Harrison et al. (2013) Eye Movement Targets Are Released from Visual Crowding

Harrison et al. (2013) Eye Movement Targets Are Released from Visual Crowding
The Journal of Neuroscience, February 13, 2013 • 33(7):2927–2933 • 2927
Behavioral/Cognitive
Eye Movement Targets Are Released from Visual Crowding
William J. Harrison,1 Jason B. Mattingley,1,2 and Roger W. Remington1
1
School of Psychology and 2Queensland Brain Institute, The University of Queensland, St Lucia, Queensland 4072, Australia
Our ability to recognize objects in peripheral vision is impaired when other objects are nearby (Bouma, 1970). This phenomenon, known as
crowding, is often linked to interactions in early visual processing that depend primarily on the retinal position of visual stimuli (Pelli, 2008; Pelli
and Tillman, 2008). Here we tested a new account that suggests crowding is influenced by spatial information derived from an extraretinal signal
involved in eye movement preparation. We had human observers execute eye movements to crowded targets and measured their ability to
identifythosetargetsjustbeforetheeyesbegantomove.Beginning!50msbeforeasaccadetowardacrowdedobject,wefoundthatnotonlywas
there a dramatic reduction in the magnitude of crowding, but the spatial area within which crowding occurred was almost halved. These changes
in crowding occurred despite no change in the retinal position of target or flanking stimuli. Contrary to the notion that crowding depends on
retinal signals alone, our findings reveal an important role for eye movement signals. Eye movement preparation effectively enhances object
discrimination in peripheral vision at the goal of the intended saccade. These presaccadic changes may enable enhanced recognition of visual
objects in the periphery during active search of visually cluttered environments.
Introduction
Voluntary eye movements are crucial for efficient sampling of the
visual environment. During fixation, objects at the fovea receive
enhanced processing and are easily recognized, whereas those in
the periphery are more difficult to identify, particularly when
closely adjacent objects surround them, a phenomenon referred
to as visual “crowding” (Bouma, 1970; Pelli and Tillman, 2008).
This effect can be experienced by fixating first on the red cross
and then on the blue cross in Figure 1A. Note that the letter “Y” is
much harder to discern when fixating the red cross than the blue
one, even though it is located an equal distance from fixation in
the two situations.
Crowding has been assumed to reflect obligatory integration
of visual features in early visual areas that represent a region of
space which includes both target and nontarget stimuli (Parkes et
al., 2001). The extent of this region—the “critical distance”—
scales with eccentricity, so that the zone of crowding becomes
progressively larger as target stimuli are moved further into the
periphery. Critical distance is approximated by Bouma’s law as
0.5 !, where ! is the eccentricity of the target (Bouma, 1970; Pelli
and Tillman, 2008). The spatial extent of crowding can be used to
approximate the minimum cortical distance between two objects
necessary for accurate object recognition (Pelli, 2008).
Received Aug. 31, 2012; revised Dec. 11, 2012; accepted Dec. 20, 2012.
Author contributions: W.J.H., J.B.M., and R.W.R. designed research; W.J.H. performed research; W.J.H. analyzed
data; W.J.H., J.B.M., and R.W.R. wrote the paper.
This research was supported by an Australian Research Council (ARC) Discovery Project awarded to R.W.R. and
J.B.M. (DP0666772). J.B.M. was also supported by an ARC Australian Laureate Fellowship (FL110100103). Parts of
these data were presented at the Australasian Experimental Psychology Conference in April, 2012. We thank T.S.A.
Wallis for his assistance with analysis of data for Experiment 2.
The authors declare no competing financial interests.
Correspondence should be addressed to William J. Harrison at his present address: Schepens Eye Research Institute, Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, Harvard Medical School, Boston, MA
02114. E-mail: willjharri@gmail.com.
DOI:10.1523/JNEUROSCI.4172-12.2013
Copyright © 2013 the authors 0270-6474/13/332927-07$15.00/0
Attempts to reduce crowding using spatial cues to indicate the
location of the crowded target have yielded mixed findings, and
only modest improvements in target discriminability at best
(Felisbert et al., 2005; Strasburger, 2005; Scolari et al., 2007;
Yeshurun and Rashal, 2010). Thus, it has been suggested that
crowding imposes a fundamental limit on conscious vision
(Levi, 2008; Whitney and Levi, 2011).
It is well established that responses of visual neurons and perception of uncrowded targets can be modulated by extraretinal
signals generated before an eye movement. For example, Moore
et al. showed that activity related to an eye movement command
in the frontal eye fields (FEF) alters the gain of V4 responses to
stimuli presented at the goal of the intended eye movement
(Moore and Armstrong, 2003; Moore et al., 2003; Moore and
Fallah, 2004). Moreover, Tolias et al. (2001) showed that the
receptive fields of V4 neurons shrink in size and shift toward
the saccade goal just before a saccadic eye movement. Human
psychophysical studies have shown that enhanced identification of uncrowded targets at the goal of a saccade (Remington,
1980) is substantially greater than that arising from visual cues
alone (Deubel, 2008). Critically, these neural and perceptual
effects are evident before the eyes begin to move, before any
change in the retinal location of the target stimulus (Kowler et
al., 1995; Deubel and Schneider, 1996; Moore and Fallah,
2004; Deubel, 2008).
