Howard Hughes Medical Institute, Department of Physiology, W. M. Keck Foundation Center for Integrative Neuroscience, and Neuroscience Graduate Program, University of California, San Francisco, California 94143
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ABSTRACT |
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Churchland, Mark M. and
Stephen G. Lisberger.
Apparent Motion Produces Multiple Deficits in Visually Guided
Smooth Pursuit Eye Movements of Monkeys.
J. Neurophysiol. 84: 216-235, 2000.
We used apparent motion
targets to explore how degraded visual motion alters smooth pursuit eye
movements. Apparent motion targets consisted of brief stationary
flashes with a spatial separation (x), temporal
separation (
t), and apparent target velocity equal to
x/
t. Changes in pursuit initiation
were readily observed when holding target velocity constant and
increasing the flash separation. As flash separation increased, the
first deficit observed was an increase in the latency to peak eye
acceleration. Also seen was a paradoxical increase in initial eye
acceleration. Further increases in the flash separation produced larger
increases in latency and resulted in decreased eye acceleration. By
varying target velocity, we were able to discern that the visual inputs driving pursuit initiation show both temporal and spatial limits. For
target velocities above 4-8°/s, deficits in the initiation of
pursuit were seen when
x exceeded 0.2-0.5°, even
when
t was small. For target velocities below
4-8°/s, deficits appeared when
t exceeded 32-64
ms, even when
x was small. Further experiments were
designed to determine whether the spatial limit varied as retinal and
extra-retinal factors changed. Varying the initial retinal position of
the target for motion at 18°/s revealed that the spatial limit
increased as a function of retinal eccentricity. We then employed
targets that increased velocity twice, once from fixation and again
during pursuit. These experiments revealed that, as expected, the
spatial limit is expressed in terms of the flash separation on the
retina. The spatial limit is uninfluenced by either eye velocity or the
absolute velocity of the target. These experiments also demonstrate
that "initiation" deficits can be observed during ongoing pursuit,
and are thus not deficits in initiation per se. We conclude that such
deficits result from degradation of the retino-centric motion signals
that drive pursuit eye acceleration. For large flash separations, we
also observed deficits in the maintenance of pursuit: sustained eye
velocity failed to match the constant apparent target velocity.
Deficits in the maintenance of pursuit depended on both target velocity and
t and did not result simply from a failure of
degraded image motion signals to drive eye acceleration. We argue that
such deficits result from a low gain in the eye velocity memory that
normally supports the maintenance of pursuit. This low gain may appear because visual inputs are so degraded that the transition from fixation
to tracking is incomplete.
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INTRODUCTION |
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Smooth pursuit eye movements are used by primates
to track small moving targets. Step-ramp target trajectories,
consisting of a step in target position concurrent with the onset of
target motion, have become a standard approach for analyzing
nonpredictive features of pursuit (Lisberger and Westbrook
1985; Rashbass 1961
). Shortly after the onset of
target motion, the eye accelerates rapidly toward target velocity.
Following this rapid acceleration, eye velocity settles near target
velocity. Pursuit of step-ramp targets is thus often described as
having "initiation" and "maintenance" phases.
While dividing the response into initiation and
maintenance phases is descriptively useful, there is no evidence that
the pursuit system makes an active transition from one phase to the other, or that its responsiveness differs between the two states. Instead, analysis of pursuit has revealed two functional mechanisms that do not map directly onto the two phases of pursuit initiation and
maintenance. One mechanism, called "visuo-motor drive," relies on
visual motion inputs represented in a population code in the middle
temporal area of extra-striate visual cortex (area MT), and
transforms that code into commands for smooth eye acceleration (Dursteler et al. 1987; Groh et al. 1997
;
Morris and Lisberger 1987
; Newsome et al.
1985
). The other mechanism, called "eye velocity memory,"
converts commands for eye acceleration into signals for desired smooth
eye velocity and ensures that eye velocity will decay only slowly from
its current value in the absence of image motion (Morris and
Lisberger 1987
; Robinson 1971
;
Robinson et al. 1986
; Young et al.
1968
). Acting as an acceleration to velocity integrator, eye velocity memory is conceptually similar to, but functionally distinct from, the well-known "neural integrator" that
converts commands for eye velocity into commands for eye position
(Robinson 1989
). Visuo-motor drive and eye velocity
memory are both active during both the initiation and maintenance of pursuit. However, for step ramp targets, changes in pursuit initiation can typically be attributed to changes in visuo-motor drive, assuming that the status of eye velocity memory remains constant. Likewise, the
analysis of maintenance can be used to evaluate the status of eye
velocity memory, assuming that visuo-motor drive is sufficient to drive
the eye to the constant target velocity.
Recent reports from our laboratory have emphasized a third mechanism
that we have previously called a "pursuit switch" or "on-line
gain control" and that we will refer to here as the "engagement" of pursuit. The existence of different levels of engagement of pursuit
was previously demonstrated using brief perturbations of target motion
to probe the gain of visuo-motor drive (Goldreich et al.
1992; Schwartz and Lisberger 1994
). The gain of
the evoked pursuit response depended on whether the monkey was fixating
or tracking when the probe was presented, and on the ongoing eye/target velocity during pursuit maintenance. These experiments demonstrate that
the pursuit system is engaged to differing degrees during fixation and
ongoing pursuit. A deficit in engagement of pursuit was also proposed
as an explanation for a number of deficits in sustained eye velocity
during the maintenance of pursuit (Grasse and Lisberger
1992
; Kiorpes et al. 1996
). We have thus assumed that both visuo-motor drive and eye-velocity memory are modulated by
the state of engagement of the pursuit system. That the engagement of
pursuit influences eye velocity memory was first suggested by Robinson
(Luebke and Robinson 1988
; Robinson et al.
1986
), and is assumed by the pursuit model of Krauzlis
and Lisberger (1994)
. Visual motion thus serves a dual role in
pursuit. It is the primary input for the visuo-motor drive of eye
acceleration during pursuit, but is also necessary to engage pursuit in
the first place.
One approach to understanding the perception and neural processing of
visual motion has been to degrade the quality of motion using
"apparent motion" stimuli, consisting of flashes of a target at a
sequence of positions. Studies of human perception using different
types of targets have revealed very different spatial limits for
"short-range" and "long-range" perception of motion (Barlow and Levick 1965; Braddick 1980
;
Newsome et al. 1986
; Tyler 1973
).
Parallel analysis of human motion perception and neuronal responses in
awake monkeys have revealed a broad similarity in the spatial limit of
motion perception and the spatial limit of direction selectivity for MT
neurons (Mikami et al. 1986
; Newsome et al.
1986
). Previous studies of pursuit eye movements using apparent
motion along periodic trajectories have revealed tracking deficits when
the flash separation was increased past 80-150 ms (Fetter and Buettner 1990
; Morgan and
Turnbull 1978
; Schor et al. 1984
; Van der
Steen et al. 1983
). However, the continuous nature of the
target trajectories used in these prior studies makes it difficult to
determine whether the deficits arose because the degraded motion failed
to support normal visuo-motor drive of eye acceleration, or because the
degraded motion was insufficiently convincing to fully engage pursuit.
We now report the pursuit evoked by step-ramp target trajectories consisting of apparent motion with a range of spatial and temporal separations of the flashes. Our data reveal separable effects of apparent motion on both visuo-motor drive and eye velocity memory. Effects on visuo-motor drive were manifested as changes in the latency and magnitude of eye acceleration at the initiation of pursuit, including a paradoxical facilitation of eye acceleration over a narrow range of parameters. Effects on eye-velocity memory were manifested as sustained maintenance phase eye velocities much lower than target velocity. We interpret eye-velocity memory deficits as resulting from a failure of the visual stimulus to provide a sufficiently convincing motion signal to fully engage pursuit. Our data indicate that the engagement and subsequent visuo-motor guidance of pursuit eye movements both depend on the quality of the visual motion. We suggest that the motion signals governing engagement may not be the same as those driving eye acceleration. While deficits in visuo-motor drive were independent of extra-retinal factors such as eye and target velocity, deficits in eye velocity memory were not.
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METHODS |
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Parameterizing apparent motion stimuli
The solid line in Fig.
1A illustrates the
spatio-temporal trajectory of a horizontally moving point. As time
passes, the point moves rightward. The filled circles along this line
illustrate the trajectory of an apparently moving spot, with spatial
and temporal separations x and
t,
respectively. The apparent velocity is given by
x/
t. Smooth and apparent motion may also be
represented in the frequency domain. The transform of a single spot
contains a broad range of spatial frequencies. For a smoothly moving
spot, each spatial frequency is associated with a different temporal frequency, where velocity = temporal frequency/spatial frequency (Adelsen and Bergen 1985
; Watson and
Ahumada 1985
). The solid diagonal line in Fig.
1B illustrates this relationship. Apparent motion is
equivalent to sampling a smoothly moving stimulus and produces
aliasing. In the frequency domain aliasing produces "replicas" of
the original spatio-temporal frequency content, as shown by the dashed
lines in Fig. 1B.
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The range over which apparent motion effectively emulates real motion
can be described in the space-time domain in terms of the effective
combinations of x and
t. The same range can
also be described in the frequency domain by outlining the "window of
visibility": the range of temporal and spatial frequencies to which
the system of interest is sensitive. Apparent motion becomes noticeably
un-smooth when the replicas produced by aliasing enter this window of
visibility. We choose to describe our stimuli and the effective range
of apparent motion in the space-time domain for two reasons. First, the
spots we used are simply and intuitively described in the space-time
domain. Second, because our stimuli were actually spots, not sine wave
gratings, linearity becomes an issue when one attempts to describe the
response of either pursuit or of neural motion sensors in terms of the
responses to individual frequency components. As an example, some of
the components of an apparently rightward moving spot are in fact moving leftward (those aliasing components in the bottom right quadrant of Fig. 1B). A leftward tuned motion sensor
would, if linear, respond to these components just as surely as if the
stimulus had actually been a leftward moving grating. If nonlinear, the sensor might or might not be expected to respond. Unpublished experiments from this laboratory indicate that many MT cells fail to
respond in the way expected given the assumptions of linearity. We
therefore choose to describe the limits of apparent motion in terms of
maximum
x and
t, and not in terms of the
border of the window of visibility. This is not to deny that the latter description could be constructed, provided that the relevant
nonlinearities were understood and accounted for. Such a description
is, however, outside the scope of this paper, the goal of which is to
parameterize the limits of apparent motion for pursuit in a simple
descriptive manner that might then be compared with a similar
description of the effects of apparent motion on the response of the
population of MT neurons.
