High temporal precision for perceiving event offsets

Abstract

Characterizing the temporal limits of the human visual system has long been a central goal of vision research. Spanning three centuries of research, temporal order judgments have been used to estimate the temporal precision of visual processing, with nearly all the research focusing on onset asynchrony discriminations. Recent neurophysiological work, however, demonstrated that neural latencies for stimulus offsets are shorter and less variable than those following event onsets, suggesting that event offsets might provide more reliable timing cues to the visual system than event onsets. Here, we tested this hypothesis by measuring psychophysical thresholds for discriminating onset and offset asynchronies for both stationary and moving stimuli. In three experiments, we showed that offset asynchrony thresholds were indeed consistently lower and were less affected by stimulus variations than onset asynchrony thresholds. These findings are consistent with neurophysiology and suggest a possible role of offset signals as reliable timing references for visual events.

Keywords: Event offset; Event onset; Temporal order; Temporal resolution; Vision.

Fig. 1

A schematic illustrating the time course of a single offset asynchrony trial. Observers' task was to indicate which Gabor patch disappeared first by pressing a designated key (corresponding to the left Gabor in this example). For the purposes of this illustration, the duration of the offset asynchrony is exaggerated. See Experiment 1 Methods section for additional details.

Fig. 2

Results of Experiment 1. (A) Psychometric functions for an observer (DT), showing the percentage of trials in which the right Gabor patch was identified as appearing/disappearing first as a function of temporal asynchrony in the condition where the spatial separation was set to 3.3°. Solid and empty symbols show results for offset and onset asynchrony trials, respectively. Data were fit with a cumulative normal function, from which we estimated the JND value by computing the half-difference between asynchrony values yielding 75% and 25% points. (B) Group data showing JNDs for onset and offset asynchrony discriminations as a function of spatial separation. Error bars are SEM.

Fig. 3

Results of Experiment 2. Psychometric functions for an observer (DT) showing results in the offset (A) and (B) onset asynchrony task. Circles show the data for the conditions where target Gabors moved in the same direction. Triangles depict the data for the conditions with target Gabors moving in the opposing directions. (C) Group data showing JNDs for onset and offset asynchrony discriminations as a function of relative direction of target Gabor patches. Error bars are SEM.

Fig. 4

Results and stimuli of Experiment 3. (A) Screen snapshots of stimuli used in Experiment 3. The top right panel is the stimulus in the homogeneous condition. The panels to the right and below illustrate ±0.5 log unit random variations in contrast and spatial frequency, respectively. The bottom right panel shows a stimulus varied in both contrast and spatial frequency. (B) Group data showing temporal asynchrony thresholds for onset and offset asynchrony discriminations as a function of contrast and/or spatial frequency variation. (C) “Threshold cost” for onset and offset asynchrony discrimination across contrast, spatial frequency, and joint contrast + spatial frequency variation conditions. Threshold cost was calculated by subtracting the onset and offset thresholds for the homogeneous stimulus (the leftmost points in B) from the thresholds estimates for the conditions with ±0.5 log unit variation (the rightmost points in B). Error bars are SEM.