The evidence reviewed here suggests that an extraretinal signal
involved in saccade preparation (Wurtz, 2008) can enhance perception at the goal of an eye movement. Whether similar perceptual improvements before a saccade occur for crowded targets
remains an open question. We therefore tested if visual crowding
is reduced when a crowded stimulus is the target of an intended
saccade.
Materials and Methods
Overview of experiments. In two experiments, we quantified changes in
the magnitude and spatial extent of visual crowding during steady fixa-
2928 • J. Neurosci., February 13, 2013 • 33(7):2927–2933
A
B
C
Figure 1. Demonstrationofvisualcrowdingandmethodusedtotestcrowdingbeforeeyemovements. A, Visual crowding for letter stimuli. In the upper row, the Y in the word “EYES” is virtually
impossible to identify while fixating the red cross. In the lower row, the Y on its own is relatively easy
to identify while fixating the blue cross, even though it is located at the same eccentricity as the Y in
“EYES” above. B, Sequence of displays used to quantify the magnitude of crowding before a saccade.
At the offset of a blue fixation spot observers executed a saccade to the target and then reported the
orientation of the central Gabor. If the fixation spot was red observers maintained fixation and performedthesametaskonthecentralGabor.C,Schematicshowingthetimingoftargetdisplaysrelative
to saccade onset. The saccade commences at time 0, and negative times on the x-axis reflect the
presaccade intervals over which target stimuli were presented. Saccadic latencies were recalculated
continuouslyonline.Theselatencieswereusedtodeterminetarget-saccadeonsetasynchronies,such
that targets were presented with close to equal probability in each of three intervals before the saccade (%149 to %100 ms, %99 to %50 ms, and %49 to 0 ms; Hunt and Cavanagh, 2011). Dimensions of stimuli in B are not to scale.
tion and before a saccade toward a crowded target. Observers’ basic task
was to report the orientation of a peripheral target Gabor surrounded by
four vertically oriented Gabors (Fig. 1B). Blocks in which central fixation
was maintained (“no-saccade” trials) were intermingled with blocks in
Harrison et al. • Eye Movements Release Crowding
which observers executed a saccade to the target placeholder (“saccade”
trials). Target presentation durations were brief (!24 ms) and, in saccade trials, were presented at varying times before the eye movement
(Fig. 1C, Fig. 2B). Critically, because all orientation judgments were
made before the eyes moved, the retinal locations of target and flanking
stimuli were identical for the saccade and no-saccade conditions.
Observers. Five experienced psychophysical observers (one female)
participated in each experiment. Two observers, including one author
(W.J.H.), participated in both experiments. All observers had normal or
corrected-to-normal vision and gave informed consent. The study was
approved by The University of Queensland’s School of Psychology Ethical Review Committee.
Materials. Participants sat with their head in a head and chin rest
positioned 57 cm from a 20 inch Dell CRT monitor (1600 " 1200 pixels,
85 Hz) in Experiment 1 or 61 cm from a 17 inch Samsung CRT monitor
(1280 " 1024 pixels, 85 Hz) in Experiment 2. Stimulus presentation, eye
movement recording, and response collection were programmed using
the Psychophysics Toolbox Version 3 (Brainard, 1997; Pelli, 1997) and
Eyelink Toolbox extensions (Cornelissen et al., 2002) for MATLAB
(MathWorks). Eye movements were recorded at 500 Hz with an EyeLink
1000 (SR Research) infrared eye tracker, calibrated using a 9 point calibration procedure.
Stimuli and procedure. Each trial began with a fixation spot (width #
0.2°) in the center of a uniformly gray display. As shown in Figure 1B, the
target and four flanker positions in Experiment 1 were indicated with
black placeholders (1° " 1°). The target in Experiment 1 was 7.7° to the
right of the fixation spot, and the center-to-center distance between target and flankers was 1.3°. In Experiment 2, only the target position (7°
from central fixation) was indicated with a placeholder, and this placeholder was offset at target onset such that no borders were visible during
target presentations. Target and flanking stimuli were Gabors (width #
1°, 2 cpd, 100% contrast) presented for 23.5 ms. Immediately before
target presentation, patches of white noise randomized with each screen
refresh (85 Hz) were presented at positions corresponding to targets and
flankers. In Experiment 1 only, the same dynamic white noise followed
target and flanker presentation. Randomly from trial to trial, the combined target and flanker configuration was jittered vertically by $1° to
ensure that observers could not preprogram eye movements throughout
each testing session.
A trial began after gaze was detected continuously for 500 ms within a
2° " 2° region centered on the fixation spot. The fixation spot offset after
a variable delay of 750 –1250 ms (randomly drawn from a uniform distribution), cueing the observer either to make a saccade to the target
(blue spot), or to remain fixated (red spot). Runs of saccade and nosaccade trials were alternated in blocks of 12, and testing always began
with a saccade block to estimate target presentation times, as described
below. In Experiment 1, observers completed 360 trials (180 saccade, 180
no-saccade) in a single testing session. In Experiment 2, each targetflanker separation was tested in a different session, and each observer
completed a minimum of two sessions per target-flanker separation. The
minimum number of trials completed by each observer in Experiment 2
was 3600.