Surgical procedures
Experiments were performed on six adult male rhesus monkeys that
had been trained to pursue single moving targets. Our basic experimental methods have been presented before (e.g., Lisberger and Westbrook 1985). Briefly, monkeys were trained to track
visual targets and were rewarded with drops of water or Tang. Eye
movements were monitored using scleral search coils that had been
implanted with the technique of Judge et al. (1980)
,
using sterile procedure while the monkey was anesthetized with
Isofluorane. Postsurgical analgesia was provided for a minimum
of 2 days with Buprenorphine (0.01 mg/kg every 12 h).
During experiments, monkeys sat in a primate chair with their heads
affixed to the ceiling of the chair using a dental acrylic fixture that
had been implanted at the same time as the eye coil. Experiments lasted
2-3 h. Methods had been approved in advance by the Institutional
Animal Care and Use Committee at the University of California, San Francisco.
Visual stimuli and presentation of targets
Stimuli were presented on a 12-in. diagonal analog oscilloscope (Hewlett Packard model 1304, P4 phosphor) driven by the D/A converter outputs from a digital-signal-processing board in a pentium PC computer. This system provided us with a spatial resolution of 65,536 by 65,536 pixels and a maximum temporal resolution of 4 ms (2 ms in a few later experiments). We positioned the display 30 cm from the monkey so that it subtended a vertical visual angle of 40° and a horizontal visual angle of 50°.
Stimuli were sequences of flashes with a wide range of temporal flash
separations (t) and spatial flash separations
(
x), which were systematically varied. When
t and
x were small, the series of flashes
produced the perception of a smoothly moving target (Newsome et
al. 1986
). Thus we will refer to the series of flashes as a
target, with a given
t,
x, and apparent
velocity. As the apparent velocity of a target is given by
x/
t, the stimulus is fully defined by any
two of these three parameters. To maintain a constant mean luminance of
the target, the luminance of each flash was varied linearly with the
time between flashes (e.g., if
t was doubled, so was the
luminance of each flash). We adopted this approach instead of the
alternative (keeping individual flash luminance constant) because it
rendered pursuit targets that appeared to have similar brightness
regardless of
t, and because we anticipated it would
avoid changes in pursuit latency that would be a function of luminance
rather than of the parameters of the apparent motion itself.
Each individual target flash was very brief. The duration increased
with t, due to the extra time necessary to increase the luminance. For a
t of 4 ms each flash lasted
approximately 160 µs. Each doubling of
t doubled this
duration, so that for a
t of 64 ms each flash lasted
approximately 2,560 µs. The specifications of the display
oscilloscope indicated that the phosphor will decay to 10% of its
maximal level in 10 µs to 1 ms. The tracking target was brighter than
the fixation point (see next paragraph for description of
these targets). Photometer measurements revealed that the fixation target and tracking target had net luminances of approximately 1.6 and
25 cd/m2, respectively. Because targets were
small, roughly 0.2° across, these luminances were bright but not
dazzling. Experiments were performed in a dimly lit room. Due to the
dark screen of the display, background luminance was beneath the
threshold of the photometer, less than 1 mcd/m2.
Subsequent to an earlier review of this paper, an error was found in
the program controlling the visual stimuli. The timing of the second
flash in the sequence was often erroneous: the first two flashes would
occur immediately following one another, with the specified
t occurring only between subsequent flashes. This error
was not visible to the naked eye, but could certainly have influenced
some of our measurements of the effect of apparent motion on the
initiation of pursuit, perhaps reducing the size of the observed
deficits. All experiments were replicated following correction of the
error, using monkeys Na, Ka, and Mo. As all the
same effects were observed, we have retained the original data and
added the new data to our presentation.
Targets were presented in individual trials that began with the
appearance of a fixation point 10° to either the right or left of
straight-ahead gaze. The fixation point always had a t of
4 ms. The monkey was required to fixate this spot within 600 ms after
its appearance and to maintain fixation within a 2° window of target
position for 700-1,100 ms. The fixation point was then extinguished
and replaced 4 ms later with a tracking target that appeared eccentric
relative to the fixation point and immediately began to move toward the
position of fixation (Rashbass 1961
). For example, a
given trial might begin with the appearance of a fixation point to the
left of center. When the fixation point disappeared, the target would
appear to its left and move rightward. Because of the initial 10°
offset of the fixation point, targets were able to traverse up to 35°
before reaching the edge of the monitor. The duration of target motion
varied from 700 to 2,400 ms, depending on the speed of the target.
Quickly moving targets were extinguished when they neared the edge of
the screen. In some later experiments, and for velocities faster than
16°/s, the target was not extinguished at the end of its trajectory. Instead, it stepped forward 2-4° and remained stationary for
600-1,000 ms before being extinguished. This helped to minimize the
decrease in sustained eye velocity that often occurred near the end of a trial.
Most experiments also included "control trials," in which the tracking target appeared eccentric to the fixation spot and moved away from the fixation point toward the edge of the monitor that was closest to the fixation point. For all but the slowest velocities, the target neared the edge of the monitor quickly, at which point it stopped and fixation was enforced for up to 1,000 ms. These trials were not analyzed, but were intended to prevent the monkey from predicting the direction of target motion. In some later experiments, control trials were omitted. This had no discernable effect on pursuit within that experimental session, and no anticipatory eye acceleration was observed before the normal onset of pursuit.
Following the onset of target motion, the monkey was given 450 ms to
bring his eyes from the initial point of fixation to the target, and
was required to track the target with an accuracy of 3°. If the
monkey maintained the required fixation and tracking throughout the
trial, he was rewarded with a drop of juice. If fixation requirements
were not met during a trial, the trial was immediately aborted. For
some trials, particularly those with large values of x,
the size of the fixation window was increased to as large as 9°, to
allow the monkey to complete most trials successfully. Each experiment
consisted of multiple repeats of a list of up to 132 types of trials,
where each trial type presented a different stimulus. The trials were
sequenced by shuffling the list and requiring the monkey to complete
each trial successfully once. If he failed a trial, it was placed at
the end of the list and presented again after all the other trials had
been completed. After all trials had been completed once, the list was
shuffled and presented again. Monkeys were allowed to work as long as
they continued to complete most trials successfully, usually for
2,000-4,000 trials.
The wide range of possible parameters of apparent motion made it
impossible to evaluate all parameters within a single experimental session. Instead, we varied different parameters on different days, in
experiments designed to be complete along selected axes of the possible
parameter space. Because each experiment type required slightly
different methods for design and data analysis, we outline separately
the five basic classes of experiment reported here.
1 | |
Experiments using a single target velocity and varying flash
separation. All trials had the same target velocity of 18°/s, and up
to eight different values of ![]() ![]() ![]() ![]() |
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2 | |
Experiments using a single target velocity in which both target eccentricity and flash separation varied. These experiments were similar to those in 1) above, except we varied the size of the initial step of target position and observed the interaction of retinal eccentricity with the effects of flash separation. Within each experiment, the size of the step was randomly varied among 0.5, 3, and 7°. For steps of 0.5 and 7°, saccades were common during the first 400 ms of pursuit. When deficits were absent or small, the majority of responses nonetheless exhibited considerable presaccadic pursuit, with the first saccade occurring near the end of the rising phase of eye acceleration. | |
3 | |
Experiments varying both target velocity and flash separation. Both
apparent target velocity and ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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4 | |
Experiments presenting two steps of target velocity. These experiments
were designed to compare pursuit responses to a given apparent image
motion presented either during fixation or during ongoing pursuit.
These experiments included a) control trials in which we
recorded the initiation of pursuit for apparent target motion that
started at the position of fixation (with no position step) and
b) experimental trials in which apparent target velocity changed after pursuit initiation. For the experimental trials, the
initial target motion had a ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
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5 | |
Experiments in which ![]() ![]() ![]() ![]() |
Data acquisition
Experiments were controlled and data were acquired by computer
programs running on a UNIX workstation and a Pentium PC. The workstation provided a graphical user interface for the design and
control of the experiment, and the PC acted as a data-server and
streamed the data over the local area network for storage on the UNIX
file system. We obtained voltages proportional to eye velocity by
analog differentiation of the eye position outputs from the search coil
electronics (DC-25 Hz, 20 dB/decade), and we sampled voltages
proportional to horizontal and vertical eye position and eye velocity
at rates of 1,000 samples/s per channel. In each file, we also recorded
a series of codes to indicate the target motions we commanded, and we
used these codes in the data analysis program to reconstruct horizontal
and vertical target position and velocity.
