and Use of Laboratory Animals.
Surgery was performed under aseptic conditions. Under isofluorane gas
anesthesia, a ~2 cm craniotomy was trephined in the skull, at
anterior position 24 mm in Horsley-Clark stereotaxic coordinates. The
craniotomy was centered on the midline of the brain in monkey
GU and 5 mm right to the midline in monkey SA. Bone
screws were inserted around the perimeter of the exposed area. A
stainless steel recording chamber (Crist Instrument) was positioned
over the craniotomy. The chamber was cemented on the skull using
rapidly hardening acrylic. A coil of Teflon-coated stainless steel wire
was set under the conjonctiva of one eye using the method developed by
Fuchs and Robinson (1966). A head-restraint device was
positioned on the midline caudally. After surgery, the monkeys were
returned to their cage and were allowed to recover fully from surgery.
Antibiotics (Ancef) and analgesics (Buprenex) were administered under
the direction of a veterinarian during the postoperative period.
At the end of experiments, monkey GU was deeply anesthetized with pentobarbital and perfused with a 10% formalin solution, and the brain was removed.
Animal training
Monkeys were trained to pursue a 1° target spot back-projected
on a tangent screen located 40 cm in front of the animal that was
generated with an analog oscilloscope. Each trial was initiated by the
appearance of a target for 400 ms during which the monkeys had to fix
at that initial position. After the animal foveated the target, the
fixation period lasted for 500 ms. During that period, animals had to
maintain gaze within a square electronic window of 4 × 4°
centered around the target. At the end of the fixation period, the
target stepped to an eccentric position and then started to move at
constant velocity ("step-ramp" or Rashbass stimulus)
(Rashbass 1961). The target always stepped in the
direction opposite that of subsequent target motion. For some
experiments, the amplitude of the step was varied to try to obtain
saccade free trajectories. This strategy was successful in monkey
SA (example presented on Fig. 1). In
monkey GU, catch-up saccades were more frequent (see
following text, example presented on Fig. 8).
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Monkeys were also trained in a fixation task to evaluate the influence of stimulation during fixation of a stationary target. During this task, monkeys were required to maintain their gaze at the position of a spot of light that appeared in the center of the screen or at an eccentric position. A variant of this task, the gap-fixation task, was designed to evaluate the effect of stimulation during fixation in the absence of a visual target. During that task, the target disappeared for 200 or 400 ms at the end of the fixation period. The fixation point reappeared afterwards at the same position it occupied before. The task of the monkeys was to keep fixating the former position of the target until its reappearance.
Electrical stimulation
Stimulation trains consisted of bipolar pulses (cathodal-anodal)
with a duration of 0.2 ms for each phase. Stimulation frequency was
usually 300 Hz, and train duration varied between 100 and 400 ms.
Current intensity was usually varied between 25 and 200 µA.
Stimulation was delivered by a constant current generator through
tungsten microelectrodes (impedance, ~1 M; Frederic Haer). Stimulation trains could be triggered at different times with respect
to behaviorally relevant events like fixation point onset and offset or
target motion onset. Control and stimulation trials were either
randomly interleaved in one block or presented in different blocks.
These two procedures yielded similar results.
Definition of the supplementary eye fields
We stimulated in the area in the dorsomedial frontal cortex that
was previously defined as the supplementary eye fields (SEF), based on
saccades evoked by electrical stimulation and neuronal recordings
(Schlag and Schlag-Rey 1987). In a preliminary testing, we determined the approximate location of the SEF by stimulation with a
current intensity of 50-75 µA at 300 Hz. In the text, SEF corresponds to the functionally defined area and DMFC (dorsomedial frontal cortex) is used to describe the anatomical region.
Data analysis
Vertical and horizontal eye position signals were digitized (1 kHz) and stored on a hard disk for off-line analysis. Horizontal and vertical eye velocity was obtained directly by analog differentiation (with a cutoff frequency of 170 Hz). Matlab and its Signal Processing and Statistical Toolboxes (Mathworks) were used to implement all signal processing and data analysis algorithms. Eye acceleration was obtained by digital differentiation of the eye velocity signal and was filtered using a zero-phase forward and reverse digital filtering procedure (Matlab function filtfilt) and a second-order Butterworth filter (cutoff frequency, 25 Hz).
SMOOTH PURSUIT LATENCY.
The latency of smooth pursuit (referred to as
LatPUR) was determined on a trial-by-trial basis.
The latency of smooth pursuit is the time elapsed between the
appearance of the moving target and the increase in eye velocity that
characterizes the initial acceleration period. Two independent methods
were used to determine latency. The first determined pursuit latency by
extrapolation. A segment of the velocity profile during the initiation
period was fit with a straight line using linear regression methods. The intersection of that regression line with the baseline velocity level during fixation determined the time at which pursuit started. A
similar method has been used previously by other investigators (Carl and Gellman 1987; Krauzlis and Miles
1996
). The second method detects latency by determining when
acceleration exceeds a threshold fixed at
70°/s2 in monkey GU and
150°/s2 in monkey SA. Both methods
of determination of pursuit latency were visually checked and yielded
similar results.
MEASURES DURING PURSUIT INITIATION.