Using a method similar to that described by Hunt and Cavanagh
(2011), the interval between the offset of the fixation spot and target
onset was manipulated to maximize the number of trials presented in
three time bins before saccade onset (Fig. 1C, Fig. 2B). We estimated the
median saccadic latency of a saccade block after each saccade trial, and
from this value subtracted 25, 75, or 125 ms to adjust the delay between
fixation offset and target onset. During testing only, saccade latencies
were taken as the time between fixation spot offset and the time at which
the point of gaze shifted beyond 2° to the right of screen center. Median
saccade latencies were calculated separately for each saccade block. For
the first trial of a block we used the median saccade latency from the
previous block. For the first trial of the experiment, median saccade
latency was manually set to 200 ms. These time adjustments were pseudorandomized across a block of trials, such that there were four of each
(%25, %75, %125 ms) per block of 12. We then used these time adjustments in the next block of no-saccade trials to ensure stimulus timing was
closely matched across saccade and no-saccade blocks. Saccade trial data
Harrison et al. • Eye Movements Release Crowding
J. Neurosci., February 13, 2013 • 33(7):2927–2933 • 2929
means for each time bin, representing an estimate of null performance across time. Using
the distributions of permuted data, we calculated 95% confidence intervals around estimated null performance, such that actual data
falling beyond these intervals represent significant changes in performance across time. To
verify this analysis, we bootstrapped data from
each condition to estimate the distribution of
the means (Efron and Tibshirani, 1993). In this
case, for the number of observations in a given
condition for each observer, we randomly sampled data from that condition (with replacement) to create bootstrapped means. By
repeating this procedure 1000 times we created
C
D
a distribution of means from bootstrapped
data. From these distributions, we derived confidence intervals around the observed means,
where two means falling outside each other’s
confidence intervals represents a significant
change in performance. This analysis yielded
the same significant changes over time as the
permutation method.
Curve fitting and critical distance calculations followed previously described analyses
(Scolari et al., 2007; Yeshurun and Rashal,
2010). Proportion correct data were modeled
using a function with the following equation:
pc ! a(1 " e ("s(d " i ))), d # i, where pc is
proportion correct, a is the asymptote, s is the
scaling factor, d is the target-flanker separaFigure 2. Influence of saccade preparation on visual crowding. A, Mean percentage correct orientation judgments for a tion, and i is the x-intercept. We repeated this
crowded Gabor target during central fixation (black symbol) and at 50 ms intervals before saccade execution (colored symbols). The procedure for each set of bootstrapped data
horizontal red line indicates performance without flanking Gabors. B, Frequency distributions of trials as a function of target- (see above) to derive the confidence intervals.
saccade onset asynchrony. Target onset was timed to yield an approximately equal number of observations across three epochs Critical distance, c, was calculated by: c ! i " ln
(colored frequency distributions), and trials were screened and divided into 50 ms time bins (individual points). Only trials in which (0.1)/s.
the target-saccade latency was #24 ms were included (i.e., included trials were exclusively those in which the target disappeared
We quantified oculomotor precision by
before the eyes moved). C, Graph showing mean gaze deviation from screen center during target presentation. Overlapping fitting an ellipse to saccade endpoints using
symbols show that observers maintained fixation close to the screen center in both no-saccade (black symbol) and saccade (colored custom code in MATLAB. We first found the
symbols) trials. D, Mean saccade endpoints corresponded to each of the three jittered target locations (see Materials and Methods). x-y-coordinate of the center of all saccade endObservers executed eye movements toward the crowded targets with high accuracy, but saccadic errors were generally radially points, then, unconstrained, found the points
dispersed. Error bars indicate 1 SEM. n ! 5.
in 2D space that created the center-to-edge distances of an ellipse comprising 95% of all
points. The axes of the ellipse were calculated
were sorted into bins off-line according to the recorded target-saccade
by finding the two most extreme pairs of x-y coordinates on the circumonset asynchrony, using a velocity of 30°/s and acceleration of 8000°/s 2 as
ference of the ellipse in horizontal and vertical space.
criteria for saccade onset. Following target presentation, there was a delay
Eye trace filtering. Trials were excluded if (1) fixation drifted #2° in any
of 500 ms before observers were able to indicate the orientation of the
direction from the fixation spot; (2) a saccade #2° in amplitude was
target Gabor (rotated left or right off vertical; unspeeded, two-alternative
executed on a no-saccade trial; (3) probe onset occurred earlier than 150
forced-choice judgment).
ms or later than 24 ms before a saccade (with the exception of the analysis
Before testing, each observer completed a threshold procedure in
presented in Fig. 5, see text); (4) the target was presented during an
which we established the minimum orientation to yield 75% correct
eye-blink; and (5) a saccade endpoint was #2° from the target in Experidentification of an unflanked target Gabor. We took the average orieniment 1, or 4° in Experiment 2. In total, 1373 trials (76%) were included
tation yielded by two interleaved QUEST procedures (40 trials each;
in Experiment 1, and 15,353 trials (79%) were included in Experiment 2.
Watson and Pelli, 1983). The target was presented after a delay of between 12 and 200 ms (randomly drawn from a uniform distribution)
following the offset of the fixation spot. Observers were required to mainResults
tain steady fixation throughout threshold trials and gaze was monitored
Experiment 1
on-line. All other trial details during this threshold procedure were as
We first compared discrimination accuracy for a crowded target
described above.