Data analysis for the initiation of pursuit
Pursuit initiation was analyzed for experiment types 1) through 4) above. Eye velocity and position traces were initially viewed on a computer monitor and screened according to criteria that depended on the exact analysis to be done. The changes in pursuit initiation produced by apparent motion are illustrated using averages of the eye velocity response, often with eye velocity traces from individual trials superimposed. Our methods of averaging are described in more detail in a later section. Further quantification of the changes in pursuit initiation depended on the type of experiment and the prevalence of early saccades. For experiments of type 1), the great majority of saccades were delayed until after the initiation of pursuit was over. This afforded the opportunity to observe the effects of apparent motion on both peak initial eye acceleration and the latency of initial eye acceleration. For this analysis only, we smoothed the individual eye velocity traces by convolving them with a Gaussian having a standard deviation of 20 ms. For each trial we then differentiated, measured the peak eye acceleration, and estimated a value that we call "acceleration latency": the time when eye acceleration reached 63% of its peak value. For the vigorous eye accelerations evoked by fast target velocities, measurements made using the 63% criterion were typically slightly more robust than similar measurement using the time-to-peak eye acceleration. In practice, we were interested in changes in latency, and these differed only slightly whether calculated using the peak of eye acceleration, or using the 63% point. In one experiment, when target velocity was 3°/s, we did in fact use the time-to-peak eye acceleration to calculate latency, as this measure was more robust in the presence of a low signal-to-noise ratio. We chose not to use the time of the actual onset of pursuit (when initial eye acceleration first began) as a dependent variable. Estimates of the actual onset of pursuit can be made reliably by human observers for target motions that evoke sufficiently crisp initiation of pursuit that eye velocity quickly exceeds measurement noise. However, human observers cannot make such reliable estimates for low target velocities or for parameters of apparent motion that evoke lower initial pursuit eye accelerations. Numerical algorithms suffer related drawbacks. Moreover, as we shall see, a consistent effect of apparent motion was to increase the latency to normal acceleration. Effects on absolute latency were less consistent.
For all other experiments concerning the initiation of pursuit (2-4
above), saccades during the rising phase of pursuit were common. It was
therefore impossible to make the acceleration based measurements, as
peak acceleration was potentially obscured by a saccade. However, at
least when t was small, and deficits absent to moderate,
most early saccades occurred near the end of the rising phase of
pursuit, at least 50-100 ms after initiation. We therefore chose to
assess initiation by measuring eye velocity at a fixed time, after
normal pursuit onset but before saccades occurred. We defined the
"normal" time of pursuit onset using the average eye velocity when
t was 4 ms. For all trial types we then measured eye
velocity at a fixed time following the normal onset. This method is
illustrated in Fig. 6. The measurement time was selected to fall during
the rising phase of pursuit, as close as possible to the end of the
open loop interval, and before the time of most saccades. The exact
time ranged from 50 to 70 ms and depended on the duration of the open
loop interval of the monkey being studied. Minor errors in estimating
either the duration of the open loop interval or the time of the onset
of pursuit would not have had a major impact on this analysis, as the
same measurement time was used for all values of
t at a
given apparent target velocity.
We discussed above three scalar measures of pursuit initiation: peak acceleration, acceleration latency, and eye velocity at a fixed time. When a given measure was made, it was made for each individual trial of a given type. Averages and standard errors were then calculated. For experiments of type 3) above, responses to target velocities below approximately 4°/s suffered from a signal-to-noise problem. Large numbers of trials (at least 20-50) were needed to make accurate measurements of eye velocity at a fixed time. As these experiments employed a range of velocities and many trial types, it was often not possible to collect more than 20 trials of each type (some of which would have to be excluded because of early saccades, as described below). Measurements at low velocities were therefore sometimes quite variable, preventing us from analyzing pursuit for target speeds slower than 2°/s.
In examining the initiation of pursuit, we were primarily interested in
changes in the pursuit trajectory, rather than in the absolute values
of latency, eye velocity, or eye acceleration. Thus the three measures
described above are expressed in normalized form. Peak acceleration is
expressed as the proportion of the average peak acceleration seen for
the same target velocity when t was 4 ms. The eye
velocity measure is normalized by the average eye velocity at the same
fixed time when
t was 4 ms. Acceleration latency is
expressed as the time shift relative to the average acceleration
latency measured when
t was 4 ms. An assumption of much
of our analysis is that a
t of 4 ms produces normal
pursuit, and that the pursuit response to such targets would not have
changed had we been able to decrease the temporal separation further. This appears likely for two reasons. First, with the exception of the
highest apparent target velocities (32-45°/s), pursuit performance
was not altered by doubling the temporal separation to 8 ms. For the
highest target velocity of 45°/s, a
t of 4 ms is
probably only just acceptable, as doubling
t to 8 ms does produce a small deficit. Second, in some later experiments, we were
able to test performance at a
t of 2 ms, revealing that it was identical to performance when
t was 4 ms, even for
target motion at 45°/s.
For all analyses, the onset of target motion was defined to be
coincident with the first flash of the tracking target. However, no
directional information is available until after the second flash. It
might therefore appear that the onset of target motion should be
defined as the time of the second flash, and that effects of varying
t should be assessed after aligning the responses at this
time. However, a simple example illustrates how aligning the data on
the second flash would introduce artifacts. At many target velocities,
pursuit initiation was identical when
t was 4 and 16 ms.
If we had aligned these responses on the second flash by shifting the
response 12 ms left when
t was 16 ms, then we would have
found that pursuit initiation was earlier when
t was 16 ms than when
t was 4 ms. We thus opted not to shift the
timing of the responses, even though it is to be expected that
initiation deficits at large values of
t will be due at
least partially to the delay in motion information until after the
second flash.
Exclusion of trials with early saccades for analysis of the initiation of pursuit
In all analyses of pursuit initiation, some trials inevitably
contained saccades that made the chosen measurement impossible. The
analysis of acceleration described above was employed when saccades
were rarely observed during the rising phase. However, the occasional
saccade still fell within the rising phase. Similarly, the analysis of
eye velocity at a fixed time was occasionally confounded by a saccade
at or before that time. In such cases the trial was typically excluded
from analysis. A sole exception was made in the analysis of
acceleration. Some longer values of t produced initiation
so delayed and slow that there were often saccades during the rising
phase. Such trials were included (after interpolation of saccades, see
next section) so long as saccades were delayed by at least 400 ms following target motion onset. To the degree that linear
interpolation of saccades is imperfect, measurements of the precise
size of large initiation deficits will be imperfect.
Trials with saccades before or during the measurement interval were
excluded not only because saccades obscure pursuit eye velocity, but
also because saccades are known to enhance subsequent pursuit
(Lisberger 1998). If we had included measures made after the first saccade in our analyses of the initiation of pursuit, then
postsaccadic enhancement of pursuit might have created effects that
resulted indirectly from the relationship between different targets and
the latency of the first saccade. However, exclusion of trials with
early saccades raises the concern that early saccades occurred
primarily when pursuit was deficient, and that the exclusion of trials
with early saccades might therefore reduce the visibility of deficits.
We spot-checked a handful of cases in which early saccades were common,
comparing presaccadic pursuit when saccades were early in initiation to
that when saccades were late. The magnitude of presaccadic eye
acceleration was uninfluenced by the timing of subsequent saccades, and
no consistent or statistically significant effects were seen.
In instances when the majority of responses contained early saccades,
we did not attempt to analyze the data. For experiments using a range
of apparent target velocities and values of t, the
leftward pursuit of two monkeys (Fi and Ka) had
to be discarded because early saccades were very common at slower
apparent velocities. For experiments that varied the eccentricity of
the moving targets, monkeys El and Da were unable
to provide sufficient usable responses. Some monkeys had very few early
saccades (Mo and Na in both directions, and
Ka in the rightward direction) and were particularly useful in experiments in which eccentricity could not be optimized. We realize
that the prevalence and latency of early saccades in response to
step-ramp targets varies among publications from different laboratories, and we attribute the delayed saccades and excellent presaccadic pursuit in many of our monkeys to the extensive experience they have with targets that could be tracked successfully with very few saccades.
Data analysis for the maintenance of pursuit
For analysis of the maintenance of pursuit, saccades were excised from each individual eye velocity trace, either by a user-supervised and verified semi-automatic algorithm or by using a cursor to point out the start and end of each rapid deflection of eye velocity. Each rapid deflection was replaced with a line segment that connected the eye velocities before and after the excision. Eye velocity traces then were aligned on the onset of target motion, averaged, and filtered with a 25-Hz digital filter. This cutoff frequency reduced noise with no noticeable effects on the basic trajectory of either the initiation or maintenance of pursuit. For the maintenance of pursuit, our main documentation of the effects of changing the parameters of apparent motion consists of averages of eye velocity as a function of time. However, we will also show that average eye velocity traces are representative of single trial performance during both the initiation and maintenance of pursuit.
The analysis of pursuit maintenance necessarily includes epochs of
pursuit that contain saccades. Nearly every pursuit response contained
at least one saccade during maintenance. Experimental manipulations
that impair pursuit maintenance further increase the prevalence of
saccades, both in prior studies (Dursteler and Wurtz
1988; Dursteler et al. 1987
) and in our data. It
was thus necessary to analyze pursuit in a way that preserved as best
as possible the eye velocity component produced by the pursuit system, but ignored the eye velocity component produced by the saccadic system.
Inspection of our data showed relatively little change in smooth eye
velocity before and after saccades during the maintenance of pursuit,
implying that linear interpolation across the excised saccadic eye
velocity is valid during the maintenance of pursuit. Saccades sometimes
facilitated eye velocity during maintenance, but this effect was small.
Another workable method is to excise each saccade, but to treat the
missing time points as missing data during averaging. This approach
essentially replaces each saccade with averaged data from other trials
that do not have a saccade at that time. This approach only appears to
avoid the necessity of interpolation. The replacement data may or may
not be a good estimate of the saccade-obscured pursuit for that
particular trial. Averages of excised data are particularly
unlikely to provide a good estimate of the excised pursuit if
maintained pursuit eye velocity varies from trial to trial, as was
often the case when maintenance was impaired. In fact, both methods in
practice provide very similar results during maintenance. Still, the
method of saccade replacement by linear interpolation seemed better
suited to our purposes. It should be noted that the maintenance
deficits we observe below are large and could be neither produced nor
obscured by any reasonable method of dealing with saccades.