During pursuit initiation, eye acceleration increases, reaches a
maximum, and then decreases. The maximum acceleration of the eye during
that period was measured (referred to as AccMAX). Eye velocity was measured at a fixed time during initiation, before the
catch-up saccade. The latency of the catch-up saccade with respect to
pursuit onset was shorter in monkey SA (shortest average saccade latency, ~100 ms) than in monkey GU (shortest
average saccade latency, ~160 ms). Furthermore, smooth eye
acceleration reached a maximum before the saccade. Therefore eye
velocity was measured and averaged during the period from 40 to 60 ms
after pursuit onset in monkey SA and from 80 to 100 ms after
pursuit onset in monkey GU. This measurement will be
referred to as initial velocity or
VINIT. The difference in
VINIT between control and stimulation
conditions will be referred to as
VINIT.
LATENCY AND PARAMETERS OF THE CATCH-UP SACCADE.
The latency of the catch-up saccade (referred to as
LatSACC) was detected when eye acceleration
crossed a threshold of 2,000°/s2 for 20 ms. A
computer program indicated when that threshold was crossed. Saccade
offset was detected using the same threshold but starting from a point
during steady-state pursuit and moving back in time until the threshold
during the deceleration period of the saccade was crossed. After
saccade onset and offset were determined, the amplitude of the movement
was computed (referred to as AmpSACC).
STATISTICS. Matlab Statistics Toolbox (Mathworks) and Statistica (Statsoft) were used to perform statistical procedures. The significance of all observed effects was tested with parametric methods: Student's t-test (referred to as t-test) for two-sample comparisons and ANOVA when multiple comparisons were needed. The statistical significance level (P level) was always 0.05. All results given in the text are in the form means ± SE. When necessary, the confidence interval of mean eye velocity during pursuit initiation was computed. The Student's t statistics were used to determine the boundaries of the confidence interval of the mean.
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RESULTS |
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Determination of stimulation sites
Sixty-five sites were stimulated in the SEF of two monkeys (38 sites in monkey GU, 28 sites in monkey SA). During experiments, stimulation was delivered during the fixation and gap-fixation tasks when the eyes were oriented toward different positions in the orbit to assess the possible role of initial orbital eye position on the threshold to evoke a movement. Stimulation was also delivered when the monkey was sitting in a darkened room and not involved in an externally controlled task. Currents used in this preliminary test varied between 50 and 200 µA. Stimulation trains lasted between 100 to 400 ms at 300 Hz. Eye movements were monitored as well as overt behavioral and muscular responses. These procedures were used to determine whether the site of microstimulation was within the neuronal pathway controlling saccades or other movements. The influence of electrical stimulation on smooth pursuit initiation was studied only at sites in the SEF were saccades could not be evoked using the procedures described in the preceding text. Stimulation was delivered at sites where neurons active during pursuit movements were found.
Facilitation of smooth pursuit initiation
We found that at 32 sites, low current electrical stimulation in the region of the SEF during smooth pursuit initiation increased the acceleration and the velocity of the eye in the direction of the moving target. Figure 1 shows an example of a smooth pursuit trial during which the subject (monkey SA) had to pursue a target that moved at 50°/s to the right after a step of the target to a position 3° to the left.
In the control situation when no stimulation was applied (gray
curves), initial horizontal eye velocity
(VINIT) 50 ms after pursuit
onset was 25.2°/s and maximum eye acceleration
(AccMAX) was 608.2°/s2.
During the stimulated trial (black curves),
VINIT was 41.5°/s and
AccMAX was 965.9°/s2.
Electrical stimulation lasted for 400 ms, starting 169 ms before pursuit onset (100 ms before target motion onset). Current intensity was 50 µA at 300 Hz. This stimulation site was located in the right
hemisphere (site SA02). It can be seen that low current electrical stimulation produced an increase in maximum eye acceleration and velocity during pursuit initiation, an effect that will be referred
to as pursuit facilitation or simply as facilitation. At this site and
for this current intensity, average values of VINIT were 28.9 ± 1.9°/s in
controls (n = 18) and 34.2 ± 0.9°/s in
stimulation trials (n = 30) in a block where
stimulation and control trials were interleaved randomly.
VINIT during stimulation was
significantly different from VINIT in
controls (P = 0.0075) with the average difference in
eye velocity (VINIT) being
5.3°/s. Average maximum eye acceleration was 653 ± 38°/s2 in controls and 753 ± 26°/s2 in stimulation trials. This difference
was also significant (P = 0.03). At site
SA02 and in the same block of trials, pursuit latency was
66.2 ± 2.5 ms (n = 18) during stimulation and
64.1 ± 1.2 ms (n = 30) in controls. This
difference was not statistically significant (P = 0.41).
During pursuit facilitation, the direction of the smooth pursuit
movement remained unchanged with respect to controls. This was
quantified by comparing the direction or polar angle () of the
velocity vector at the time VINIT was
measured (see METHODS). At site SA02, the
average value of angle
was 0.15 ± 0.60° (n = 18) in controls and 0.10 ± 0.50° (n = 30) in
stimulation trials. This difference was not significant
(P = 0.96). The direction of the velocity vector was
compared at nine additional stimulation sites in monkey SA
and GU. The value of
was compared in blocks of randomly
interleaved stimulation and control trials (15-20 trials in each
condition). It was found that stimulation did not significantly change
the orientation of the velocity vector at any of these sites.