Statistical analyses. To quantify changes in performance over time and
to which observers made a saccade with discrimination accuracy for
across different target-flanker separations (Experiment 2), we used a
the same target when observers instead maintained fixation cenpermutation analysis described by Rolfs et al. (2005, 2011). Expected
trally. The orientation of the target Gabor was adjusted for each
performance under the null hypothesis (i.e., that data within each targetobserver using a staircase procedure (Watson and Pelli, 1983) to
flanker condition are temporally invariant) can be estimated by ranyield 75% correct responses for targets presented in isolation (i.e.,
domly permuting the observed data across time. These permutations
unflanked) when no saccade was planned (see Materials and
were achieved by randomly re-assigning each response to a time bin
Methods). As expected, when no saccade was planned the flank(without replacement), creating a surrogate time course of data for each
ing stimuli impaired orientation judgments for the target Gabor,
individual, from which we derived an average surrogate time course. This
such that observers’ discrimination accuracy fell significantly to
procedure was repeated 1000 times to yield a distribution of surrogate
A
B
2930 • J. Neurosci., February 13, 2013 • 33(7):2927–2933
Harrison et al. • Eye Movements Release Crowding
60 ! 2% (mean ! SEM; two-tailed single
sample t test against 75%: t(4) " 5.93, p "
0.004; Fig. 2A).
When observers prepared a saccade to
the crowded target, orientation judgments improved markedly in the interval
between the signal to saccade to the
crowded target and the initiation of the
saccade (Fig. 2A). When the target and
flankers appeared during the 50 ms immediately before saccade onset, orientation judgments were just as accurate as Figure 3. Presaccadic changes in accuracy of orientation judgments as a function of saccade-onset latency, displayed individwhen the target was presented alone (un- ually for a range of target-flanker separations. The dark horizontal line in each plot shows expected null performance for each
flanked) with no planned saccade. During target-flanker separation, based on permutations of actual data (see Results and Materials and Methods). Shading represents 95%
this same 50 ms epoch before saccade confidence intervals, where observed data falling beyond this area are significant changes in performance across time. n " 5
onset, orientation judgments were also observers.
significantly more accurate than in nosaccade trials (two-tailed paired samples t
separation (Bouma, 1970). When target and flankers were sepatest, t(4) " 4.29, p " 0.013). We screened data from the saccade
rated by 1°, 1.5°, or 2°, accuracy peaked in the final 50 ms before
condition to include only those trials in which the target was
the saccade (purple, blue, and green plots, respectively). In conoffset before the eyes moved (Fig. 2B). Thus, throughout the
trast, accuracy remained unchanged at target-flanker separations
presaccadic interval, target and flanker stimuli always appeared at
of 3.5 and 5° (orange and red plots, respectively).
exactly the same retinal locations as in the no-saccade trials (Fig.
To quantify these changes in target identification accuracy
2C). As shown in Figure 2D, saccades were accurate despite the
across time, we used a permutation analysis to simulate expected
presence of flanking elements, and saccade endpoints were radiperformance under the null hypothesis of no change in accuracy
ally dispersed. The proportion of trials excluded due to saccade
across time (Rolfs et al., 2011; see Materials and Methods). In
error was 5.2, 5.0, and 5.3% for the 0 – 49, 50 –99, and 100 –149
each plot in Figure 3, the dark lines show chance performance
ms presaccade conditions, respectively. These values were statisacross time at each target-flanker separation, and the shaded retically indistinguishable (pairwise comparisons, all ps # 0.69,
gions the 95% confidence intervals around these simulated
uncorrected), ruling out the possibility that improved performeans. Points falling beyond the shaded regions indicate signifimance in the final time bin was artificially inflated by our saccade
cant changes in accuracy. Improved performance just before a
accuracy exclusion criterion.
saccade was significant when target and flankers were separated
To summarize the results of Experiment 1, immediately beby 2°, and fell just short of being significant when target and
fore a saccade, orientation discrimination accuracy is signififlankers were separated by 1° or 1.5°. We verified these analyses
cantly improved for a crowded stimulus that is the target of an
using conventional bootstrapping methods to estimate confiimpending saccade. This release from crowding before a saccade
dence intervals (Efron and Tibshirani, 1993; see Materials and
yielded target judgments that were just as accurate as those made
Methods), which yielded the same significant changes over time
for unflanked targets at the same peripheral location in the noas described for the permutation tests. Together, the results reveal
saccade condition.
that presaccadic perceptual benefits for the 7° target were not
equal across all flanker separations, but were limited to the smallExperiment 2
est separations, with marked improvement when flankers were
Having established that visual crowding is significantly reduced
separated from the target by 2°.
