Attention moderates the motion silencing effect for dynamic orientation changes in a discrimination task

Abstract

Being able to detect changes in our visual environment reliably and quickly is important for many daily tasks. The motion silencing effect describes a decrease in the ability to detect feature changes for faster moving objects compared with stationary or slowly moving objects. One theory is that spatiotemporal receptive field properties in early vision might account for the silencing effect, suggesting that its origins are low-level visual processing. Here, we explore whether spatial attention can modulate motion silencing of orientation changes to gain greater understanding of the underlying mechanisms. In Experiment 1, we confirm that the motion silencing effect occurs for the discrimination of orientation changes. In Experiment 2, we use a Posner-style cueing paradigm to investigate whether manipulating covert attention modulates motion silencing for orientation. The results show a clear spatial cueing effect: Participants were able to discriminate orientation changes successfully at higher velocities when the cue was valid compared to neutral cues and performance was worst when the cue was invalid. These results show that motion silencing can be modulated by directing spatial attention toward a moving target and provides support for a role for higher level processes, such as attention, in motion silencing of orientation changes.

Figure 1.

Example trial sequence for Experiment 1. The arrows represent example global and local rotation directions; in this trial, the annulus rotated clockwise and half of the individual Gabors rotated clockwise. The other half did not change orientation. The size and hue of the panels are exaggerated for clarity.

Figure 2.

Representative psychometric curve fits for discrimination task performance. Error bars denote the standard error of proportion. Curve fits are from Participant 5 and Participant 12, respectively.

Figure 3.

Box plot of participants’ 75% orientation discrimination thresholds. The red triangles represent individual participant 75% thresholds.

Figure 4.

Example trial sequence for Experiment 2 showing the different cue types. The arrows represent example rotation directions; in these example trials, the annulus rotated counterclockwise and the Gabors rotated clockwise. The size and hue of the panels are exaggerated for clarity.

Figure 5.

Mean threshold collapsed across participants by cue type. Individual data are shown as a line plot. Black dots show cue-type threshold means. Error bars denote (across participant) 95% confidence intervals.

Figure 6.

Mean RTs collapsed across participants by cue type. Individual data are shown as line a plot. Black dots show cue-type RTs. Error bars denote (across participant) 95% confidence intervals.