Although electrical stimulation did not change the direction of
pursuit, the increase in VINIT might
be directionally selective. To test whether
VINIT was increased for certain
directions only, stimulation was delivered during pursuit in eight
different directions spaced by 45°. Each direction was tested
independently, with 20 stimulation and 20 control trials randomly
interleaved (60 µA, 300 Hz, 200-ms train duration). The results are
presented on Fig. 2 (site
SA43). Electrical stimulation increased
VINIT in all directions (significant differences are indicated by * in Fig. 2). The
largest effect at this site was observed for downward pursuit
(VINIT = 10.3°/s), and the
smallest difference was observed for leftward pursuit
(
VINIT = 1.6°/s). This figure
shows the poor spatial selectivity of the facilitation. It is
reasonable to suggest that facilitation was omnidirectional for the
site presented on Fig. 2. Some directions might show a larger increase
in VINIT than others, perhaps due to
variations in performance of the monkey. A "tuning curve" like the
one represented on Fig. 2 was not built for all sites because of the
large amount of data needed (40 trials for each direction). However,
during experiments the effect of stimulation was always monitored
during both leftward and rightward pursuit. At seven stimulation sites,
facilitation was observed for both directions (bilateral facilitation).
This observation is consistent with an omnidirectional tuning. For
example, at site GU21, pursuit initiation was facilitated
both to the left (controls: VINIT = 11.2 ± 0.8; stimulation: VINIT = 16.3 ± 1.1;
VINIT = 5.1°/s
or 31%; P = 0.001) and to the right (controls: VINIT = 11.7 ± 0.75;
stimulation: VINIT = 15.5 ± 0.92;
VINIT = 3.8°/s or 25%;
P = 0.0039). However, at 17 stimulation sites, facilitation was observed for pursuit directed ipsilateral to the side
of the stimulated hemisphere, and at eight sites, facilitation was
observed for pursuit directed contralateral to the side of the side of
the stimulated hemisphere. Facilitation was therefore mainly
ipsilateral with a large proportion of bi- or even omnidirectional effects.
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A significant facilitation was observed at 32 sites among the 65 sites
stimulated in the two monkeys (32/65; 49%; 20 sites in monkey
GU, 12 sites in monkey SA). On average,
VINIT was 5.5 ± 0.5°/s
(n = 32). The average difference in
AccMAX was 52.2 ± 7.2°/s2 (n = 32), acceleration
during stimulation being larger, except at one site. Figure
3 shows a summary of the facilitation
observed for stimulations sites in the two monkeys where a significant increase in VINIT was found. The
facilitation was expressed as a percentage increase in eye velocity
(Fig. 3A) or maximum acceleration (Fig. 3B)
during stimulation trials with respect to controls
[(stimulation-control/stimulation)*100]. Each bin contains the
number of sites where the labeled increase in
VINIT or AccMAX
was observed. Electrical stimulation evoked most frequently an increase
in VINIT between 16 and 24% and an increase in AccMAX between 5 and 25%.
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Average pursuit latency was 76 ± 2 ms (n = 32) in controls and 74 ± 3 ms (n = 32) in stimulation trials. Pursuit latency was significantly affected only at 3 of 32 stimulation sites (3/32; 9%). The significant difference was independent of the method used to determine LatPUR. In conclusion, it is reasonable to suggest that electrical stimulation did not alter the time of smooth pursuit initiation.
Stimulation during steady-state pursuit
The effect of microstimulation was also tested after pursuit initiation during the period of constant eye velocity that characterizes steady-state pursuit. Stimulation trains were timed with respect to the onset of target motion. The exact onset time of stimulation trains varied between 300 and 500 ms after target motion onset to start after a potential catch-up saccade. Eye velocity was measured 100 ms after stimulation onset. We found that stimulation during that period did not increase eye velocity as it did during pursuit initiation at the same stimulation sites (P > 0.05). This experiment was repeated at seven different stimulation sites and yielded the same negative result: electrical stimulation at sites where initiation was facilitated did not increase eye velocity during ongoing pursuit (7/7 sites). The facilitatory influence of electrical stimulation of the SEF on smooth pursuit was therefore limited to the period of initiation.
Influence of stimulation parameters
Parameters of the stimulation trains that were varied were current
intensity, frequency, onset time, and duration. Stimulation frequency
was investigated at one stimulation site only. Three different
frequencies were tested, 200, 300, and 400 Hz. Current intensity was 75 µA (200-ms train duration). With these parameter, the average
VINIT was 5.7°/s at 200 Hz,
12.2°/s at 300 Hz, and 2.6°/s at 400 Hz (20 trials for each
category). The largest increase in eye velocity was obtained with a
300-Hz stimulation train.
At 300 Hz, current intensity was varied to determine an intensity
threshold to observe facilitation. In the saccadic domain, a typical
definition of an intensity threshold is the current needed to evoke a
saccade in 50% of trials. Currents routinely used are 1.5 times the
threshold intensity. In the pursuit domain, it is usually difficult to
establish a threshold in a similar way as changes in eye velocity are
gradual. Current intensity was systematically varied at seven different
stimulation sites to determine the minimal or statistical intensity of
stimulation trains needed to observe facilitation and characterize the
relationship between intensity and facilitation. Figure
4A shows an example where a
large range of current intensities could be tested. Control trials
() and stimulation trials at different intensities (
) were
collected in separate blocks of ~20 trials each. Stimulation blocks
with different current intensities were randomized in the order of
presentation. Stimulation with low current intensities after
stimulation with high current intensities still induced smooth pursuit
facilitation, indicating that the decreased effect with higher current
intensities was not due to tissue damage or lowered electrode
impedance. The duration of the stimulation train was 400 ms at 300 Hz.