when a peripheral stimulus is the target of a saccade, we next
To estimate the critical distance of crowding we computed
tested whether the critical distance of crowding around a target is
exponential
fits to the accuracy data across target-flanker separaalso reduced just before an eye movement. A reduction in critical
tions,
separately
for no-saccade trials and for saccade trials in
distance would suggest eye movement signals interact with the
which
the
target
was
presented within 50 ms before saccade execompulsory averaging of visual features (Pelli, 2008; Pelli and
cution
(see
Materials
and Methods). Figure 4 shows the resulting
Tillman, 2008), effectively enhancing object discrimination in
functions plotted separately for no-saccade trials (gray) and sacperipheral vision at the goal of the intended saccade. There are
cade trials (maroon). By convention (Scolari et al., 2007;
conflicting reports as to whether advance information reduces
Yeshurun and Rashal, 2010) the critical distance of crowding is
the critical distance of crowding in the absence of eye movements,
defined as 90% of the asymptotic value for each function (see
despite improvements in target identification accuracy (Felisbert
Materials and Methods). The critical distance for no-saccade triet al., 2005; Strasburger, 2005; Scolari et al., 2007; Yeshurun and
als was estimated at 3.7°. Expressed as a ratio of target eccentricRashal, 2010). In a second experiment, therefore, we tested oriity, this yields a critical distance of 0.53!, conforming well to
entation discrimination for a peripheral target located at 7° ecBouma’s law (Bouma, 1970; Pelli and Tillman, 2008). In contrast,
centricity, and surrounded by nontarget stimuli across a range of
critical distance during the final 50 ms before a saccade was estitarget-flanker separations. As in Experiment 1, observers either
mated at 2.0°, or 0.28!, a 47% decrease in the critical distance
made a saccade to the target, or remained fixated at the center of
observed during fixation.
the display.
In absolute terms, the critical distance for saccade trials indiFigure 3 shows the accuracy of target orientation judgments as
cates that flankers interfered with identification when they apa function of the time to saccade onset, plotted separately for each
peared within 2° of the target stimulus. This critical distance
target-flanker separation. As expected, orientation judgments beestimate is consistent with the accuracy data presented in Figure
came progressively more accurate with increases in target-flanker
Harrison et al. • Eye Movements Release Crowding
J. Neurosci., February 13, 2013 • 33(7):2927–2933 • 2931
A
B
Figure 4. Change in the critical distance of crowding just before a saccade. A, Critical distance of crowding when no saccade is planned (gray fitted curve and vertical line) and in the
final 50 ms before a saccade (maroon fitted curve and vertical line). The upper x-axis shows
target-flanker separation as a proportion of the target eccentricity, !. Error bars indicate 95%
confidence intervals of the curves, derived from standard bootstrapping procedures (see Materials and Methods; Efron and Tibshirani, 1993). B, Horizontal and vertical gaze position during
target presentation, shown as separate colored disks for the no-saccade condition (open symbols) and the 0 – 49 ms presaccade condition. Colors denote target-flanker separations as in
Figure 3. Error bars have been omitted for clarity.
3: while accuracy improved significantly when flankers were 2° from
the target, no statistically reliable improvements in orientation judgments were observed when target-flanker separations were !2°. The
influence of saccade preparation on the critical distance of crowding
cannot be attributed to differences in the retinal positions of target
and flanker stimuli in saccade versus no-saccade trials. Horizontal
and vertical gaze position during target presentation were matched
across no-saccade trials and trials in which the target was presented
in the final 50 ms before the saccade (Fig. 4B).
In line with studies showing eye movement centers influence
visual processing of uncrowded stimuli (Corbetta et al., 1998;
Moore and Armstrong, 2003), we propose that oculomotor programming interacts with early visual processes to alleviate crowding. If the reduction in the critical distance of crowding is due to
spatially precise selection of the target location immediately before a saccade, then there should be a tight relationship between
critical distance and the precision of oculomotor selection. To
test this hypothesis, we plotted the accuracy of saccade landing
points relative to the target position for all observers (Fig. 5A).
The red and purple points show mean saccadic deviation from
the target center when flankers were separated from the target by
1° or 5°, respectively. These points fell the same distance from
target center, revealing that oculomotor accuracy was unaffected
by target-flanker separation. Each black spot in Figure 5A repre-
Figure 5. Relationship between oculomotor precision and the critical distance of crowding.
A, The horizontal and vertical deviations of 8153 saccade endpoints obtained from five observers are plotted on the x- and y-axes, respectively. Position 0°, 0° represents the target center,
and the target Gabor extended from "0.5° to #0.5° on both axes. Saccades with negative
x-values fell short of the saccade target center, and saccades with positive x-values overshot the
target center. An ellipse was adjusted to fit 95% of the saccade endpoints. As shown by the
ellipse and its axes, saccadic precision was radially biased. The purple and red points show
average deviations of saccade endpoints to targets with flankers at distances of 1 and 5°,
respectively. There was no difference between these points; the proximity of flankers to the
target did not interfere with oculomotor selection. B, The spatial extent of observers’ oculomotor radial precision closely matches the edge-to-edge spatial extent of crowding within 50 ms
before a saccade, and both are approximately half the spatial extent of crowding when no
saccade is planned.
sents the endpoint of a saccade included in the critical distance
estimates for Experiment 2. We fitted an ellipse that encompassed
95% of all saccade endpoints (see Materials and Methods). The
horizontal extent of the ellipse corresponds to the radial precision
of the saccades and the vertical extent denotes the tangential precision. The axes of the fitted ellipse reveal that saccadic precision
is poorer in the radial plane than in the tangential plane, with a
radial-to-tangential ratio of 1.6. This asymmetry in saccadic precision corresponds closely to the classical radial-tangential asymmetry of critical distance measured using pairs of flankers
arranged either radially or tangentially with respect to the target
(Toet and Levi, 1992). Moreover, as shown in Figure 5B, the
absolute, edge-to-edge spatial extent of crowding when no saccade was planned (gray line) is approximately twice that observed
for trials in the 50 ms just before a saccade (maroon line). Note
that oculomotor precision (pink line) closely approximates the
spatial extent of crowding just before a saccade.