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RESULTS |
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Figure 2 shows a typical pursuit
response for a target that moved with an apparent velocity of 22°/s
and a t of 16 ms. Although the stimulus consisted of
sequential flashes of a stationary target at the times indicated by
dots, both the eye position and velocity profiles appear normal (e.g.,
Lisberger and Westbrook 1985
). Pursuit began about 100 ms after the onset of target motion: the eye accelerated rapidly toward
target velocity, and maintained eye velocity settled near target
velocity with only small fluctuations. The first saccade (arrows on the
eye position and velocity traces) occurred more than 200 ms after the
initiation of pursuit, after the end of the initial rising phase.
|
Pursuit initiation shows changes with increasing flash separation
In the first part of the paper, we analyze deficits in the
presaccadic initiation of pursuit. In so doing, we explicitly avoid showing examples of deficits in the maintenance of pursuit, which are
analyzed in the second part of the paper. Apparent motion had effects
of three types on pursuit initiation: 1) increases in the
latency to peak eye acceleration, 2) decreases in peak eye
acceleration, and 3) unexpected increases in peak eye
acceleration. The left column of Fig.
3 illustrates an effect of the first
type. Figure 3A shows 10 single trial responses (thin
traces) of monkey Ka to target motion with an apparent
velocity of 16°/s and t of 4 ms. These traces are
superimposed on the average response for all trials of this type (bold
trace). Figure 3B shows a similar plot for target motion at
the same apparent velocity but with a (longer)
t of 32 ms. The average responses in Fig. 3, A and B, are
similar in that both exhibit crisp initial eye acceleration, a small
overshoot of target velocity, and a steady-state gain of near unity.
Comparison of the averaged and individual traces shows that the
individual traces are well represented by the averages. Superposition
of the two averages of eye velocity (Fig. 3C) reveals that
peak initial eye acceleration was delayed when
t was 32 ms, although the magnitude of peak eye acceleration appears similar. Note that the latency to the onset of pursuit appears little affected: it is the latency to normal eye acceleration that increased. Subsequent figures show examples where the onset of pursuit was also delayed. Effects of apparent motion on the latency of the onset of pursuit were
generally less consistent than the effects on the latency to peak eye
acceleration. We term this latter measure "acceleration latency."
|
In addition to producing increases in the acceleration latency,
increases in t often produced decreases in peak eye
acceleration. For example, Fig. 3D shows responses of
monkey Ka to target motion at an apparent velocity of
32°/s and
t of 4 ms. Figure 3E shows a
similar plot for data obtained when
t was increased to 48 ms. Superposition of the average eye velocity traces for different values of
t reveals a clear progression of deficits (Fig.
3F). Increasing
t from 4 to 24 ms caused an
increase in acceleration latency accompanied by a small decrement in
initial eye acceleration. A further increase of
t to 48 ms (dashed trace) caused a larger increase in acceleration latency and
a clear decrement in initial eye acceleration. For all three values of
t, eye velocity eventually reached a sustained value that
was close to target velocity. Note in Fig. 3, D and
E, that the averages made after linear interpolation across
excised saccades provide a reasonable estimate of pursuit eye velocity
during the period obscured by the saccades. Of course, there is no way
of directly observing the underlying pursuit eye velocity during this
period. Therefore all subsequent quantitative analysis of pursuit
initiation is limited to time periods that were saccade free.
Analysis over a finer grain of values for t revealed that
as
t was increased, initial eye acceleration at first
increased and began to decrease only for still larger values
of
t. These effects are illustrated in Fig.
4 using averages of eye velocity and
acceleration. For the experiment summarized in Fig. 4A, an increase in
t from 4 ms (bold traces) to 32 ms (fine
traces) caused an increase both in acceleration latency and in peak eye acceleration. Further increases in
t to 48 ms (dashed
traces) caused the expected decrease in peak eye acceleration. For the experiment summarized in Fig. 4B, peak eye acceleration
increased as
t was increased from 4 to 16 ms. Peak eye
acceleration remained above normal at a
t of 20 ms and
was reduced when
t was 32 ms. The latency to peak
acceleration increased when
t was 20 ms or larger.
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The increases in peak eye acceleration were not due to any effects of saccades, as all the above described data were collected under conditions that produced few saccades during the initiation of pursuit, and rare trials with saccades before the peak of acceleration were excluded from the analysis. Neither do the increases in peak eye acceleration result from any compensation for the longer latency of pursuit. This explanation assumes the pursuit system knows it is "behind," and compensates to "catch up." This is unlikely, as the increase in acceleration was regularly observed within the open loop interval (60-80 ms), before visual feedback could have any impact. Further, the increase in acceleration cannot result from compensation for increased latency, as it occurred even when pursuit initiation was not delayed (e.g., Fig. 4B and Fig. 5, monkeys Mo and Na). We therefore postulate that the increase in initial eye acceleration results because the relevant flash separations produce a larger than normal image velocity signal. This explanation is developed further in the discussion.
|
As t increased, changes in acceleration latency and peak
eye acceleration followed different trajectories. We measured peak eye
acceleration and the acceleration latency for each individual trial, as
described in METHODS. The graphs in Fig. 5 compare the progression of changes in these two measures as a function of
t. Target velocity is held constant within each graph.
Data are shown for four monkeys. Average peak eye acceleration (
) is
plotted as a fraction of that obtained when
t was 4 ms.
Average acceleration latency (
) is plotted as the time shift from
when
t was 4 ms. Sign conventions were chosen so that the
horizontal dashed line shows normal performance and deficits are
plotted as decreases on either y-axis. In the three examples
in the left column, latency began to increase when
t exceeded 16 ms and increased progressively as a
function of
t. Peak eye acceleration first increased,
starting with values of
t as low as 12 ms, and then
declined below normal only for relatively large values of
t. Statistically significant latency increases, peak
acceleration increases, and peak acceleration decreases were observed
in the experiments using Mo, Na, and Ka. The
responses of monkey El are discussed below.
The three experiments shown in the left column of Fig. 5
were designed to reveal the typically small increase in eye
acceleration that occurs over a narrow range of flash separations.
These experiments also illustrate a more general finding. As
t was increased, deficits in acceleration latency were
produced prior to the production of deficits in the magnitude of eye
acceleration (although not necessarily before the production of
increases in eye acceleration). For the plots in the
left column, the open symbols denoting acceleration latency
are always below the filled symbols denoting peak acceleration. This
pattern was consistently observed for all experiments and all monkeys,
with a single exception, illustrated in the bottom right
panel. For rightward moving targets, monkey El showed
the inverse pattern: as
t increased, eye acceleration was
significantly reduced at values of
t that did not cause
any increase in acceleration latency. We do not know why the changes
observed in the rightward pursuit of monkey El are so
atypical. However, the rightward pursuit of monkey El was
unusual in a number of other respects and had an onset latency of 130 ms, nearly twice that of most monkeys and of monkey El's
own leftward pursuit. The leftward pursuit of monkey El
shows the more typical pattern: deficits are observed in acceleration
latency before any deficits are observed in peak eye acceleration. For
the leftward pursuit of monkey El, the lack of statistically
significant increases or decreases in eye acceleration were probably
due to an insufficient number of trials and to the limited range of
values of
t employed, as both effects were observed in
other experiments using the same monkey (data not shown).
Spatial and temporal limits on the initiation of pursuit
The above-described results reveal that apparent motion causes
consistent deficits in pursuit, but do not reveal the cause of the
deficits. At a given target velocity, t and
x increase together. To ask whether the spatial or
temporal separation between flashes is the limiting factor, we observed
the effect of a given
t at multiple target velocities.
The same
t is associated with large values of
x at high velocities and small values of
x
at low velocities. Figure 6 shows the
time course of average eye velocity during the initiation of pursuit at
three apparent target velocities and three values of
t.
For a target speed of 32°/s (Fig. 6A), deficits in the
initiation of pursuit were present at values of
t as low
as 16 ms and became severe when
t was increased to 32 ms.
As target speed was lowered, the deficit associated with each value of
t was reduced. For a target speed of 16°/s (Fig.
6B), a deficit was visible only when
t was 32 ms (dashed trace). For a target speed of 8°/s (Fig. 6C),
the deficit was mild even when
t was 32 ms. That the
deficits associated with a given
t are diminished as
target velocity decreases indicates that they are related to the
decreasing spatial separation.
|
These effects are quantified in Fig. 7,
which shows the effect of target speed on the magnitude of deficits in
the initiation of pursuit for two values of t in three
monkeys. In these experiments, it was not possible to optimize all
trial types so as to minimize early saccades while maintaining the same
starting eccentricity across velocities (see METHODS). As a
result, peak eye acceleration often was obscured by saccades,
especially for flash separations that produced increases in latency. To
circumvent these problems, we measured average eye velocity at a fixed
presaccadic time during the rising phase of pursuit (vertical dashed
line in Fig. 6) and normalized by the average eye velocity evoked at
the same time, by the same target velocity, when
t was 4 ms. Normalized eye velocities less than one indicate initiation
deficits. This metric does confound the effects of increases in
acceleration latency and decreases in eye acceleration and indicates
only the degree to which pursuit initiation is normal or abnormal
without indicating the nature of the underlying deficit. However, small
to moderate decreases in normalized eye velocity were caused primarily
by latency deficits, as these appeared first.
|
Inspection of the data in Fig. 7 reveals both spatial and temporal
limits on the presaccadic initiation of pursuit. When t was 16 ms (open symbols), eye velocity was normal for target speeds up
to 12-16°/s and then declined steeply. Because
t was
fixed at 16 ms, the deficits at higher target speeds must be due to an
excessive
x. In contrast, when
t was 64 ms
(filled symbols), eye velocity was not normal even for the lowest
target speeds. For such slow target speeds, the values of
x associated with a
t of 64 ms were
sufficiently small to have evoked normal pursuit initiation when
t was 16 ms. For example,
x was identical
when
t was 64 ms at 2°/s and when
t was
16 ms at 8°/s. Yet eye velocity is normal for the latter parameters
and about half normal for the former. We therefore argue that the
deficit in the former case cannot be due to
x and must be
due to the fact that
t was 64 ms. In summary, although in
all figures we express the flash separation in terms of
t, the temporal separation is the limiting factor only
for slow target velocities. For faster target velocities, deficits are
actually produced by the associated
x.