As shown on Fig. 4A, a current intensity of 50 µA was
sufficient to evoke pursuit facilitation at this site. When the current
was further increased, the effect of stimulation increased also. At
this site, the relationship between current intensity and
VINIT was approximately linear for
currents
100 µA. A maximum increase in
VINIT was reached around 200 µA, and larger currents were less effective. The current for which
VINIT was the largest will be
referred to as the optimal current at that stimulation site (Fig. 4,
). At 400 µA, stimulation did not increase eye velocity. To
determine the significance of the stimulation effect, a comparison was
performed between the different pairs of current intensities and
controls. This comparison was achieved with an ANOVA and a post hoc
test. Stimulation had a significant effect on
VINIT for currents
50 µA but
300
µA [ANOVA; F(6,133) = 17.04; P < 0.01; LSD post hoc test]. For instance, for the site presented on Fig.
4, VINIT in control trials was 13.0 ± 0.5°/s (n = 20) and 15.6 ± 0.8°/s (n = 20) during stimulation with an intensity
of 50 µA. Fifty microamps could therefore be considered as a
statistical threshold for the facilitation effect. However, to maximize
the facilitation, current intensities routinely used were 75, 100, or
maximum 200 µA (at 300 Hz). The influence of current intensity was
tested at 7 sites among the 32 sites where a significant pursuit
facilitation was observed. At these seven sites, very high current
intensities (300-400 µA) were tested only three times (3/7) to not
damage the brain tissue. Figure 4B, left, shows stimulation
sites where high current intensities were tested. Figure 4B,
right, shows stimulation sites where current intensities between
20 and 200 µA were tested. Eye velocity in stimulation trials was
normalized with eye velocity in controls. At all sites tested (7/7),
the relationship between VINIT and current intensity was linear for current intensities <200 µA.
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Median values of VINIT for different current intensities were always close to the mean values, indicating that velocity distributions at different current intensities were symmetric. For the example presented on Fig. 4, the mean of VINIT in controls was 13.0°/s and the median was 13.4°/s. For stimulation at 50 µA, the mean was 15.6°/s and the median was 16.6°/s. For stimulation at 200 µA, the mean and the median were both 20.4°/s. These results suggest that the velocity of each individual movement was increased not just the proportion of exceptionally fast pursuit movements. Indeed, if this were true, it is expected that the mean would be larger than the median.
Temporal relationship between stimulation and facilitation
The effect of stimulation was greater when administered at the end of the fixation period before smooth pursuit began. The influence of the timing of the stimulation train was tested at seven different stimulation sites. Stimulation trains were triggered with respect to the onset of target motion (see METHODS). Figure 5A shows the relationship between the onset of a 200-ms stimulation train and the facilitation effect for one site. The timing of the onset of the stimulation train was varied between 200 ms before target motion onset to 200 ms after target motion onset, in steps of 50 ms. The data are expressed with respect to pursuit onset with zero on the abscissa indicating the onset of pursuit (PON), which occurred 75 ms after target motion onset on average. Negative values indicate that the stimulation train started before pursuit onset, during the fixation period. A significant facilitation was observed when the stimulation train began between 275 and 75 ms before pursuit onset and was not significant if the stimulation train started 25 ms before pursuit or later. Figure 5B shows all stimulation sites where the influence of the timing of the stimulation train was tested. The left graph shows sites where at least five different onset times were used. The right graph shows sites where four or less different onset times were used. Eye velocity in stimulation trials was normalized with eye velocity in controls. Continuous lines indicate sites where the strongest facilitation occurred when stimulation started 175 ms before pursuit onset (indicated by a vertical arrow). Interrupted lines show sites where the maximum effect occurred for different onset times. The dotted curve shows a site where only two different onset times were used.
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The latency of the facilitation effect was defined as the time when
VINIT became significantly different
in stimulation trials compared with controls. This latency could be
estimated from the above described time/velocity relationship. If
stimulation began 25 ms before pursuit onset,
VINIT measured 90 ms after pursuit onset was not significantly increased (time, 25 on Fig. 5; 115 ms
after stimulation onset). On the other hand, a significant increase in
VINIT was found when stimulation
started 75 ms before pursuit onset (time,
75 on Fig. 5). In this
condition, the estimated latency is ~165 ms (90 + 75 ms). Therefore
the latency of the facilitation on
VINIT with respect to stimulation
onset could be between 115 and 165 ms. This estimation is biased by the
time at which the measure was made, in the case of monkey
GU, 90 ms after pursuit onset. This might produce latency measures
that are overestimated. To avoid this limitation, we determined when the velocity of the eye in individual stimulation trials diverged from
the mean velocity in controls by using a method based on confidence
intervals. Eye velocity in control trials was averaged during the first
150 ms of pursuit initiation and the confidence interval was computed
using the Student's t statistics (see METHODS). Ten to 20 trials were used to compute the mean and confidence interval
of control eye velocity. Ten to 20 individual stimulation trials were
compared with that mean. The latency of facilitation was estimated by
comparing the time course of eye velocity during pursuit initiation in
a single stimulation trial with the average time course in controls. We
defined latency as the time when eye velocity in stimulation trials
exits the confidence interval of controls and remained out of the
confidence interval for more than 50 ms. This last condition was
necessary because eye velocity could exit the confidence interval for
short periods of time, due to the larger amount of noise present in a
single trial as compared with a mean of controls. Figure
6 shows the mean eye velocity (white
traces) and the confidence interval of the mean of controls (gray
shaded areas) together with the eye velocity of a single stimulated
trial (black traces) for two different stimulation sites. In the
example presented on Fig. 6A, stimulation started 180 ms
before target pursuit onset and lasted for 400 ms. In the example
presented on Fig. 6B, stimulation started 67 ms before
pursuit onset and lasted for 200 ms. The latency of the facilitation
for these single trials is indicated by a vertical arrow above the
velocity profile. For the site illustrated on Fig. 6A, this
procedure gave an average latency of 56.5 ± 2.1 ms
(n = 15) with respect to pursuit onset. For the site
presented on Fig. 6B, the average latency was 50.6 ± 2.8 ms (n = 10). The latencies were similar at the two
sites, in spite of the different onset time of the stimulation trains.
A similar analysis was repeated at five additional sites. The average
latency obtained from all sites tested with this procedure was
61.3 ± 3.5 ms (n = 7). This suggests that the
facilitation latency does not depend primarily on the onset of
stimulation, but on the onset of pursuit. Stimulation of the SEF could
alter eye velocity as early as ~60 ms after pursuit onset.
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Influence of eye velocity
The facilitation during pursuit initiation produced by SEF stimulation could result from either an influence of the electrical stimulation on sensory processes, such as the perception of target motion, or on neuronal processes related to the preparation of the movement. Therefore the facilitation could be related either to target velocity, eye velocity or a combination of both. The influence of eye velocity can be determined if a range of eye velocities can be compared in control and stimulation trials for the same target velocity and stimulation parameters. Figure 7A shows the relationship between average VINIT in controls (abscissa) and stimulated trials (ordinate) for stimulation sites tested in monkey GU with the same target velocity (40°/s) and stimulation parameters. Each point represents the mean of VINIT in control and stimulation trials for one site. VINIT in controls varied between 10 and 20°/s. A linear relationship between VINIT in controls and stimulation trials was found (correlation: r = 0.97; P < 0.001; n = 15). Initial eye velocity during stimulation increased with eye velocity in controls. The intercept of the linear relationship was ~1°/s and was not significantly different from zero (P = 0.47). The slope of the linear relationship was 1.17, showing that the higher the velocity of the eye, the larger was the increment in eye velocity due to stimulation. The main effect of the stimulation, the facilitation effect, resulted of the multiplication of VINIT by a gain factor of ~1.2 and not from the addition of a bias. This suggests that electrical stimulation was altering a gain mechanism in the premotor pathway for pursuit.
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To investigate the possibility that pursuit facilitation depended on
target velocity, a large range of target velocities were tested at the
same stimulation site with all other stimulation parameters kept
constant. Target velocity was varied between blocks of trials.
Stimulation and control trials were randomly interleaved. Figure
7B shows the results obtained at one site, where the largest range of target velocities available could be tested (monkey
GU; target velocity varying between 5 and 60°/s by steps of
5°/s). The figure shows the relationship between target velocity and VINIT in controls () and
stimulation trials (
). Each point shows the average value and the
standard error of VINIT for more than 10 trials. It can be seen that VINIT
increased nonlinearly with target velocity. However, for targets moving
slower than 30°/s, the relationship between
VINIT and target velocity is
approximately linear. When fitted with a linear model, the slope of
that relationship was larger in stimulation (0.8) than in control
trials (0.6). The different slopes of the relationship between target
velocity and VINIT in control and
stimulation trials further suggests that electrical stimulation
was altering a gain mechanism in the premotor pathway for pursuit.
Facilitation was weak for low values of
VINIT in controls (e.g., for a target
moving at 5°/s) and was larger when
VINIT in controls was higher (e.g.,
for a target moving at 30°/s). For target velocities 30°/s,
VINIT varied between 15 and 20°/s in
controls and varied between 25 and 30°/s in stimulation trials.
Higher eye velocities were attained later during the pursuit trial
(e.g., in monkey GU, maximum eye velocity during pursuit of
a target moving at 40°/s was 31 ± 0.9°/s, n = 17). The nonlinear relationship between target velocity and
VINIT shows that the facilitation was
not correlated with target velocity. Indeed, if the facilitation was
primarily related to target velocity, it would be expected that
VINIT in stimulation trials would
continue to increase with increasing target velocities. We conclude
that the facilitation does not depend on target velocity primarily, but
is a function of the velocity of the eye. The same experiment was
repeated at three other stimulation sites and yielded similar results.
Stimulation during fixation
Stimulation was also applied during a fixation task. Pursuits and fixations were collected in different blocks of trials. During the fixation task, the fixation point either remained lit during the whole trial or was temporarily extinguished for 200-400 ms (gap fixation task). The gap fixation task was designed to suppress any retinal slip signal that could interact with the outcome of the stimulation. The initial position of the eye in the orbit was the same as during pursuit trials. Stimulation was applied at the same time with respect to fixation onset with similar current parameters. During fixation trials, smooth eye movements could not be evoked. Similarly, no smooth eye movements were observed if electrical stimulation was delivered during intertrial periods when the animal was spontaneously orienting its gaze toward different positions. These results suggest that the effect of stimulation depended on the motor context at the time of stimulation. Specifically, monkeys had to be involved in a pursuit task for the stimulation to have any observable effect.