We further tested the extent to which saccade endpoints are
related to identification of a crowded target by comparing performance for trials in which saccades deviated from the target
center by more than one degree with those in which the saccade
fell within one degree of the target center. We performed this
2932 • J. Neurosci., February 13, 2013 • 33(7):2927–2933
analysis separately for three conditions that represent the full
range of perceptual performance. We chose (1) the condition in
which performance was poorest (100 –149 ms time bin, 1° targetflanker separation); (2) the condition in which performance
improved the most (0 – 49 ms time bin, 2° target-flanker separation); and (3) the condition in which performance was best
(0 – 49 ms time bin, 5° target-flanker separation; see Fig. 3). We
chose these three conditions to maximize the likelihood of uncovering any effect of saccade accuracy, while limiting the risk of
type 1 error due to multiple post hoc comparisons. There was no
difference in target discrimination according to saccade accuracy
in any of these conditions ( ps ! 0.81, uncorrected), and the
differences in performance were "1.5% within each condition.
Thus, performance corresponds best to the overall precision of
eye movements (Fig. 5A) rather than the accuracy of saccade
endpoints.
Discussion
We have shown that improvements in perception immediately
before saccade onset, previously demonstrated with isolated
stimuli in sparse displays (Remington, 1980; Kowler et al., 1995;
Deubel and Schneider, 1996; Moore and Armstrong, 2003;
Deubel, 2008), can also operate to release peripheral targets from
visual crowding. By systematically varying target-flanker separations, we also found that the critical distance of crowding established during passive fixation shrinks by approximately half in
the 50 ms immediately before saccade onset. The changes in
crowding we observed during saccade trials relative to no-saccade
trials cannot be attributed to differences in the retinal locations of
target and flanker stimuli, as the critical visual events were offset
before any eye movements. Moreover, in both saccade and nosaccade conditions observers always knew the precise location of
the upcoming target, indicating that the saccade-related mitigation of crowding cannot be ascribed to differences in advance
positional information.
The fact that crowding of a target at a fixed retinal eccentricity
is significantly attenuated before a saccade implies that extraretinal signals that arise just before the eyes move (Wurtz, 2008) play
a key role in modifying the spatial extent of visual crowding, and
extend a recent computational modeling report linking crowding
and eye movements (Nandy and Tjan, 2012). Enhancement in
perceived contrast at the saccade goal (e.g., Rolfs and Carrasco,
2012) might have contributed to the improved discriminability
of the crowded targets in our experiments, but our finding that
performance improvements varied across target-flanker separations (Fig. 3) suggests that changes in perceived contrast alone
cannot account for the results. The change in critical distance just
before a saccade (Fig. 4A) reflects the fact that target identification improved most for the smallest target-flanker separations,
but did not change for the larger separations. If the presaccadic
benefit we have shown were attributable solely to contrast enhancement of the target, this effect should have been equivalent
across all target-flanker separations. Moreover, attempts to mitigate crowding by cueing attention to the target, which has also
been linked to increased contrast sensitivity (Carrasco et al.,
2000), have not yielded reliable reductions in visual crowding
(Scolari et al., 2007; Yeshurun and Rashal, 2010).
Changes in the spatial extent of crowding before a saccade
suggest that oculomotor signals required for accurate localization
of a saccade target can influence responses of visual neurons involved in integrating form information from the peripheral visual field. Such an influence is consistent with evidence for a close
functional relationship between oculomotor and visual sensory
Harrison et al. • Eye Movements Release Crowding
areas in the primate brain (Wurtz and Mohler, 1976; Umeno and
Goldberg, 1997; Moore et al., 1998; Tolias et al., 2001; Moore and
Armstrong, 2003; Moore and Fallah, 2004; Gregoriou et al.,
2012). In particular, Tolias et al. (2001) found that just before a
saccade there is a reduction in the size of the receptive fields of
neurons throughout V4, an area thought to be important in
crowding (Anderson et al., 2012), as well as a shift of these receptive fields toward the saccade goal. Such a reduction in the size of
receptive fields of V4 neurons could result in a corresponding
reduction in the critical distance of crowding. Indeed, the mean
reduction in receptive field size reported by Tolias et al. (2001)
was 2.1°, similar to the 1.7° reduction in critical distance we observed just before a saccade (Fig. 4A). Critically, the changes in
receptive field sizes observed by Tolias et al. (2001) were greatest
in the final 50 ms before saccade onset, consistent with our findings in human observers.
The observation that crowding is reduced before a saccade is
consistent with recent accounts that suggest that crowding arises
from imprecise position information for peripheral stimuli.
Greenwood et al., (2009) found that the perceived position of
target elements can be accounted for by a weighted average of
noisy representations of target- and flanker-feature positions.
