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0042-6989/$ - see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.visres.2006.02.025
Perception of visual motion coherence by rats and mice
R.M. Douglas
a,b,¤
, A. Neve
b
, J.P. Quittenbaum
b
, N.M. Alam
a
, G.T. Prusky
b
a Department of Ophthalmology and Visual Sciences, University of British Columbia, 2550 Willow Street, Vancouver, BC, Canada V5Z 3N9b Canadian Centre for Behavioural Neuroscience, The University of Lethbridge, 4401 University Drive, Lethbridge, Alta., Canada T1K 3M4 Received 13 November 2004; received in revised form 17 January 2006
Abstract
The coherence thresholds to discriminate the direction of motion in random-dot kinematograms were measured in rats and mice.
Per-formance was best in the rats when dot displacement from frame-to-frame was about 2 degrees, and frame duration was less than 100 ms.
Mice had coherence thresholds similar to those of rats when tested at the same step size and frame duration. Although the lowest
thresh-olds in the rats and mice occasionally reached human levels, average rodent values (»25%) were 2–3 times higher than those of humans.
These data indicate that the rodent and primate visual systems are similar in that both have local motion detectors and a system for
extracting global motion from a noisy signal.
© 2006 Elsevier Ltd. All rights reserved.
Keywords: Extrastriate cortex; MT; Random dot; Kinematograms; Visual water task; Psychophysics
1. Introduction
The detection and e
Vective use of visual motion is
widespread in the animal kingdom. Experimental
investi-gations of the neural mechanisms of motion perception
have been conducted in species as diverse as
Xies, pigeons,
and monkeys (
Cli
Vord & Ibbotson, 2002
), and simple
neural circuits capable of detecting local motion of single
elements have been studied in the
Xy (
Reichardt, 1961
)
and rabbit retinas (
Barlow & Levick, 1965; Fried, Munch,
& Werblin, 2002
). In recent years, it has become common
to use dynamically moving random-dot patterns (or
kinematograms) to assess visual motion, as they enable
the study of motion perception in the absence of
posi-tional or form cues (
Nakayama & Tyler, 1981
).
Percep-tual mechanisms that can detect common motion of
many elements have been identi
Wed in humans and other
primates (
Braddick, 1974; Morgan & Ward, 1980;
Wil-liams & Sekuler, 1984
) and localized to extrastriate
cor-tex (
Baker, Hess, & Zihl, 1991; Newsome & Paré, 1988
). It
is, however, an open question whether primates have
unique cortical capabilities, or whether such a functional
organization is a fundamental property of mammalian
visual systems. If extrastriate analysis of global visual
motion is common to mammals, this would have
implica-tions for its evolution and ecological utility. In addition,
studying motion perception in laboratory rodents would
facilitate experiments into the cellular and molecular
substrates of visual motion processing. To this point,
however, no systematic study of motion perception has
been conducted in rodents, largely because it has been too
di
Ycult to test their visual motion thresholds
psycho-physically. Over the past several years, we have used the
Visual Water Task (
Prusky, West, & Douglas, 2000
) to
quantify acuity and contrast sensitivity thresholds in rats
and mice (
McGill, Douglas, Lund, & Prusky, 2004;
Pru-sky et al., 2000; PruPru-sky & Douglas, 2004
), and we report
here that this task can be adapted to measure their visual
motion thresholds.
In order to determine whether rodents have visual
motion capabilities and anatomical substrates comparable
to primates, we compared the dot motion coherence
thresh-olds of rats with those of humans.
* Corresponding author. Fax: +1 604 876 6553.
2. Methods
2.1. Subjects
Six adult female Long–Evans rats and six adult C57BL/6 mice were used in the experiments. The animals were between 90 and 150 days of age at the start of training, and testing continued over the subsequent 4–6 months. All procedures were authorized by the University of Lethbridge Animal Care Committee, which approves procedures that are conducted in accordance with the standards of the Canadian Council on Animal Care.
To facilitate comparison with human motion vision, three human observers viewed the same stimuli from the same distance. They used pushbuttons to start each trial and to record their decisions about which side had the positive stimulus. Human testing was conducted in accor-dance with the guidelines of the University of Lethbridge Human Subjects Research Committee.