Characteristics of the initial catch-up saccade
When a catch-up saccade occurred, its latency (~200 ms) was longer than the latency of pursuit (~80-100 ms). Pursuit facilitation was measured on the smooth eye movement preceding the saccade. Figure 8 shows an example of smooth pursuit facilitation before the occurrence of the catch-up saccade in monkey GU (site 22, left hemisphere), during the initiation of pursuit toward a target moving to the left at 40°/s. In the control condition (gray curves on Fig. 8), VINIT before the catch-up saccade was 10.7°/s. In the stimulated trial (black curves on Fig. 8), VINIT was 21.6°/s. Electrical stimulation lasted for 400 ms and began 100 ms before target motion onset, with a current intensity of 100 µA at 300 Hz (2 times threshold intensity at this site, see Fig. 4A). On average, eye velocity in controls was 13.0 ± 0.5 and 18.4 ± 0.8°/s during stimulation (P < 0.001; n1 = n2 = 20). As can be seen on Fig. 8, the latency of the catch-up saccade was longer during stimulation trials (230.9 ± 18.9 ms; n = 20) than during control trials (156.1 ± 7.5 ms; n = 19). This difference was statistically significant (t-test; P = 0.001). A similar significant increase in saccade latency was found in 62% of stimulation sites where catch-up saccades were frequent (13/21 sites or 62%; see Fig. 8B). Across all sites, average catch-up saccade latency was 177.1 ± 9.8 ms in controls and 213.1 ± 12.4 in stimulated trials (17% increase on average). The average difference in catch-up saccade latency was as large as 114 ms at one site.
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At site GU22, in a block of interleaved trials, the amplitude of catch-up saccades was significantly reduced by the stimulation (controls: 7.8 ± 0.2, n = 18; stimulation: 6.2 ± 0.5, n = 17; t-test; P < 0.05). However, the position of the eye with respect to the target at the end of the saccade (final error) was not significantly different in control and stimulation trials (controls: 0.3 ± 0.2, n = 18; stimulation: 0.3 ± 0.3, n = 17). In both conditions, saccades were hypometric. Therefore catch-up saccades in stimulation trials were normal and landed near the moving target, except that their occurrence was delayed. As a consequence, the error in position before the saccade was triggered was smaller during stimulation trials.
Saccade delay could be due to current spread to neighboring sites involved in saccade planning due to a competition between the site activated by the electrical stimulus and the site activated by the normal planning of the movement. To test this hypothesis directly, we stimulated the same sites with the same current parameters before saccades of similar amplitudes toward stationary targets. If the increased latency is due to an interaction with neighboring sites involved in saccade control, saccades toward stationary targets should be affected in a similar way as saccades during pursuit. If the delay of the catch-up saccade is specifically due to smooth pursuit facilitation, saccades toward stationary targets should not be affected by electrical stimulation. Therefore at five sites where pursuit facilitation was observed, a control experiment was run during which electrical stimulation was delivered before visually guided saccades toward stationary targets. Current intensity and timing were identical in both pursuit and stationary targets paradigms (100 µA, 400 ms at 300 Hz). The stimulation train started 100 ms before target onset in both conditions. The amplitude of saccades toward stationary targets was matched with the amplitude of catch-up saccades usually observed during control pursuit trials (~8°). Figure 9 shows an example when stimulation preceded the occurrence of saccades toward a stationary target. It was found that electrical stimulation did not delay saccades toward stationary targets at sites where catch-up saccades were delayed during pursuit facilitation. For instance, at site GU22, the latency of catch-up saccades in controls was 164.6 ± 7.7 (n = 22) and 156.1 ± 4.3 (n = 17) during stimulation trials (difference not significant, P = 0.38; see Fig. 9B). This experiment was repeated at five sites (controls: 149.8 ± 7.1; stimulation: 145.8 ± 13.9; n = 5; see Fig. 9B). The amplitude of saccades toward stationary targets were similar in controls (site GU22: 9.1 ± 0.2, n = 12; 4.8 ± 0.2, n = 10) and stimulation trials (8.9 ± 0.2, n = 8; 5.1 ± 0.2, n = 9; P > 0.05). Stimulation before saccades toward stationary targets was repeated at four additional sites where saccades during pursuit were delayed. At each site, the latency and metrics of saccades toward stationary targets were unaltered. This result suggests that current spread to neighboring saccadic areas cannot explain the delay that was observed during pursuit.
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To reveal whether delayed saccades were due to the higher gain of
smooth pursuit initiation observed during stimulation, the effect of
current intensity was compared for both phenomena. Figure 10A shows individual traces
of the position of the eye as a function of time during control and
stimulation trials at site GU39. Eye velocity was higher in
stimulation versus control trials. Saccade latency increased by 100 ms
on average in stimulation trials. At site GU39, the optimal
current intensity for facilitation was 100 µA. That current was used
during the trials presented on Fig. 10. As the velocity of the eye also
increased with current intensity for intensities 200 µA, there
could be a correlation between the latency of the catch-up saccade and
VINIT. Figure
11A shows the relationship
between current intensity and VINIT in
controls and stimulation trials for a large range of currents tested at the same site. The same nonmonotonic relationship as described before
was found (see Fig. 4). Figure 11B shows the relationship between current intensity and saccade latency for the same site. A
significant increase of saccade latency was observed for a current intensity of 50 µA. Saccade latency increased with current intensity until a maximum was reached at 100 µA. Larger current intensities caused a progressive return of the latency toward control values. The
value of the current for which the strongest effect on saccade latency
was observed was similar to the optimal current for facilitation at
this stimulation site (100 µA). Indeed, the relationship between current intensity and saccade latency was similar to the relationship between current intensity and facilitation (compare Fig. 11,
A and B). Therefore the delay of the catch-up
saccade covaried with the velocity of the eye during stimulation trials
(correlation coefficient: r = 0.72, P = 0.028, n = 9). As
VINIT was increased with increasing
current intensity, the amplitude of the catch-up saccade was modified
appropriately to land near the moving target (Fig. 11C). A
similar increase in catch-up saccade latency with increasing current
intensity was observed at five additional stimulation sites. Figure
11D shows the average value of normalized saccade latency
for these sites. Saccade latency during stimulation trials was
normalized with the saccade latency in controls. Saccade latency increased with current intensity for the three intensities tested (50, 100, and 200 µA).
