Effects of involuntary and voluntary attention on critical spacing of visual crowding

Abstract

Visual spatial attention can be allocated in two distinct ways: one that is voluntarily directed to behaviorally relevant locations in the world, and one that is involuntarily captured by salient external stimuli. Precueing spatial attention has been shown to improve perceptual performance on a number of visual tasks. However, the effects of spatial attention on visual crowding, defined as the reduction in the ability to identify target objects in clutter, are far less clear. In this study, we used an anticueing paradigm to separately measure the effects of involuntary and voluntary spatial attention on a crowding task. Each trial began with a brief peripheral cue that predicted that the crowded target would appear on the opposite side of the screen 80% of the time and on the same side of the screen 20% of the time. Subjects performed an orientation discrimination task on a target Gabor patch that was flanked by other similar Gabor patches with independent random orientations. For trials with a short stimulus onset asynchrony between cue and target, involuntary capture of attention led to faster response times and smaller critical spacing when the target appeared on the cue side. For trials with a long stimulus onset asynchrony, voluntary allocation of attention led to faster reaction times but no significant effect on critical spacing when the target appeared on the opposite side to the cue. We additionally found that the magnitudes of these cueing effects of involuntary and voluntary attention were not strongly correlated across subjects for either reaction time or critical spacing.

Figure 1.

Schematic of the anticueing task. After a fixation interval, one set of vertical bars became thicker and brighter for 40 ms. After an SOA of 40 ms (short) or 600 ms (long), the crowded stimuli appeared for 133 ms within one of the two sets of vertical bars. In $20\%$ of trials, the stimuli appeared on the cued side and in $80\%$ of trials, the stimuli appeared on the opposite side. Stimuli were composed of a central target Gabor patch ($45{}^{\circ }$ or $135{}^{\circ }$ orientation) and two sets of two flanking Gabor patches with independent random orientations. Target/flanker spacing was varied over a range of center-to-center distances, and the range of spacings and the size of the Gabor patches were customized for each subject (see Methods). There was also a condition in which the target was presented without flankers. Subjects performed a two-alternative forced choice task on the orientation of the target Gabor patch as quickly and as accurately as possible without moving their eyes from the central fixation cross. We recorded RT and accuracy. Gabor patch and cue sizes shown here were increased for visualization purposes and are not representative of actual experimental values.

Figure 2.

Mean subject task accuracy (left) and mean subject median RT (right) as a function of mean target/flanker spacing for each cue location (opposite or cue side) and SOA (short = 40 ms; long = 600 ms) combination. Note that the range of target/flanker spacing values were customized for each individual subject. Therefore, the displayed target/flanker spacing values are the average across subjects for each of the seven nominal spacings. A Weibull function (Equation 1) and a single line were fit to the averaged data across subjects for accuracy and RT, respectively. Error bars are standard errors of the mean. The black dashed line represents the designated task performance at the critical spacing.

Figure 3.

(Top) The effect of stimulus location relative to cue location (opposite or cue side) and SOA (40 or 600 ms) on RT (left; blue) and critical spacing (right; orange) for the crowding task. Gray lines represent matched individual subject data across location conditions. (Bottom) Mean within-subject cueing effects for each metric, defined as the difference between values when the stimulus appeared on the same side as the cue (Cue) and values when the stimulus appeared on the opposite side of the cue (Opp.). Gray dots represent individual subjects, and asterisks indicate significance $\alpha \text{level}<0.05$ from a planned comparison paired t test. Error bars are standard errors of the mean.

Figure 4.

Cueing effects on RT were not strongly correlated with cueing effects on critical spacing for either short SOA (left) or long SOA (right) trials. The ‘x’s represent individual subjects. The solid and dashed lines represent the linear regression fits and $95\%$ confidence intervals, respectively. Pearson’s $r$ and $p$ values for the correlations are displayed in the upper right corner of each plot. Attention “enhances” or “impairs” labels correspond with the direction of the cueing effect for each of these metrics. Specifically, enhanced processing due to attention (i.e., faster RT/smaller critical spacing) is associated with a negative cueing effect (Cue $<$ Opp.) for involuntary attention and with a positive cueing effect (Cue $>$ Opp.) for voluntary attention.

Figure 5.

Cueing effects for involuntary (short SOA trials) and voluntary attention (long SOA trials) were not significantly correlated across individual subjects for both RT (left; blue) and critical spacing (right; orange). The ‘x’s represent individual subjects. The solid and dashed lines represent the linear regression fits and $95\%$ confidence intervals, respectively. Pearson’s $r$ and $p$ values for the correlations are displayed in the upper right corner of each plot. Attention “enhances” or “impairs” labels correspond to the direction of the cueing effect for each of these metrics. Specifically, enhanced processing due to attention (i.e., faster RT/smaller critical spacing) is associated with a negative cueing effect (Cue $<$ Opp.) for involuntary attention and with a positive cueing effect (Cue $>$ Opp.) for voluntary attention.