For values of t < 32 ms, the disappearance of deficits
when the target is slowed rules out a tempting explanation for these deficits: that they result from the delay in motion information until
after the second flash. This explanation is unlikely for another
reason. Latency deficits are often too large to be explained by the
separation of the first two flashes. In Fig. 6B, for
example, a 16-ms increase in
t, from 16 to 32 ms, delayed
the initiation of pursuit by nearly 40 ms. In each of the graphs in the
left column of Fig. 5, the rate of increase in acceleration
latency at high values of
t exceeds the rate of increase
in
t.
To visualize simultaneously the spatial and temporal limits governing
pursuit initiation, we measured eye velocity during the initiation of
pursuit for a range of combinations of t and
x, where apparent velocity is
x/
t. The symbols in Fig.
8 plot normalized eye velocity as a
function of
t and
x. The magnitude of
initial eye velocity is indicated by the size of the symbol, with
filled symbols denoting eye velocities within 90% of normal. Although
the plots from different monkeys are quantitatively different, there is
a broad qualitative pattern. In each graph, the filled symbols denoting
normal or nearly normal pursuit cluster in the bottom left corner.
The range of parameters that evoked nearly normal eye velocities can be
exited by traveling either vertically or horizontally, indicating that
normal initiation is bounded by both a spatial and a temporal limit.
Traveling vertically within a graph keeps
t constant, as
in Fig. 7, while traveling horizontally keeps
x constant.
Target velocity remains constant along the diagonal lines, at values
indicated by the numbers along the top and right
sides of each graph. All four monkeys tested with target speeds up
to 45°/s showed a limit on pursuit initiation expressed primarily in
terms of
x (Fig. 8, C-F). At lower target
velocities, pursuit faltered before this spatial limit was reached,
indicating that pursuit initiation is also limited by
t.
The temporal limit is particularly clear in Fig. 8B. Defined
as the point at which eye velocity falls below 90% of normal, the
spatial limit lay between 0.2 and 0.4° for five monkeys, and between
0.5 and 1° for the sixth (Fi). The temporal limit lay
between 32 and 64 ms. The plots are somewhat noisy, especially at low
target velocities, because of the large number of trial types used in
these experiments.
|
Deficits observed when x becomes too large are assumed to
arise because the spatial integration ability of neural motion sensors
is exceeded. Are the deficits observed when
t becomes too
large related to the temporal integration time of neural motion sensors? We concluded above that deficits seen when
t was
32 ms or less were not due to the delay in motion information until the
second flash, as they disappeared when the target was slowed. However,
this conclusion does not apply to the deficits observed when
t is large, which persist at slow target velocities. In the extreme, delays in the arrival of motion information obviously must
contribute: a monkey with a pursuit latency of 80 ms could not initiate
normal pursuit when
t is 96 ms. Still, there is some
reason to believe that initiation deficits seen when
t is large result in part from a failure of neural motion sensors. Figure
9 plots peak eye acceleration and
acceleration latency as a function of
t for monkey
Ka at a target velocity of 3°/s. Little or no deficit is
observed when
t is 32 ms, while a large latency deficit
is observed when
t is 64 ms. Latency increased 55 ms,
while
t increased only 32 ms. The deficit is 23 ms larger than expected if the latency increase were due solely to the additional 32-ms delay between the first and second flash. As
x is
0.192° when
t is 64 ms, just below the spatial limit of
0.2-0.4° seen for Ka in Fig. 8, the additional 23 ms of
delay are probably not the result of excessive spatial separation. This
suggests that while a
t of 32 ms is within the
integration time of the neural motion sensors driving pursuit, a
t of 64 ms produces deficits in part because it exceeds
the temporal integration time. A similar argument can be based on the
deficits in eye acceleration seen in Fig. 9. These deficits appeared
when
t was 64 ms or longer, corresponding to a
x of 0.19°. At higher target velocities, a
x of at least 0.58° was necessary to produce deficits
in eye acceleration. Thus it appears likely that, at least to some
degree, deficits produced by large
t's result because
the stimulus exceeds the temporal integration abilities of neuronal
motion sensors. These conclusions should, however, be viewed as
tentative, in part because they rest on the assumption that the spatial
limit is similar across velocities. This assumption may be true only to
a first approximation. Figure 9 shows data only for monkey Ka because only this monkey produced sufficiently regular pursuit at low velocities to allow an analysis of eye acceleration in individual trials. However, similar effects were observed in the averaged eye velocity traces of other monkeys (data not shown).
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Spatial limit is eccentricity dependent
In humans, the spatial limit governing the perception of short
range apparent motion has been shown to increase with eccentricity (Braddick and Baker 1985). The spatial limit
governing the direction selectivity of MT neurons shows a similar
increase with eccentricity (Mikami et al. 1986
). To
determine whether the spatial limit governing pursuit initiation was
eccentricity dependent, we measured the effect of changing
x on the initiation of pursuit for three values of
initial target eccentricity. Target velocity was 18°/s. Different eccentricities were created using initial target position steps of
different sizes. The three sets of traces in the left column of Fig. 10 show averaged eye velocity
as a function of time and illustrate typical deficits. Flash separation
is expressed in terms of
t, but, given the results
described in previous figures, it is presumed that, for
t < 32 ms, deficits arise from the associated value
of
x. When eccentricity was 0.5° (Fig. 10A),
deficits in the initiation of pursuit appeared when
t
increased from 4 ms (bold, solid trace) to 16 ms (fine, solid trace)
and worsened when
t was increased further to 24 ms
(dashed trace). When eccentricity was 3° (Fig. 10B),
deficits were observed only when
t increased from 16 to
24 ms. When eccentricity was 7° (Fig. 10C), there was little deficit in the initiation of pursuit even when
t
was 24 ms.
|
Using the methods described earlier, we quantified the effects of
eccentricity in three monkeys by measuring average eye velocity 50 ms
after the normal time of initiation. This measurement time is indicated
by the dashed vertical lines in Fig. 10, A-C. The histograms at the right of Fig. 10 show how changes in flash
separation affected the initiation of pursuit for targets presented at
different eccentricities. Each panel represents a given eccentricity
and contains three groups of histogram bars, one group for each monkey. The four bars within each group correspond to four values of
t. All monkeys showed the same basic effects. When
eccentricity was 0.5° (Fig. 10D), initial eye velocity
declined consistently as a function of
t, starting when
t increased from 4 to 16 ms. When eccentricity was 3°
(Fig. 10E), initial eye velocity did not decline until
t was at least 24 ms. When eccentricity was 7° (Fig.
10F), the only clear declines in initial eye velocity
occurred when
t increased from 24 to 32 ms. Thus the
effect of increasing the flash separation was reduced at larger
eccentricities. Again, although flash separation is expressed in terms
of
t, most deficits are expected to be due to the spatial
flash separation. Deficits first appeared at values of
x
around 0.29° (
t = 16 ms) when starting
eccentricity was 0.5°, and around 0.57° (
t = 32 ms) when starting eccentricity was 7°.
Effect of imposing steps of apparent target velocity during ongoing pursuit
A number of previous papers have pointed out that image
motion plays a dual role in pursuit. It must both 1) engage
pursuit by initiating the active transition from fixation to pursuit
and 2) provide the primary feed-forward drive producing eye
acceleration (Goldreich et al. 1992; Kawano and
Miles 1986
; Luebke and Robinson 1988
;
Morris and Lisberger 1985
; Robinson
1965
). The effects of apparent motion on the initiation of
pursuit could arise either because the pursuit system takes longer to
become fully engaged when a degraded motion signal is present, or
because the motion signals driving eye acceleration are delayed and
weakened. To distinguish between these two possibilities, we compared
pursuit initiation from fixation with pursuit responses to changes in target velocity, after pursuit had been engaged. Control trials were
used to study initiation, and provided a single step of target velocity
with different values of
t. To allow comparison of
pursuit initiation with responses to changes in target velocity, the
onset of target motion was not accompanied by a position step. As with all the above experiments,
t was 4 ms during fixation and
was changed only when the target began to move. Experimental trials provided two steps of apparent target velocity. The first target velocity step retained a
t of 4 ms, while the second step
increased target speed and provided the
t of interest.
This design enabled the monkey to achieve nearly perfect tracking so
that the image velocity produced by the second step was nearly equal to
the change in target velocity. We were thus able to compare the
response to a given image motion seen during fixation with the response to the same image motion seen during active pursuit. We expected one of
two outcomes for this experiment. If apparent motion causes the
initiation of pursuit to suffer because pursuit engagement is delayed,
then responses to changes in target velocity should exhibit reduced
deficits, as pursuit is already engaged. If deficits are due to
degradation of the motion signals driving eye acceleration, then
deficits in the responses to target velocity changes during pursuit
should be identical to deficits produced in pursuit initiation. An
assumption of this approach is that pursuit, once engaged by the first
step, is not disengaged by the second step.
Figure 11A shows averages of
eye velocity illustrating the effect of t on the response
to a 30°/s target velocity step. At the time of the target velocity
step, the animal was fixating the stationary target. As
t
progressed from 4 to 32 ms (trace weights moving from solid to short
dashes to long dashes), pursuit initiation became progressively more
impaired. Figure 11B shows the same progression of deficits
in response to a 30°/s step of target velocity that was imposed
during maintained pursuit at 2°/s (i.e., from 2 to 32°/s). Every
t that produced a deficit in the response from fixation
produced a similar deficit in the response to a change in target
velocity. Deficits in the response to the velocity step were not
reduced by prior engagement of pursuit. Furthermore, the second step
did not cause any decline in sustained eye velocity prior to the
pursuit response for any of the values of
t used. The
absence of any decline argues that pursuit remained engaged when the
second step was presented.
|
These and related data are quantified in Fig.