Following this finding, our results can be explained by assuming
that operations involved in preparing and executing an eye
movement to a crowded target effectively change the weights of
target- and flanker-position noise. For example, weightings for
flanker stimuli might be reduced just before oculomotor target
selection, via suppression of neural activity in FEF associated with
distractor stimuli (Schall et al., 1995). In line with this, saccadic
accuracy in Experiment 2 was unaffected by the separation between target and flanking stimuli (Fig. 5A). Alternatively, an impending saccade to a crowded target could simply reduce the
position noise of the target via a reduction in the size of the
receptive fields of V4 neurons that represent the target (Tolias et
al., 2001). Performance for crowded targets is well modeled using
values for position and identity uncertainty of unflanked targets
(van den Berg et al., 2012), suggesting that sharpening of target
position estimates could form the basis for reduced crowding
before saccades.
Previous studies have linked perceptual enhancements during
saccade and nonsaccade conditions to common neural activity in
such areas as FEF and posterior parietal cortex, both of which are
known to play an active role in saccade generation (Corbetta and
Shulman, 2002). Indeed, changes in the gain of V4 neurons occur
even when FEF activity is below that required to trigger a saccade
(Moore and Armstrong, 2003; Moore and Fallah, 2004). In line
with these accounts, both the elliptical shape and radialtangential asymmetry of saccadic precision we observed in Experiment 2 (Fig. 5) correspond to the classic spatial characteristics of
crowding zones measured previously (Toet and Levi, 1992).
These observations suggest a functional interaction between oculomotor control systems and visual neurons whose responses
are susceptible to crowding in the absence of eye movements.
Crucially, our data also reveal that the substantial gains in target
discriminability and reductions in critical distance for saccade
targets arise exclusively in the last 50 ms before a saccade, consistent with recent psychophysical reports for uncrowded stimuli
(Deubel, 2008; Rolfs and Carrasco, 2012; Rolfs et al., 2011). The
time course of these perceptual changes raises the possibility that,
in addition to the benefits associated with target selection alone,
visual centers involved in oculomotor preparation and execution
can modulate visual sensitivity during the immediate presaccadic
period (but see Gregoriou et al., 2012).
Harrison et al. • Eye Movements Release Crowding
An interesting finding in Experiment 2 was that the spatial
extent of crowding observed just before a saccade corresponded
closely with the overall precision of saccades (Fig. 5). Yet, observers’ ability to identify the target did not vary according to the
accuracy of saccade endpoints. This finding suggests that changes
in crowding during saccade preparation do not simply depend on
the specific outcome of the saccade motor command. In our
experiment, presaccadic changes in the identification of a target
at 7° in peripheral vision were relatively uniform when saccades
landed within 2° of the target. These data show that the benefits
from saccade preparation accrue to a region around the intended
endpoint and are not determined by the precision of the executed
saccade.
In summary, the current findings are consistent with the idea
that oculomotor signals associated with intended eye movements
can alter the resolution of object identification within a spatial
zone immediately surrounding a peripheral saccade target. This
hypothesized link between oculomotor control and visual perception is further supported by the finding that the distribution
of saccade errors closely matches the characteristic, radially biased spatial region within which crowding occurs. By using oculomotor signals to release saccade targets from crowding, the
visual system may effectively “presample” an object that will soon
be foveated for detailed processing. Such a preview of the saccade
target may help to explain the subjective experience of visual
continuity across eye movements in natural environments where
peripheral vision is densely cluttered.
References
Anderson EJ, Dakin SC, Schwarzkopf DS, Rees G, Greenwood JA (2012)
The neural correlates of crowding-induced changes in appearance. Curr
Biol 22:1199 –1206. CrossRef Medline
Bouma H (1970) Interaction effects in parafoveal letter recognition. Nature
226:177–178. CrossRef Medline
Brainard DH (1997) The Psychophysics Toolbox. Spat Vis 10:433– 436.
CrossRef Medline
Carrasco M, Penpeci-Talgar C, Eckstein M (2000) Spatial covert attention
increases contrast sensitivity across the CSF: support for signal enhancement. Vision Res 40:1203–1215. CrossRef Medline
Corbetta M, Shulman GL (2002) Control of goal-directed and stimulusdriven attention in the brain. Nat Rev Neurosci 3:201–215. Medline
Corbetta M, Akbudak E, Conturo TE, Snyder AZ, Ollinger JM, Drury HA,
Linenweber MR, Petersen SE, Raichle ME, Van Essen DC, Shulman GL
(1998) A common network of functional areas for attention and eye
movements. Neuron 21:761–773. CrossRef Medline
Cornelissen FW, Peters EM, Palmer J (2002) The Eyelink Toolbox: eye
tracking with MATLAB and the Psychophysics Toolbox. Behav Res Methods Instrum Comput 34:613– 617. CrossRef Medline
Deubel H (2008) The time course of presaccadic attention shifts. Psychol
Res 72:630 – 640. CrossRef Medline
Deubel H, Schneider WX (1996) Saccade target selection and object recognition: evidence for a common attentional mechanism. Vision Res 36:
1827–1837. CrossRef Medline
Efron B, Tibshirani R (1993) An introduction to the bootstrap. New York:
Chapman and Hall.
