More target features in visual working memory leads to poorer search guidance: Evidence from contralateral delay activity

Abstract

The visual-search literature has assumed that the top-down target representation used to guide search resides in visual working memory (VWM). We directly tested this assumption using contralateral delay activity (CDA) to estimate the VWM load imposed by the target representation. In Experiment 1, observers previewed four photorealistic objects and were cued to remember the two objects appearing to the left or right of central fixation; Experiment 2 was identical except that observers previewed two photorealistic objects and were cued to remember one. CDA was measured during a delay following preview offset but before onset of a four-object search array. One of the targets was always present, and observers were asked to make an eye movement to it and press a button. We found lower magnitude CDA on trials when the initial search saccade was directed to the target (strong guidance) compared to when it was not (weak guidance). This difference also tended to be larger shortly before search-display onset and was largely unaffected by VWM item-capacity limits or number of previews. Moreover, the difference between mean strong- and weak-guidance CDA was proportional to the increase in search time between mean strong-and weak-guidance trials (as measured by time-to-target and reaction-time difference scores). Contrary to most search models, our data suggest that trials resulting in the maintenance of more target features results in poor search guidance to a target. We interpret these counterintuitive findings as evidence for strong search guidance using a small set of highly discriminative target features that remain after pruning from a larger set of features, with the load imposed on VWM varying with this feature-consolidation process.

The contralateral delay activity as a neural measure of visual working memory

“…It was shown that when a new target is presented it is being held in VWM but then gradually moves to LTM. This hand-off between VWM and LTM leads to better search efficiency, so that as the CDA amplitude decreased (indicating less involvement of VWM) search RT improved (Carlisle et al, 2011; Schmidt et al, 2014; Woodman and Arita, 2011). The hand-off between VWM and LTM did not depend on the target complexity level, but when the target was associated with a high reward, VWM continued to represent the target, indicating a more controlled search in high reward conditions (Gunseli et al, 2014a,b; Reinhart and Woodman, 2014).…”

The what, where, and why of priority maps and their interactions with visual working memory

“…This relationship is clearest in the case of the large and growing literature on feature templates that are maintained in VWM and used to guide behavior, and the brain mechanisms engaged in this maintenance . These templates are thought to be neural representations of goal states that can be used to mediate a variety of tasks, with change detection and visual search being among the most commonly studied . In the case of search, a VWM representation of a search target is compared to incoming visual information for the purpose of creating a target map.…”

“…Complex actions certainly emerge from highly dynamic systems, but even seemingly static target goals likely emerge from the dynamic weighting of features allowing expected targets to be discriminated from expected distractors. In this sense, the target of a search task is not a static entity or “template,” but rather a goal state that emerges over time …”

Searching for Category-Consistent Features

“…The logic underlying this prediction is straightforward. To the extent that CCFs are the important features in the representation of a category, more CCFs mean a better and more specific category representation (see also Schmidt, MacNamara, Proudfit, & Zelinsky, 2014). A target category having a larger number of CCFs would therefore be represented with a higher degree of specificity and, consequently, fixated more efficiently than a target having a sparser “template” (Schmidt & Zelinsky, 2009).…”