12. The three graphs show data for
three different monkeys and plot average eye velocity, measured 50 ms
after the relevant step of target velocity, as a function of
t. Different symbol types plot responses for different
initial and final target velocities. Deficits in the response to
30°/s steps of target velocity were the same whether that step took
velocity from 0 to 30°/s (filled circles) or 2 to 32°/s (open
circles). Similar experiments were performed using target velocity
steps of 10°/s. Again, deficits were very similar whether the steps
took velocity from 0 to 10°/s (filled squares), from 2 to 12°/s
(open squares), or from 20 to 30°/s (open diamonds). Prior engagement
of the pursuit system did not diminish deficits. What we have referred
to as "initiation deficits" are not therefore deficits in the
initiation of pursuit per se, but rather are deficits in the
visuo-motor processing of image motion for the purpose of producing eye
acceleration.
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Figure 12 also addresses an assumption of some models of smooth pursuit
eye movements: that the visuo-motor processing that produces eye
acceleration occurs in retinal coordinates (Goldreich et al.
1992; Krauzlis and Lisberger 1994
;
Ringach 1995
). If deficits recorded at the initiation of
pursuit result from the impairment of motion processing in retinal
coordinates, then the deficits should be independent of target and eye
velocity, and of the absolute spatial separation of the flashes. They
should depend only on the retinal flash separation. Figure 12 shows
that this was indeed the case. When targets changed velocity, deficits
were linked to the retinal
x produced by the second step,
and not to the spatial
x. For example, all 10°/s
velocity steps from the three different initial target velocities
produced similar retinal image velocities and similar values of retinal
x, and all three produced similar deficits at a given
t. If the absolute
x were the relevant factor, then deficits in the responses to steps that take target velocity from 20 to 30°/s should occur at values of
t
one-third those needed to produce deficits for steps of target velocity from 0 to 10°/s. Instead, deficits became apparent when
t approached 20 ms regardless of the final target speed.
These data also indicate that the underlying eye and target velocity
have little effect on the magnitude of visuo-motor deficits produced by
a given retinal flash separation. These conclusions might seem
inevitable, but they are in contrast with the clear influence of
extra-retinal factors on maintenance deficits, described in the next section.
In two monkeys (Fig. 12, A and B), final
eye/target speed did have a small effect on the magnitude of deficits
at larger values of t: open diamonds are below the two
square symbols when
t is 32 ms. At least for monkey
Mo (Fig. 12B), this is probably because the gain of his
pursuit maintenance was slightly less than one when target velocity was
20°/s. Image velocity was actually 12°/s when target velocity
stepped from 20 to 30°/s, rather than the intended 10°/s, yielding
a slightly larger retinal
x. Alternately, we present
evidence below that deficits in pursuit maintenance do
depend on extra-retinal factors, are produced primarily at fast
eye/target velocities and large flash separations, and involve deficits
in processes other than visuo-motor drive. None of the stimulus
parameters used produced maintenance deficits in these experiments.
Nonetheless, when
t was 32 ms, the slight increase in
deficit size at the highest eye/target velocity suggests that the
deficit in visuo-motor drive is compounded with further deficits that
are related to extra-retinal factors. An extreme example of
such a compound deficit can be seen in Fig. 17, described later. For
all other stimulus configurations presented in Fig. 12, the consistency
of deficit size despite changes in absolute target velocity implies
that extra-retinal factors have negligible impact on deficits in
visuo-motor drive.
Maintenance deficits were produced by large flash separations
All the deficits discussed so far have been deficits in pursuit
initiation, with no concurrent deficits in pursuit maintenance. However, for some large flash separations, pursuit maintenance was impaired. For example, Fig.
13 shows pursuit responses of
monkey Na to 30°/s targets when t was 4 and
96 ms. When
t was 4 ms (Fig. 13A), the
initiation of pursuit was brisk and sustained eye velocity reached
target velocity. When
t was 96 ms (Fig. 13B), initial eye acceleration was both delayed and weak. Eye acceleration ceased before target velocity was reached, and the target was tracked
with a combination of deficient pursuit and frequent saccades. To show
that the averages of eye velocity are consistent with the responses in
individual trials, the eye velocity responses from individual trials
(fine traces) are superimposed on the averages (bold traces).
Inspection of the individual traces, in which intervals where saccades
were excised have not been replaced with line segments, also shows that
our method for analyzing eye velocity neither created nor obscured
these deficits. Because saccades would confound any averages of eye
position, we have superimposed the eye position traces from many
individual trials in the bottom half of Fig. 13. These
traces reveal that the eye was consistently behind the target in Fig.
13B, so that retinal image position was a few degrees eccentric, just as it was during the initiation of pursuit.
|
The most obvious explanation for the observed deficits in pursuit
maintenance is that they, like deficits in pursuit initiation, result
from a failure of the motion signals driving eye acceleration. If eye
acceleration is weak, then target velocity cannot be reached during the
course of the trial. A number of lines of evidence argue that this
explanation is incorrect. First, maintenance deficits were sometimes
observed despite considerable initial eye acceleration. In Fig.
14A, target velocity was
32°/s and t was 48 ms. Had it been maintained, initial
eye acceleration (prior to the saccade) would have been sufficient in
most trials to bring eye velocity to target velocity. In fact, eye
acceleration fails before target velocity is reached; eye velocity
actually reaches a peak and then decays somewhat, both in the average
(bold trace) and in most of the responses from individual trials (fine
traces). Figure 14B shows averages of eye velocity from the
same experiment when the value of
t was 4, 32, 48, and 64 ms, revealing a progression of deficits in both the initiation and
maintenance of pursuit. A mild maintenance deficit could be seen even
when
t was 32 ms. Although not shown, in this experiment
a
t of 64 ms produced deficits in initiation but
not maintenance for target velocities of 8°/s or slower.
|
One might reason, in Fig. 14A, that the presence of saccades
is partially responsible for the decline in eye acceleration. However,
saccades typically enhance postsaccadic eye velocity at the initiation
of pursuit (Lisberger 1998). Even if saccades were
disruptive rather than facilitory, eye acceleration would be expected
to resume following the saccade, especially as the retinal
x is less during defective pursuit maintenance that
during the target motion that initiates pursuit. The most likely
explanation for the data in Fig. 14 is that maintenance deficits result
from a failure of eye velocity memory to support eye velocity and to integrate eye acceleration commands. As discussed in the introduction, eye velocity memory is a postulated mechanism that integrates eye
acceleration commands and maintains current eye velocity if no
acceleration command is given. For a number of reasons, including the
quick decline of eye velocity following target offset, eye velocity
memory is presumed to be modulated with the engagement state of
pursuit. The state of engagement of pursuit may in turn be modulated by
the quality of the motion stimulus provided by the target.
The experiment shown in Fig. 15 further
bolsters the conclusion that deficits in the maintenance of pursuit
result from a partial failure of eye velocity memory. Each of the two
experiments shown consisted of three trial types. When t
was 4 ms (solid traces labeled "4 ms"), initiation was brisk and
the steady-state gain was near one. When
t was 64 ms
(Fig. 15A, dashed traces) or 96 ms (Fig. 15B,
dashed traces), eye acceleration was weak at the initiation of pursuit
and maintained smooth eye velocity was about half of target velocity.
If
t was initially 4 ms and was then changed to the
longer value at the time indicated by the vertical arrows (solid traces
labeled "4
64" and "4
96"), then eye velocity settled
quickly into a maintenance deficit following the increase in
t. In both examples in Fig. 15, the final eye velocity
was very close to that obtained when the longer
t was used from the outset. Thus large values of
t produced
maintenance deficits even after eye velocity had reached
target velocity, confirming that maintenance deficits result from a
failure of eye velocity memory, and not simply from a failure of
initial eye acceleration.
|
Deficits in the maintenance of pursuit are not in retinal coordinates
When we examined deficits in the initiation of pursuit, we
expressed the limits of normal eye acceleration in terms of
t and the retinal
x. It is natural to wish
to do the same for pursuit maintenance, but it does not appear that the
limits on normal maintenance can be expressed in these terms. Figure
16 shows the initiation and maintenance of pursuit
for two monkeys when
t was 4 or 64 ms and apparent target
velocity was 16°/s (bottom panels) or 32°/s (top
panels). When
t was 64 ms, deficits in the
maintenance of pursuit were present at an apparent target velocity of
32°/s (Fig. 16, A and C), but were
reduced or absent at 16°/s (Fig. 16, B and D).
These examples make a number of points. First, like many initiation
deficits, maintenance deficits cannot result simply from an excessive
t. Second, it is equally difficult to link maintenance
deficits to a particular spatial limit, at least in retinal terms. In
Fig. 16, B and D, when target velocity was
16°/s, a
x of 1° (associated with a
t
of 64 ms) produced impaired but still reasonable eye acceleration
during initiation of pursuit. The same retinal
x of 1°
(also associated with a
t of 64 ms) is achieved during
the impaired pursuit of the 32°/s target (at the times indicated by
arrows in Fig. 16, A and C), yet there is little
further eye acceleration toward target velocity. In general, any
deficit linked solely to the retinal
x should be reduced
as the eye accelerates, facilitating further eye acceleration. During
maintenance deficits, just the reverse happens. Last, if we accept the
conclusion argued above that the spatial and temporal limits of
visuo-motor drive are expressed in retinal terms, then these examples
illustrate that maintenance deficits do not result solely from a
failure to convert retinal motion signals into eye acceleration
commands. The retinal
t and
x of 64 ms and
1° are sufficient to produce considerable eye acceleration in Fig.