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Distribution of pursuit and saccades sites on the cortical surface
Pursuit sites were distributed over the rostrocaudal and lateral
extent of the area overlaid by the stimulation chamber, covering ~1
cm2 of cortical surface. Figure
12A shows the location of
the stimulation chamber in monkey GU. The drawing was made
from a photograph of the dorsal surface of the brain taken after
perfusion. The position that the chamber occupied was clearly visible
on the dorsal surface of the brain. The indicates the position of
the caudal tip of the arcuate sulcus. Figure 12B shows the
distribution of stimulation sites in monkey GU projected
onto a stereotaxic grid; the
indicates the same position as on Fig.
12A. Sites where pursuit facilitation was observed (
)
were intermixed with sites where saccades were evoked (
). At two
sites, evoked saccades and smooth pursuit facilitation were both
observed, but at different depths of the electrode in the track (
).
Stimulation sites where no observable effect of the stimulation was
found are also represented (
). No obvious spatial organization of
pursuit or saccade sites was observed. No extensive cortical mapping
was attempted. As shown on Fig. 11B, sites separated by 1 mm
on the stimulation grid could evoke saccades or facilitate pursuit.
These results show that different kinds of eye movements are not
represented in distinct subregions but in an interlaced fashion,
perhaps indicating the existence of a columnar organization. Since
monkey SA was still involved in other experiments, the
distribution of different sites could not be established in that
monkey.
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DISCUSSION |
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This study shows for the first time that electrical stimulation in the dorsomedial frontal cortex, in the region corresponding to the SEF, can induce facilitation of smooth pursuit initiation in the awake behaving monkey. Pursuit facilitation was obtained at sites different from where saccades could be evoked. Stimulation was effective during the time of movement preparation near the end of the fixation period. Catch-up saccades during pursuit were delayed during pursuit facilitation, but their accuracy was unaffected. The relationship between eye velocity in control and in stimulation trials suggests that the stimulation alters a gain mechanism, i.e., increases the performance of the system, without actually being involved in the direct initiation of the movement as suggested by the absence of effect during a fixation task and on pursuit latency.
Interconnection of the SEF with motion processing and pursuit pathways
The region of the DMFC where stimulation was applied is similar to
what was functionally defined as the SEFs in the saccadic domain.
Therefore the results of this study suggest that the SEF is part of the
smooth pursuit pathway, in addition to their previously shown
involvement in the saccade pathway (Schlag and Schlag-Rey 1987). This hypothesis is supported by anatomical studies of
the projections of the motion processing pathway to this region of the
frontal cortex. Cortical structures involved in motion processing include two regions of the temporal cortex, the middle temporal area
(MT) and the medial superior temporal area (MST). Lesions of these
areas impair motion processing and smooth pursuit (Dursteler and
Wurtz 1988
; Newsome et al. 1985
). MT and MST are
sensory areas, but area MST also contains neurons whose activity can be
correlated with the movement of the eye during pursuit (Newsome
et al. 1988
). Area MST and the neighboring region of the fundus
of the superior temporal sulcus project to the region of the FEF and to
a region dorsomedial to the upper arcuate limb of the arcuate sulcus
(Huerta and Kaas 1990
; Maoili et al.
1998
). This latter region corresponds to the DMFC and probably
also with the SEF. This projection of the motion processing and pursuit
pathways to the region of the SEF supports recent results of recordings
in that area during pursuit. Heinen (1995)
and
Heinen and Liu (1997)
have shown that some neurons in
that area are active during smooth pursuit. In the Telazol-anesthetized
monkey preparation, electrical stimulation in the SEF yields either
saccades or smooth pursuit (Tian and Lynch 1995
). In
human subjects, activation of a region of the DMFC corresponding
probably with the SEF during smooth pursuit has also been described
using imaging techniques (Berman et al. 1999
;
O'Driscoll et al. 2000
; Petit and Haxby
1999
; Petit et al. 1997
). The connectivity
between FEF and SEF suggests that the smooth pursuit region of the FEF
area could also project to the SEF (Tian and Lynch
1996b
). Altogether, these results support the hypothesis that
the SEF is part of the smooth pursuit pathway. Moreover, the SEF
projects to the nucleus reticularis tegmenti pontis (NRTP)
(Shook et al. 1990
), which is known to be an important relay in the subcortical pathway for pursuit (Suzuki et al.