2.2. Apparatus
The Visual Water Task (Prusky et al., 2000) uses a trapezoidal tank (120 cm L £ 80 cm W £ 26 cm W £ 55 cm H) with two ViewSonic EF70, 17⬙ computer monitors facing into one end (Fig. 1). A midline divider (46 cm) extends into the pool from between the monitors, each of which subtended about 30° degrees when viewed from the end of the divider. The tank was Wlled with water, and an escape platform was placed just below the surface directly under one of the monitors. The platform was always located below the positive (+; reinforced) stimulus. Visual stimuli were generated by, and the experiments were controlled with custom software.
2.3. Stimuli
Kinematograms were computed separately for each monitor before every trial, and were then played continuously until the end of the trial. A random-dot kinematogram consisted of 24 frames or images. The diame-ter of the round dots was 1.9° for the rats, and 2.9° for the mice as studies from our laboratory (e.g., Prusky et al., 2000) have shown that the grating acuities of Long–Evans rats and C57BL/6 mice are 1.0 and 0.55 cycles per degree (c/d), respectively. The total area of the dots was about 20% of the screen area, and this corresponded to there being 62 (rats) or 28 (mice) dots on each image frame. The dots had a luminance of 96 cd/m2 and the background was 1.1 cd/m2.
Each dot could move from one frame to the next, or disappear. The step size, or amplitude of the displacements from fame to frame, was the same for all dots, with only the direction of movement varied between frames. Motion noise was introduced by having a percentage of the dots move in random directions (Fig. 2) with the additional constraint that there was no net movement. The remainder of the dots all moved in one, coherent direction. Dot displacements of 0.24°, 0.47°, 0.94°, 1.88°, 3.77°, 5.65°, and 7.54° were used in diVerent blocks of trials.
After moving for 2 or 12 frames (lifetime) each dot was randomly repo-sitioned, thus ensuring a constant number of dots on screen. A constant percent of dots died and were reborn elsewhere on each frame, and motion wrapped from the 24th to the 1st frame so that the kinematogram could be played continuously. Longer lifetimes were not possible with a looping requirement, and thus dot lifetimes of 2 and 12 frames limited the maxi-mum eVective coherence to 50 and 92%, respectively (Bischof, Reid, Wylie, & Spetch, 1999).
Frame duration set the stimulus onset asynchrony (SOA) for the dots to appear on two successive frames, and frame duration was a multiple of the video screen refresh rate. In the experiments with rats, 1, 2, 4, 8, 13, 19, and 26 screen refreshes were employed. As the monitors had an 85 Hz ver-tical refresh rate, these values translate to frame durations of 12, 24, 48, 94, 153, 224, and 306 ms.
2.4. Behavioral testing
The animals were trained to associate swimming to the positive stimu-lus, regardless of its left/right location, with escape from water. The initial training consisted of training the rat or mouse to distinguish between 100 and 0% coherence. Rats learned to grasp the end of the divider and inspect both screens before making a choice; mice tended to slow down at the bar-rier and swim back and forth before making a choice. After an animal had Wnished a trial, it was returned to a holding box to dry and groom while the other 5 animals completed the same trial. Sessions consisted of 15–20 trials per animal. The training kinematograms had a step size of 0.471°, a frame duration of 12 ms, and a lifetime of 10 frames.
Once the rats reached at least 80% accuracy over a block of 10 trials, we changed the task to identifying the direction of motion. This had the advantage that the kinematograms on the two monitors were identical in coherence, step size, frame duration, and lifetime, and only diVered in
Fig. 1. Schematic top-view of the Visual Water Task. The task uses a trape-zoidal pool with two computer monitors at one end displaying either a pos-itive (+, reinforced) or negative (¡, non-reinforced) stimulus. An escape platform is placed below the monitor showing the positive stimulus and the left/right position of the pair is randomized. The platform surface is just below the water level and is not visible to the animal. Animals are released at one end and they swim to the end of a divider where they inspect the two monitors before choosing one arm of the maze to swim into.
Submerged Platform Choice Plane Video Monitors Start Point
+
–
WaterFig. 2. Schematic diagram of stimulus attributes. Motion coherence dis-plays consisted of multiple dots that could move in any direction across frames. After moving on 2 or 12 successive frames, the dot disappeared and a new dot was created at another random location on the screen (dashed circles). At 0% coherence, all dots moved in random directions with the average being zero. At maximal coherence all moving dots moved coherently in one direction.
100% Coherence 0% Coherence
direction of the coherent motion. For the rats, the discrimination was between leftward (negative) and rightward (positive) coherent motion. For the mice, the task required a discrimination between horizontal (positive) and vertical (negative) motion.
Coherence thresholds were then established by reducing the percent of dots moving coherently for blocks of ten trials. A preliminary threshold was established when performance fell below seven correct in a block of 10 trials. The threshold was assessed several times or until a reliable pattern of performance was generated. Generally, three or four estimates were so obtained.
3. Results
3.1. Behavior and training
All the rats and mice were eventually able to
discrimi-nate the direction of motion in random-dot
kinemato-grams, and did so even when coherence was 25% or less.
The directional discrimination, however, was a di
Ycult test
for the animals to learn. Initially we tried testing the rats
with a dot lifetime of 2 frames, but none of the rats could
learn to make the discrimination. This may have been
because 50% was the maximum coherence possible with
single frame motion. When dot lifetime was increased to 12
frames we could start testing at 92%, and the animals had
fewer problems learning, taking 86 trials on average to
learn the new discrimination (range 30–200 trials). Once the
rats learned the task, performance was close to perfect at
high coherencies, and then declined as the percentage was
decreased (
Fig. 3
). Testing was discontinued once
perfor-mance dropped below 70% because animals rapidly become
confused when they made many errors. Although most of
the experiments used dot lifetimes of 12 frames, we tried
reducing dot lifetime later, after the rats had had extensive
experience with task. On the second attempt, all of the rats
were able to discriminate the direction of motion with
two-frame lifetimes, but there was no signi
Wcant diVerence in
coherence thresholds for 2-frame (31.0 § 2.85) and 12-frame
motion (25.21 § 4.59) kinematograms (t D 1.0, df D 5,
p D 0.36).
We attempted to train the mice in the same way as the
rats, but they could not learn the initial discrimination of
maximal coherent motion versus one that had no coherence
(i.e., 0%). After this initial failure, we tried training the mice
on an alternative task in which the requirement to
discrimi-nate between horizontal motion (+) and vertical motion
(¡). This they did learn in an average of 360 trials (range
262–520). Like the rats, once the mice had learned the task,
they could perform at a high level.
Fig. 4
A shows one
mouse making only occasional errors over 544 trials as
coherence was lowered progressively six times.
Perfor-mance improved over the experiment: Initially the mouse
started making errors at dot coherencies of 60%, but on
subsequent runs the mouse made fewer errors and the
threshold stabilized at about 25%. On average 449 (§4.1)
Fig. 3. Performance of the rats for kinematograms with a dotdisplace-ments of 3.8° per 47 ms frame. Testing started at 92% coherence, and that was reduced until performance dropped below 70%. This was repeated several times, and an average of 239 trials was needed to establish the threshold for each animal. Each point is the mean percent correct for the 6 animals, and the error bars are for one standard error.
0 10 20 30 40 50 60 70 80 90 100 40 50 60 70 80 90 100
% Coherence
% Correct
Fig. 4. (A) Example of coherence threshold testing in one mouse. Initially the mouse made errors almost as soon as the coherence was reduced, but with further testing, performance stayed near 100% until the coherence had dropped to below 30%. (B) The average performance of the 6 mice are plotted as a function of coherence. The error bars show one standard error above and below the means.
0 100 200 300 400 500 0 10 20 30 40 50 60 70 80 90 100 40 50 60 70 80 90 100
% Correct
0 10 20 30 40 50 60 70 80 90 100 40 50 60 70 80 90 100% Coherence ( )
% Correct
% Coherence
Trial
A
B
trials were used to measure one coherence threshold. The
corresponding threshold in rats was obtained more rapidly
(239 § 9.9 trials) but with a shallower frequency-of-seeing
curve (
Fig. 3
) than that for the mice (
Fig. 4
B).
3.2. Dot motion
In the
Wrst quantitative experiment with the rats, dot
step size was varied and coherence thresholds were lowest
between 1° and 4° (
Fig. 5
A). At 26.9%, the rat thresholds
were 3.9 times that of the average of 6.8% for the humans
over the same range. The coherence thresholds were higher
for both rats and humans at larger step sizes, and at 7.54°
two rats were unable to discriminate at the maximum
avail-able coherence of 92.5%. Smaller step sizes were also
chal-lenging for the rats, whereas humans had little trouble with
the same sizes, or even at 0.047° at which their threshold
was 10.4% (not shown).
The average rat thresholds were higher than the human
thresholds for all frame durations (
Fig. 5
B). The lowest,
22.9%, was 2.2 times higher than the corresponding 24 ms
threshold for the three humans. Rat thresholds became
pro-gressively higher for longer durations, whereas the human
thresholds varied little. Four of the six rats were unable to
discriminate when the frame duration was 306 ms.
Changing either the size of the jumps a dot makes, or the
time between the jumps can vary the speed of dot motion.
The data from
Figs. 5
A and B are replotted in
Fig. 5
C as a
function of velocity. The two speeds from the two
experi-ments cover the same velocity range, and the coherence
thresholds are similar and low for the 20° s
¡1to 80° s
¡1range, but diverge at each extreme. At higher velocities, a
lower threshold was present when the increase in speed was
due to shorter frame durations than it was with larger step
sizes. Conversely at low velocities, small step sizes were
more discernible than long frame durations.
4. Discussion
All the rats and mice learned to discriminate the
direc-tion of random dot kinematograms. The lowest coherence
thresholds were about 20–25%, which was higher than
that of humans, but comparable to those in cats (
Rudolph
& Pasternak, 1996
). The experience in our laboratory is
that mice are harder to train and test, and do not perform
as well as rats in visual tasks. They have a lower acuity
and contrast sensitivities, and we expected that they
would not do as well with motion coherence. The fact they
did as well as the rats may have been due to the use of an
“easier” task. Discriminating vertical from horizontal
motion may be an easier task than leftward versus
right-ward motion. This could be a cognitive problem with the
directional signal having a much lower saliency than the
orientation signal. Alternatively, the local motion
detec-tors may be oriented, but not directional selective, and
this would make the leftward versus rightward
discrimina-tion impossible.
Fig. 5. EVects of varying dot step size and delay on coherence thresholds. (A) Rat and human motion coherence thresholds for displays with dots moving diVerent distances per frame. Each Wlled circle indicates the aver-age value for the six rats, and open squares depict the averaver-age for 3 human observers. Two rats were unable to discriminate above 70% accuracy at the largest step size. Frame duration was 48 ms. (B) Motion coherence thresholds for displays with diVerent frame durations (and thus diVerent stimulus onset asynchronies). Four rats were unable to discriminate at better than 70% accuracy for the largest SOA. Dot displacement was 3.78°. (C) Changing either dot displacement or frame duration alters the speed of the dots. The data from (A and B) are plotted here as a function of velocity. The two manipulations were not equivalent as diVerent thresh-olds were obtained for the same speed. The error bars show one standard error around each mean.
0.2 0.4 0.6 1.0 2.0 4.0 6.0 8.0 0 10 20 30 40 50 60 70 80 90 100 Humans Rats Coherence Threshold (%) Frame Duration (ms) Coherence Threshold (%) Varying Frame Duration Varying Displacement Size 4 6 8 10 20 40 60 100 200 400 0 10 20 30 40 50 60 70 80 90 100
Velocity (degrees/second)
Coherence Threshold (%) 10 20 40 60 100 200 400 0 10 20 30 40 50 60 70 80 90 100 Rats HumansDisplacement per Frame (degrees)
A
B
4.1. Global motion
The present results clearly demonstrate that rodents
have a global motion system. The tasks can not be solved
by tracking a single dot. Rather, information about many
dots must be integrated over a larger part of the visual
Weld.
In primates, the biological basis of the perception of motion
coherence has been thought to rely on the area around MT,
as lesions there impair the extraction of a motion signal
from a noisy display (
Baker et al., 1991; Newsome & Paré,
1988
). Similarly, area PMLS in the cat appears to be
spe-cialized for motion processing, and lesions of PMLS impair
motion coherence perception (
Huxlin & Pasternak, 2004;
Rudolph & Pasternak, 1996
). At present, there is no
electro-physiological evidence for a homologous extrastriate area
in rat, but induction of c-fos immunoreactivity in the area
after viewing moving stimuli has suggested that rat
antero-lateral (AL) visual area is the equivalent of primate MT
and cat PMLS (
Montero & Jian, 1995
).
In the present study, human thresholds were consistently
lower than the rat thresholds for the same stimuli, usually
by a factor of 2–4, and sometimes by much more. This
dis-crepancy is probably a di
Verence in their visual capabilities
and not due to the animals giving up when the task became
more di
Ycult. Performance was often close to 100% until
the coherence approached the eventual thresholds, and the
Wnal threshold estimates were consistent across animals.
Interestingly,
Bischof et al. (1999)
report that pigeons also
have motion coherence thresholds much higher than
humans. Coherence thresholds of 10–20% in guppy
Wsh
have been reported (
Anstis, Hutahajan, & Cavanagh, 1998
)
so it may be that all vertebrate visual systems have some
ability to extract motion in the presence of noise. This
func-tion may be partly localized in rat to AL and in cat to LS,
but the homology to primate MT is not exact, as these areas
do not appear to be as pro
Wcient as MT is in the primate.
The higher coherence thresholds in the rodents
com-pared to primates could be due to poorer temporal
integra-tion. Each dot appeared on 12 successive frames, and thus
there were multiple displacement and stimulus onset
asyn-chronacy (SOA) combinations that could, in principle, have
been used to compute a motion signal. Human observers
integrate information over multiple frames (
Burr &
Sant-oro, 2001; Watamaniuk & Sekuler, 1992
) but the absence of
a signiWcant diVerence between the coherence thresholds
when using 2- and 12-frame kinematograms suggests that
temporal integration was poor in the rat. Reduced temporal
integration, relative to that for humans, has also been
reported in pigeons (
Bischof et al., 1999
).
4.2. Local motion
The variations in coherence thresholds at di
Verent dot
displacements and SOAs re
Xect the properties of the
mech-anisms that detect the motion of the individual dots. For
both humans and rats, the thresholds increased for
dis-placements larger than 4°, suggesting a maximum
displace-ment (D
max) of about 8° (
Fig. 5
A). This is a much larger
D
maxthan the 0.25°
Wrst found by
Braddick (1974)
, and is
most likely due to the much large dot sizes (
Morgan, 1992
),
long lifetimes (
Todd & Norman, 1995
), and large display
areas (
Eagle & Rogers, 1996
) which extended into
periph-ery (
Baker & Braddick, 1985
). Another way to look at the
data is to consider that, for the rats, the large dots are
roughly equivalent to the small dots used in many human
studies. If one scales a typical human D
maxof 0.25° by the
30-fold di
Verence in acuity, one gets an predicted D
maxof
7.5° for rats. These considerations suggest that the rats and
humans have local motion systems that have very similar
properties when working at the same spatial scale.
Frame duration or stimulus onset asynchrony (SOA) is
also critical for obtaining apparent motion, and the rats
had increasing diYculty as SOA increased and were quite
poor beyond 150 ms. Similar limits have been seen in
human studies of random-dot motion using small dots
(
Braddick, 1974
), but the human performance reported
here is quite diVerent as it was good across all SOAs tested.
This may be because the optimal (and presumably
maxi-mal) delay grows with larger dot displacements (
Eagle &
Rogers, 1997
).
5. Conclusions
The limited spatial and temporal ranges for dot
move-ment are consistent with simple local motion detectors
being used in the rodent to detect individual dot motion.
The low thresholds for motion coherence are evidence for a
more global mechanism that combines the output of these
detectors. Although the visual capabilities of rodent are
more limited than in primates, there are advantages of
using rats and mice as a experimental models in uncovering
the fundamental mechanisms underlying the perception of
visual motion. Genetic tools are more readily available in
rodents than in cats or primates, and the Xat cortex in
rodents has advantages for optical imaging of cortical
activity (
Cang, Kalatsky, Lowel, & Stryker, 2005; Ohki,
Chung, Ch’ng, Kara, & Reid, 2005
).
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