15, B and D. The failure of these same retinal
parameters to produce eye acceleration in Fig. 15, A and
C, suggests that eye velocity memory is not properly
integrating eye acceleration commands.
|
A final experiment further illustrates a number of these points. Figure
17, A and B, show
data for two monkeys. Pursuit target velocity was increased twice,
first from 0 to 15°/s and then from 15 to 30°/s, while
t was held constant for the duration of target motion.
Neither velocity step was accompanied by a position step. When
t was 4 ms (bold traces), both monkeys showed brisk eye acceleration in response to both the first and second 15°/s step of
target velocity. When
t was 60 ms in Fig. 16A
and 96 ms in Fig. 16B (fine traces), the initiation of
pursuit was delayed and showed clear deficits in eye acceleration.
However, eye velocity neared or reached target velocity, implying that
the apparent motion seen during the first step leads to a deficit in
visuo-motor drive without a deficit in eye velocity memory. Because
maintained eye velocity was close to target velocity, the second step
of target velocity, to 30°/s, provided another 15°/s step of
apparent image velocity, with the same
t and retinal
x as the first. Both monkeys showed little eye
acceleration in response to this second step of target velocity. If one
accepts that visuo-motor drive depends on the retinal rather than
absolute
x, then visuo-motor drive is expected to be
similar for the first and second step of target velocity. That the
observed acceleration is very weak after the second step argues that
1) eye velocity memory is not operating normally and/or
2) the visuo-motor commands for eye acceleration are being
gated. Additionally, this experiment further illustrates that the
effect of a given
t on pursuit maintenance depends on
target velocity.
|
Taken together, Figs. 13-17 strongly argue two points. First, maintenance deficits result primarily from a failure of eye velocity memory. Maintenance deficits persist under conditions where visuo-motor drive ought to be sufficient to accelerate the eye toward target velocity. Maintenance deficits can be produced even after eye velocity has reached target velocity, when no further eye acceleration is needed. We discuss below the likelihood that this failure of eye velocity memory is due to partial engagement of pursuit. A secondary contribution to maintenance deficits may arise if partial engagement gates visuo-motor drive, although our data do little to address this possibility. Second, the conditions that produce deficits in the maintenance of pursuit are not tied solely to the retinal image motion in retinal coordinates. The impact of apparent retinal image motion depends on the absolute velocity of the target and/or eye.
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DISCUSSION |
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Pursuit of step-ramp targets is generally described as having
separate initiation and maintenance phases. While apparent motion does
produce deficits in both pursuit initiation and maintenance, a full
account of the deficits we have observed requires a more mechanistic
description of pursuit. Behavioral (Morris and Lisberger 1987; Robinson 1971
; Young et al.
1968
), lesion (Dursteler and Wurtz 1988
;
Dursteler et al. 1987
; Newsome et al.
1985
), and modeling (Goldreich et al. 1992
;
Krauzlis and Lisberger 1994
; Ringach
1995
) studies argue that pursuit eye velocity is created by two
mechanisms. The first is visuo-motor drive, which converts retinal
image motion into commands for eye acceleration. The second is eye
velocity memory, which integrates the eye acceleration commands into
commands for eye velocity, and maintains those eye velocity commands
until subsequent visual inputs provoke renewed eye acceleration, or until pursuit is disengaged. Each of these mechanisms contributes to
both the initiation and maintenance of pursuit. The role of visuo-motor
drive is minimized (although not eliminated) during maintained pursuit
of constant velocity targets, but this would not be true for the
majority of natural pursuit targets. In addition, several lines of
evidence reviewed in the INTRODUCTION have suggested that
the gain of visuo-motor drive and eye velocity memory are under on-line
control by a mechanism governing pursuit engagement. Both visuo-motor
drive and eye velocity memory may operate at full gain only when
pursuit is maximally engaged. The level of engagement may depend on
"cognitive" factors such as motivation and expectation, sensory
factors such as the speed and direction of the target, and, we will
argue, the quality of the visual motion. In the first part of the
DISCUSSION, we will outline how our results fit with this
more mechanistic view of the organization of the pursuit system.
Separable deficits in visuo-motor drive and eye velocity memory
We have reported deficits in the latency and magnitude of initial pursuit eye acceleration that depended on retinal parameters such as the spatial separation of flashes on the retina and retinal eccentricity, and were independent of extra-retinal parameters such as eye velocity, target velocity, and the prior level of engagement of the pursuit system. We conclude that the deficits we have recorded at the initiation of pursuit are due to a failure of visuo-motor drive, presumably subsequent to the failure of apparent motion stimuli to evoke normal responses in the sensory end of the pathways that convert image motion into eye acceleration.
In contrast, the deficits we measured in pursuit maintenance cannot be
attributed simply to a failure of visuo-motor drive and instead appear
to result from a failure of eye velocity memory. A failure of
visuo-motor drive alone is insufficient to explain the data in Figs.
13-17. We suggest that the gain of eye velocity memory is influenced
by the state of engagement of the pursuit system and that maintenance
deficits result from a failure of highly degraded motion signals to
fully engage pursuit. The idea that pursuit engagement may influence
the gain of eye velocity memory has been suggested before, by
Robinson et al. (1986) and Krauzlis and Lisberger
(1994)
.
Origin of deficits in visuo-motor drive
Cortical area MT is known to be a key part of the visuo-motor
pathway driving eye acceleration, and there are a number of parallels
between the factors influencing deficits in visuo-motor drive and those
influencing the responses of cells in MT. These parallels provide some
support for the obvious interpretation that deficits in visuo-motor
drive result from a failure of the relevant apparent motion stimuli to
evoke normal responses in MT. First, deficits in visuo-motor drive were
tied to the retinal x rather than the absolute or spatial
x. Current data imply the same retinal coordinate frame
for neurons in MT. Second, visuo-motor drive during the initiation of
pursuit was able to withstand larger values of
x when the
target started more eccentrically. Cells in area MT with more
eccentric, and therefore larger, receptive fields are also able to
withstand larger values of
x before losing directionality
(Mikami et al. 1986
). Third, as described below, there
is general agreement between the maximum
t and
x that produce normal initiation of pursuit and the
maximum
t and
x that evoke strongly
directional responses in area MT. There is no such agreement for
primary visual cortex. Thus although the first parallel drawn above
clearly applies to V1, and the second likely does, the third does not.
To allow comparison of our data with neural responses recorded in
previous studies, we defined the spatial and temporal limits on pursuit
as the maximum values of x and
t that
produced pursuit initiation within 90% of normal (Fig. 8). The spatial
limit on pursuit varied among monkeys from 0.2 to 0.5° for targets
that appeared between 1.1 and 3.5° eccentric. For neural responses, we defined strong direction selectivity as a directional index >0.8.
Extrapolation along the curve used in Fig. 5 of Mikami et al.
(1986)
to fit their neural recording data suggests that MT neurons have a spatial limit of 0.55° at an eccentricity of 2°. In
contrast, the same figure shows that the spatial limit for V1 cells is
only 0.1° at an eccentricity of 2°. These comparisons imply that
pursuit initiation is dependent on strongly directional responses in
area MT but not on strongly directional responses in V1. Because both
neural and pursuit responses degrade quickly once the spatial limits
are exceeded, the qualitative conclusions drawn in this paragraph do
not depend strongly on the precise criteria chosen to define the
spatial limits.
Comparison of the effect of t on pursuit initiation and
on responses in MT is more difficult. Figure 6 of Mikami et al.
(1986)
implies that neurons in MT maintain strong direction
selectivity for values of
t up to 90 ms. The latency to
initiate pursuit was typically <90 ms, and the maximum
t
for normal pursuit initiation was of necessity less than this, falling
between 32 and 64 ms. Measurements of the effect of
t on
initial eye acceleration afford a better opportunity for comparison but
were difficult to make at the low velocities required to remain below
the spatial limit for normal pursuit initiation. The only experiment in
which we were able to make these measurements is shown in Fig. 9 and
indicates that the temporal limit on normal acceleration was between 64 and 80 ms, in rough agreement with the temporal limits of responses of
MT neurons.
Despite the agreement between the temporal and spatial limits for MT
and for pursuit, a number of factors make it risky to compare our
pursuit data with the available physiological data. 1)
Mikami et al. (1986) recorded from cells with receptive
fields more eccentric than our pursuit stimuli, requiring estimates
made by extrapolation of linear fits. 2) Mikami et
al. (1986)
analyzed mean firing rate over the full 1,000-ms
duration of their stimulus while the initiation of pursuit would be
driven by approximately the first 100 ms of the response. 3)
Mikami et al. (1986)
quantified responses in terms of
the directionality of the responses. Their analysis was entirely
appropriate given the issues they considered, but does not directly
address the question of how an estimate of target speed extracted from
the population code in MT would change with
x and
t. To better compare the changes induced in MT responses
and pursuit initiation, one would wish to pay particular attention to
the initial 100 ms of the neural responses, and to observe the
magnitude and time course of a reconstruction of target speed from the
population response in MT.
Such an approach is also needed to understand the presence of the different deficit types we observed in the visuo-motor drive for pursuit. Deficits in acceleration latency could conceivably result either from changes in the latency of MT responses, or from decreases in firing rates. Deficits in the magnitude of eye acceleration could result either from decreases in firing rate across the population of MT neurons, or from shifts in the population vector. Any of the deficits could be related either to decreases in the responses of neurons that prefer motion in the direction of target motion, or to increases in the responses of neurons with null directions that correspond to the direction of target motion.
Interestingly, the seemingly paradoxical facilitation of eye
acceleration can be explained by a property of motion sensitive cells
described by Mikami et al. (1986): cells tuned for lower speeds lose their directional selectivity at smaller values of
x. This was true both for MT and V1. If we consider a
population representation of speed within MT or V1, at a given target
speed some values of
x will suppress only the responses
of cells with slower preferred speeds. This will effectively shift the
peak of the population code to a speed higher than the veridical speed. If the population code is converted to commands for eye acceleration by
a neural computation that depends on which cells are firing most, then
this shift in the population code would be construed as an increase in
image speed.