1999
; Yamada et al. 1996
)
Comparison with other studies of electrical stimulation in the motion/pursuit pathway
Komatsu and Wurtz (1989) showed that electrical
stimulation in the foveal representation of MT and MST alters smooth
pursuit. These authors found an increase of smooth pursuit velocity
toward the side of the brain being stimulated. The most prominent
effect, however, was a decrease in pursuit velocity in the
contraversive direction. Stimulation was more effective during pursuit
than during fixation and catch-up saccades as well as saccades toward stationary targets were significantly delayed during stimulation in the
MT-MST complex. Komatsu and Wurtz (1989)
interpreted
these results by suggesting that stimulation introduced an additional motion signal in the motion processing pathway. This interpretation was
supported by a recent study of electrical microstimulation in area MT
(Groh et al. 1997
). These authors showed that electrical stimulation in area MT introduces an artificial motion signal that
increases the velocity of the eye in the preferred direction and
decreases eye velocity in the null direction. Electrical stimulation in
a later stage of the pursuit system has produced a different type of
results. Stimulation in the FEF pursuit area evokes smooth eye
movements during fixation (Gottlieb et al. 1993
;
Tian and Lynch 1996a
). These authors suggested that the
stimulation triggers an eye acceleration signal. Recently,
Tanaka and Lisberger (2001)
showed that stimulation in
the FEF pursuit area increases strongly eye velocity during pursuit and
moderately during fixation. Moreover, stimulation enhances the response
to a transient perturbation of target motion during fixation. The
authors suggest that the FEF sets the gain for smooth pursuit and could
be involved in the process of target selection.
In our study, pursuit facilitation does not appear to result from the
introduction of an additional directional target motion signal as
occurs when stimulating in the motion processing pathway (Groh
et al. 1997). First, introducing a directional signal should increase eye velocity in one direction and decrease it in the opposite
direction. The bilateral or omnidirectional effects which we often
observed are not reconcilable with the hypothesis of the addition of a
directional motion input. Second, the finding that sustained pursuit
was not altered by stimulation suggests that stimulation did not simply
add a certain signal in the motion processing pathway during an ongoing
smooth eye movement. Neither did stimulation evoke an additional eye
velocity command that would be combined with the ongoing movement.
Addition of an eye velocity command would always increase eye velocity
by a constant amount, probably depending on the stimulation parameters
and on the particular site being stimulated. We suggest that our
results can be explained better by an alteration of a gain mechanism in the premotor pathway for pursuit by electrical stimulation. This results in a multiplication of eye velocity in controls by a certain amount (in this case, ~1.2). In the relationship between target and
eye velocity in controls and stimulation trials (see Fig. 7B), the saturation reflects limits of the motion processing
pathway in transforming a retinal slip signal into an eye acceleration command (Lisberger and Westbrook 1985
; Lisberger
et al. 1981
). Compared with the results of Tanaka and
Lisberger (2001)
obtained in the FEF, our results extend the
possibility of a gain control of smooth pursuit to the SEF. Both areas
are interconnected (Stanton et al. 1993
), raising the
question of their relative involvement in this process.
Interaction between different kinds of eye movements
The results of this study suggest a causal relationship between
facilitation of pursuit and delay of the catch-up saccade, i.e., the
catch-up saccade was delayed because smooth pursuit was
facilitated, because saccades toward stationary targets were not
affected. In natural circumstances, acquisition of a moving target
requires a combination of saccades and smooth pursuit. A behavioral
study has shown that the latency of the catch-up saccade increases if
eye acceleration is larger for a target moving at the same velocity
(Kim et al. 1998). Therefore electrical stimulation, by
artificially increasing eye acceleration and velocity, might delay the
catch-up saccade by a similar mechanism. Interfering with the initial
smooth eye acceleration alters the timing of the next movement in the
sequence, the catch-up saccade. It has been shown that lesions of the
DMFC affects sequences of saccades more than single movements
(Schiller and Chou 1998
; Sommer and Tehovnik
1999
). Therefore that part of the cortex might be activated when sequences of eye movements are planned. Initiation of smooth pursuit can also be considered as a sequence of two different movements: an initial smooth eye acceleration and a subsequent catch-up
saccade. Although this hypothesis needs further investigation, it could
be suggested that the region of the SEF might contain modules, perhaps
columns, active during different kind of eye movements. Interactions
between nearby modules could be the neuronal basis of the functional
interaction between oculomotor systems.
Task dependency
An obvious difference between this study and the work of
Tanaka and Lisberger (2001) is the absence of effect of
microstimulation in the SEF during fixation. Smooth movements can be
evoked from the FEF pursuit area during fixation, possibly because it
is directly connected to the final pathway for pursuit eye movements,
which may not be the case for the SEF. Alternatively, the activity of neurons in the SEF could be "gated" by fixation signals. Therefore the facilitation effect in the SEF could be considered as task dependent. In the authors' experience, smooth eye movements are usually more difficult to evoke electrically from a pursuit area than
saccades from a saccadic area. This might be the consequence of the
different modes of control of these eye movements. Indeed, primates can
trigger saccades in the absence of an external stimulus. Smooth pursuit
eye movements cannot be initiated voluntarily under normal conditions
but needs the presence of a visual motion signal or an expectation
about future target motion.
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ACKNOWLEDGMENTS |
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The authors thank the Keller Laboratory for critical readings of an earlier version of the manuscript.
M. Missal was supported by a long-term fellowship from the Human Frontier Science Program (HFSP) and an Atkinson Fellowship from the Smith-Kettlewell Eye Research Institute. This work was supported by National Eye Institute Grant EY-11720-05.
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FOOTNOTES |
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Address for reprint requests: M. Missal, The Smith-Kettlewell Eye Research Institute, 2318 Fillmore St., San Francisco, CA 94115 (E-mail: missal{at}ski.org).
Received 19 March 2001; accepted in final form 17 July 2001.
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REFERENCES |
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