Abstract
The severe capacity limit of visual working memory (VWM) necessitates an efficient filtering mechanism to represent task-relevant items in VWM and restrict task irrelevant items from consuming capacity. Previous studies have shown that selective attention benefits post-perceptual as well as perceptual processing by filtering unnecessary items out of VWM (Vogel, McCollough, & Machizawa, 2005). The present study asked whether the attentional filtering is supported by the same mechanism across various loci of VWM processing such as encoding and retention stages. To answer this question, we measured the contralateral delay activity (CDA), a neural index of VWM capacity, while participants filtered out task-irrelevant VWM representations. Participants were asked to remember four sample color squares to be tested after a 1s delay period. In the selective encoding condition, a position-cue was presented at one of the four color squares at the sample display. The position-cue indicated a test location, allowing the participants to selectively encode only the cued item in VWM. In the selective forgetting condition, the same position-cue was presented at the middle of the delay period, allowing the participants to selectively hold the cued item in VWM and to forget the other three color squares. Behavioral results showed both cues improved the performance compared to the baseline condition in which the position-cue was not presented. However, the CDA showed sizable reduction only in the selective encoding condition, but not in the selective forgetting condition. These results suggest that although an attentional cue benefits the behavioral performance at both the encoding and retention stage in VWM, underlying mechanism for these cueing benefits are dissociable. Namely, while the attentional selection at the encoding stage are coupled with excluding unnecessary items from VWM, attentional selection at the retention stage does not accompany exclusion of no-longer necessary items from VWM.
Meeting abstract presented at VSS 2016