Origin of deficits in eye velocity memory
Our interpretation of the deficits in the maintenance of pursuit
is that pursuit is incompletely engaged when visual motion is
insufficiently convincing, and that eye velocity memory does not
therefore operate at full gain. Previous observations of deficits in
the maintenance of pursuit in other contexts have ascribed such
deficits to incomplete engagement, poor velocity memory, or both. These
observations include 1) a monkey who showed weak initiation
of pursuit and poor tracking of upward target motion with normal upward
visual motion processing (Grasse and Lisberger 1992);
2) two monkeys with early-onset artificially induced
strabismus who had weak initiation and maintenance of pursuit for
temporalward target motion, normal responses to temporalward image
motion presented during nasalward pursuit, and normal direction
selectivity and velocity tuning in visual area MT (Kiorpes et
al. 1996
); and 3) monkeys with unilateral lesions of
the medial superior temporal area (visual area MST)
(Dursteler and Wurtz 1988
), the frontal pursuit area
(Keating 1991
; Lynch 1987
; MacAvoy
et al. 1991
), or the dorsolateral pontine nucleus (May
et al. 1988
). Our data extend these results by suggesting that
pursuit engagement and the resulting recruitment of eye velocity memory
are gated by visual motion and are sensitive to the quality of that motion.
Deficits in the maintenance of pursuit did not depend solely on the
retinal properties of the moving image but were influenced by factors
such as absolute target or eye velocity. We see two possible
interpretations of this finding. 1) Engagement and the resulting gating of eye velocity memory may be influenced by
extra-retinal signals related to eye velocity or absolute target
velocity. Such a mechanism might ensure that large values of
t were not tolerated at high target velocities, perhaps
as they imply a large spatial
x. That the engagement of
pursuit should involve extra-retinal parameters is not necessarily
surprising. To detect a cessation of target motion (which typically
results in the disengagement of pursuit), retinal image velocity would
have to be compared with eye velocity. 2) The degree of
engagement of pursuit may be dependent only on retinal features of the
stimulus, but the gain of eye velocity memory may be nonlinear. When
incompletely engaged, eye velocity memory may be more prone to
"leak" at higher velocities. Effects of incomplete engagement on
pursuit maintenance would then be small at low eye velocities, but
would become noticeable at high velocities. In fact, eye velocity
memory does appear to be more prone to leaking at higher velocities
even under nearly optimal conditions of target motion. For some monkeys
small "maintenance deficits" were observed for higher target
velocities even when
t was 4 ms (Figs. 13-16). However,
t's that produced large maintenance deficits at high
apparent target velocities often produced perfectly normal, or even
supra-normal maintenance at lower target velocities (Figs.
15B and 16B). Thus, for this explanation to
succeed, the gain of eye velocity memory would have to be very nonlinear.
In addition to the impairment of eye velocity memory, there are two
other classes of explanations for deficits in pursuit maintenance that
we consider unlikely. 1) The prevalence of saccades during
deficient pursuit maintenance disturbs pursuit, preventing normal
maintenance. As discussed above, saccades potentiate subsequent smooth
eye velocity, presumably by enhancing incomplete engagement (Lisberger 1998), and should tend to ameliorate deficits
in the maintenance of pursuit. In addition, severe deficits in
initiation, accompanied by frequent saccades, were often followed by
normal maintenance. Further, an explanation based on interference by saccades would also have difficulty accounting for the data in Figs. 15
and 17. Thus saccades appear to be a consequence rather than a cause of
the deficits. 2) Target image eccentricity is different
during the maintenance and initiation of normal pursuit. A given
spatial flash separation produced larger deficits in visuo-motor drive
for more foveal targets. As our pursuit targets started eccentrically,
but were foveated during the maintenance of pursuit, this effect might
have quelched visuo-motor drive as eye velocity neared target velocity.
In practice, however, eye position lagged target position by a couple
of degrees during deficient maintenance of pursuit, so that the actual
retinal eccentricities of targets that failed to evoked eye
acceleration during pursuit maintenance were similar to those of
targets that evoked convincing eye acceleration at the initiation of
pursuit (see Fig. 13B). Furthermore, maintenance deficits
could be observed when a step of apparent target velocity was presented
in the absence of an initial position step (data not shown). Under such
conditions the target image becomes progressively more eccentric during
the initiation of pursuit. Last, this explanation cannot account for
the data in Figs. 15 or 17, nor can it explain why maintenance deficits
were worse at higher target velocities, as in Fig. 16.
A failure of processing in any number of cortical areas could produce
the eye velocity memory deficits we observed. The presence of eye
velocity memory deficits following lesions of visual area MST, which is
thought to be the next level of motion processing for pursuit eye
movements after area MT, suggests that the deficits we have observed
may result because the relevant apparent motion stimuli fail to evoke
normal responses in MST. Due to the presence of extra-retinal signals,
MST has previously been suggested as a site mediating corollary
feedback of the type required for eye velocity memory (Newsome
et al. 1988). Alternately, it is also possible that maintenance
deficits result when weakened inputs from MT fail to properly excite
neurons in the frontal pursuit area or the dorsolateral pontine
nucleus, lesions of which also lead to maintenance deficits.
Comparison with previous studies
Previous studies of pursuit of apparent motion in humans
have found seemingly normal pursuit for values of t up to
150 ms, which produced large initiation deficits in our monkeys
(Fetter and Buettner 1990
; Morgan and Turnbull
1978
; Schor et al. 1984
; Van der Steen et
al. 1983
). However, these studies employed either continuously
moving or low-frequency periodic stimuli and examined pursuit gain
during steady-state tracking. Under these conditions, deficits in the
latency and magnitude of visuo-motor drive are expected to have minimal
impact. Deficient pursuit will be observed only when visuo-motor drive
becomes very weak, or when eye velocity memory suffers. The studies
that produced the largest tolerable
t's (Morgan
and Turnbull 1978
, 150 ms; Van der Steen et al.
1983
, at least 100 ms) did so at relatively low apparent target
velocities (2 and 7.85°/s, respectively). These values of
t were at the limit of what produced normal pursuit
maintenance in our monkeys at these velocities. The predictable nature
of the targets used in these studies may also have contributed to the
relatively normal performance at large values of
t.
Finally, our preliminary data (unpublished observations) do not support
the possibility that human visual processing is much more resistant to
apparent motion than that of monkeys.
Comparison with perception of apparent motion
Comparison of pursuit and perception for apparent motion stimuli
offers an opportunity to address the open question of whether the
motion signals driving pursuit are identical to those that mediate
perception. Baker and Braddick (1985) used random dot displays to probe the spatial limits of perception involving the short-range apparent motion process. They found that the maximum
x increased with eccentricity and was approximately 0.2 and 1.3° for eccentricities of 1 and 8°. In reasonable agreement,
the maximum
x for normal pursuit initiation was
approximately 0.2 and 0.5° for starting eccentricities of 0.5 and
7° (Fig. 10). Comparison of the maximum
t for pursuit
initiation and for perception of short range apparent motion is more
difficult, as pursuit necessarily suffers at any
t that
approaches the latency of pursuit. Nevertheless, we note that the
maximum
t for normal initial eye acceleration was 64-80
ms, in good agreement with the maximum
t for perception of 40-80 ms.
Studies of short-range apparent motion used random dot stimuli,
and psychophysical performance was measured as the ability to discern
the direction of motion. A better approximation to our discrete target
is the bar-shaped target used by Newsome et al. (1986)
in their evaluation of the perceptual limits of apparent motion. Unlike
random dot stimuli, however, a single bar moves unambiguously in a
given direction even at very large values of
x.
Newsome et al. (1986)
therefore asked subjects to give
their subjective impression of the smoothness of motion. The five
subjects reported that smooth motion was absent when
x
exceeded 0.6 to 1.5°, for target velocities of 10-40°/s at an
eccentricity of 5°. In reasonable agreement, the maximum
x for pursuit was 0.5° for a starting eccentricity
of 7°.
The broad agreement between the parameters of apparent motion that support pursuit and perception at least suggests common inputs to the two systems. However, there are some serious caveats to this conclusion. First, pursuit in humans may have somewhat different spatial and temporal limits than pursuit in monkeys. Second, our stimuli were different from those previously used to study perception. Last, the metrics used to study perception (subjective quality of motion, discrimination of direction) are not obviously parallel to the metric we used for pursuit (latency and magnitude of eye acceleration during pursuit initiation). A more detailed comparison necessarily awaits new experiments designed to study pursuit and perception in parallel.
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ACKNOWLEDGMENTS |
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We acknowledge the efforts of K. Logan, who completed a preliminary version of these experiments using now-outdated technology but obtained many of the same results reported here. We thank Dr. J. Anthony Movshon, the members of the Lisberger laboratory, and an anonymous reviewer for insightful comments on the manuscript. S. G. Lisberger is an Investigator of the Howard Hughes Medical Institute.
This research was supported by National Eye Institute Grant EY-03878. M. M. Churchland was supported by a pre-doctoral fellowship from the Department of Defense.
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FOOTNOTES |
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Address for reprint requests: M. M. Churchland, Dept. of Physiology, 513 Parnassus Ave., Rm. 762-S, University of California, Box 0444, San Francisco, CA 94143-0444 (E-mail: mchurchl{at}phy.ucsf.edu).
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 5 November 1999; accepted in final form 24 March 2000.
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NOTE ADDED IN PROOF |
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A revised literature search revealed two additional studies of the
perception of apparent motion that may be relevant to the interpretation of our results. McKee (1981) found that the accuracy of
subjects' estimation of apparent target speed suffered at spatial separations >0.25°, in agreement with the 0.2-0.5° limit we
report for pursuit initiation. Castet (1995)
found that apparent speed actually increased for larger flash separations. This illusion occurred
only for target speeds <6°/s, but may nonetheless be related to the
increases we observed in pursuit eye acceleration.
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REFERENCES |
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