Directing Voluntary Temporal Attention Increases Fixational Stability

Abstract

Our visual input is constantly changing, but not all moments are equally relevant. Visual temporal attention, the prioritization of visual information at specific points in time, increases perceptual sensitivity at behaviorally relevant times. The dynamic processes underlying this increase are unclear. During fixation, humans make small eye movements called microsaccades, and inhibiting microsaccades improves perception of brief stimuli. Here, we investigated whether temporal attention changes the pattern of microsaccades in anticipation of brief stimuli. Human observers (female and male) judged stimuli presented within a short sequence. Observers were given either an informative precue to attend to one of the stimuli, which was likely to be probed, or an uninformative (neutral) precue. We found strong microsaccadic inhibition before the stimulus sequence, likely due to its predictable onset. Critically, this anticipatory inhibition was stronger when the first target in the sequence (T1) was precued (task-relevant) than when the precue was uninformative. Moreover, the timing of the last microsaccade before T1 and the first microsaccade after T1 shifted such that both occurred earlier when T1 was precued than when the precue was uninformative. Finally, the timing of the nearest pre- and post-T1 microsaccades affected task performance. Directing voluntary temporal attention therefore affects microsaccades, helping to stabilize fixation at the most relevant moments over and above the effect of predictability. Just as saccading to a relevant stimulus can be an overt correlate of the allocation of spatial attention, precisely timed gaze stabilization can be an overt correlate of the allocation of temporal attention.SIGNIFICANCE STATEMENT We pay attention at moments in time when a relevant event is likely to occur. Such temporal attention improves our visual perception, but how it does so is not well understood. Here, we discovered a new behavioral correlate of voluntary, or goal-directed, temporal attention. We found that the pattern of small fixational eye movements called microsaccades changes around behaviorally relevant moments in a way that stabilizes the position of the eyes. Microsaccades during a brief visual stimulus can impair perception of that stimulus. Therefore, such fixation stabilization may contribute to the improvement of visual perception at attended times. This link suggests that, in addition to cortical areas, subcortical areas mediating eye movements may be recruited with temporal attention.

Keywords: eye movements; microsaccades; oculomotor; temporal attention; visual perception; voluntary attention.

Figure 1.

Task and behavior. a, Schematic of eye-tracking and display setup. Observers fixated on a central cross and all stimuli appeared in the lower right quadrant. b, Trial timeline for two-target tasks (Experiments 1 and 3). In Experiment 3, a probe grating appeared after the response cue, which the observer adjusted to estimate orientation (not shown). c, Trial timeline for three-target task (Experiment 2). d, Performance accuracy normalized to average neutral performance for each observer, mean and SEM. Experiments 1–3, n = 30. V, Valid; N, neutral; I, invalid. **p < 0.01; ***p < 0.001.

Figure 2.

Microsaccade rate. a, Mean microsaccade rate across the trial. Data are combined across the common precue conditions of Experiments 1–3 (neutral, T1, T2, shown as separate colored lines). Dashed vertical lines show trial events. The response cue is not shown because its timing differs for two-target and three-target tasks. Light gray shading shows the pretarget inhibition period used for statistical analysis and arrow indicates the posttarget rebound. b, Enlargement of pretarget inhibition period labeled in a. Dark gray shading shows significant cluster-corrected time windows, T1 < neutral, p < 0.05.

Figure 3.

Microsaccade timing. a, Raster plot showing microsaccade (MS) onset times (blue ticks) in 40 precue T1 trials for an example observer from Experiment 2. Dashed vertical lines show trial events. For each trial, the latencies of the last pre-T1 MS and first post-T1 MS were recorded to quantify inhibition and rebound timing, respectively. b, Distribution across trials of inhibition (last pre-T1 MS) latencies for another example observer from Experiment 2. Precue conditions are shown in different colors. c, Inhibition latency distributions (last pre-T1 MS) for the group of observers. Latencies were z-scored to combine across observers with different overall timings and MS rates. Colored lines and shaded regions show mean and SEM of the estimated probability density for each precue condition. Vertical lines show the medians of the group distributions. d, Summary of group latencies. Markers and error bars show mean and SEM of each observer's median z-scored latency for each precue condition. The absolute magnitude of the latency difference between precue T1 and neutral conditions was 37 ms. e and f correspond to c and d, but show the rebound (first post-T1 MS) latencies. Experiments 1–3, n = 30; Experiment 2, n = 9.

Figure 4.

Directions of inhibition (last pre-T1) and rebound (first post-T1) microsaccades. Polar histograms show the proportion of trials with microsaccades in each direction of the total number of trials with pre-T1/post-T1 microsaccades. Target stimuli were positioned at 315°.

Figure 5.

Relation between microsaccades and behavior. a, Test of behavioral microsaccadic suppression. Change in the accuracy of target report when a microsaccade occurred 0–100 ms before the target compared with when no microsaccade occurred in that interval. b, Effect of last pre-T1 and first post-T1 MS latency on behavior. Latencies are binned into 200 ms intervals (separated by gray vertical lines). Markers show change in accuracy when a MS occurred in a bin compared with mean accuracy across all trials for a given target. Mean and SEM are shown for each target (colored markers and lines). Dashed vertical lines show trial events. Experiments 1–3, n = 30; Experiment 2, n = 9. **p < 0.01. c, Same as the central portion of b, but with higher temporal resolution (100 ms latency bins, 10 ms steps) to assess MS-driven behavioral tradeoffs between T1 and T2. (T3 is not replotted at higher resolution because of lower reliability due to fewer observers.) Gray-shaded region shows significant cluster-corrected time window (bin centers ±50 ms) for the difference between T1 and T2, p < 0.05. n = 30.