Felisbert FM, Solomon JA, Morgan MJ (2005) The role of target salience in
crowding. Perception 34:823– 833. CrossRef Medline
Greenwood JA, Bex PJ, Dakin SC (2009) Positional averaging explains crowding with letter-like stimuli. Proc Natl Acad Sci U S A 106:13130 –13135.
CrossRef Medline
Gregoriou GG, Gotts SJ, Desimone R (2012) Cell-type-specific synchronization of neural activity in FEF with V4 during attention. Neuron 73:581–
594. CrossRef Medline
J. Neurosci., February 13, 2013 • 33(7):2927–2933 • 2933
Hunt AR, Cavanagh P (2011) Remapped visual masking. J Vis 11(1):13 1– 8.
CrossRef Medline
Kowler E, Anderson E, Dosher B, Blaser E (1995) The role of attention in the
programming of saccades. Vision Res 35:1897–1916. CrossRef Medline
Levi DM (2008) Crowding–an essential bottleneck for object recognition: a
mini-review. Vision Res 48:635– 654. CrossRef Medline
Moore T, Armstrong KM (2003) Selective gating of visual signals by microstimulation of frontal cortex. Nature 421:370 –373. CrossRef Medline
Moore T, Fallah M (2004) Microstimulation of the frontal eye field and its
effects on covert spatial attention. J Neurophysiol 91:152–162. Medline
Moore T, Tolias AS, Schiller PH (1998) Visual representations during saccadic eye movements. Proc Natl Acad Sci U S A 95:8981– 8984. CrossRef
Medline
Moore T, Armstrong KM, Fallah M (2003) Visuomotor origins of covert
spatial attention. Neuron 40:671– 683. CrossRef Medline
Nandy AS, Tjan BS (2012) Saccade-confounded image statistics explain visual crowding. Nat Neurosci 15:463– 469, S1–S2. CrossRef Medline
Parkes L, Lund J, Angelucci A, Solomon JA, Morgan M (2001) Compulsory
averaging of crowded orientation signals in human vision. Nat Neurosci
4:739 –744. CrossRef Medline
Pelli DG (1997) The VideoToolbox software for visual psychophysics:
transforming numbers into movies. Spat Vis 10:437– 442. CrossRef
Medline
Pelli DG (2008) Crowding: a cortical constraint on object recognition. Curr
Opin Neurobiol 18:445– 451. CrossRef Medline
Pelli DG, Tillman KA (2008) The uncrowded window of object recognition.
Nat Neurosci 11:1129 –1135. Medline
Remington RW (1980) Attention and saccadic eye movements. J Exp Psychol Hum Percept Perform 6:726 –744. CrossRef Medline
Rolfs M, Carrasco M (2012) Rapid simultaneous enhancement of visual
sensitivity and perceived contrast during saccade preparation. J Neurosci
32:13744 –13752a. CrossRef Medline
Rolfs M, Engbert R, Kliegl R (2005) Crossmodal coupling of oculomotor
control and spatial attention in vision and audition. Exp Brain Res 166:
427– 439. CrossRef Medline
Rolfs M, Jonikaitis D, Deubel H, Cavanagh P (2011) Predictive remapping
of attention across eye movements. Nat Neurosci 14:252–256. CrossRef
Medline
Schall JD, Hanes DP, Thompson KG, King DJ (1995) Saccade target selection in frontal eye field of macaque. I. Visual and premovement activation. J Neurosci 15:6905– 6918. Medline
Scolari M, Kohnen A, Barton B, Awh E (2007) Spatial attention, preview,
and popout: which factors influence critical spacing in crowded displays?
J Vis 7(2):7 1–23. CrossRef Medline
Strasburger H (2005) Unfocused spatial attention underlies the crowding
effect in indirect form vision. J Vis 5(11):1024 –1037. CrossRef
Toet A, Levi DM (1992) The two-dimensional shape of spatial interaction
zones in the parafovea. Vision Res 32:1349 –1357. CrossRef Medline
Tolias AS, Moore T, Smirnakis SM, Tehovnik EJ, Siapas AG, Schiller PH
(2001) Eye movements modulate visual receptive fields of V4 neurons.
Neuron 29:757–767. CrossRef Medline
Umeno MM, Goldberg ME (1997) Spatial processing in the monkey frontal
eye field. I. Predictive visual responses. J Neurophysiol 78:1373–1383.
Medline
van den Berg R, Johnson A, Martinez Anton A, Schepers AL, Cornelissen FW
(2012) Comparing crowding in human and ideal observers. J Vis.
12(6):13 1–14. CrossRef Medline
Watson AB, Pelli DG (1983) QUEST: a Bayesian adaptive psychometric
method. Percept Psychophys 33:113–120. CrossRef Medline
Whitney D, Levi DM (2011) Visual crowding: a fundamental limit on conscious perception and object recognition. Trends Cogn Sci 15:160 –168.
CrossRef Medline
Wurtz RH (2008) Neuronal mechanisms of visual stability. Vision Res 48:
2070 –2089. CrossRef Medline
Wurtz RH, Mohler CW (1976) Enhancement of visual responses in monkey
striate cortex and frontal eye fields. J Neurophysiol 39:766 –772. Medline
Yeshurun Y, Rashal E (2010) Precueing attention to the target location diminishes crowding and reduces the critical distance. J Vis 10(10):16 1–12.
CrossRef Medline
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertising