Reevaluating the sensory recruitment model by manipulating crowding in visual working memory representations.

The prominent sensory recruitment model argues that visual working memory (WM) is maintained via representations in the same early visual cortex brain regions that initially encode sensory stimuli, either in the identical neural populations as perceptual representations or in distinct neural populations. While recent research seems to reject the former (strong) sensory recruitment model, the latter (flexible) account remains plausible. Moreover, this flexibility could explain a recent result of high theoretical impact (Harrison & Bays, The Journal of Neuroscience, 38 (12), 3116-3123, 2018) - a failure to observe interactions between items held in visual WM - that has been taken to reject the sensory recruitment model. Harrison and Bays (The Journal of Neuroscience, 38 (12), 3116-3123, 2018) tested the sensory recruitment model by comparing the precision of memoranda in radially and tangentially oriented memory arrays. Because perceptual visual crowding effects are greater in radial than tangential arrays, they reasoned that a failure to observe such anisotropy in WM would reject the sensory recruitment model. In the present Registered Report or Replication, we replicated their study with greater sensitivity and extended their task by controlling a potential strategic confound. Specifically, participants might remap memory items to new locations, reducing interactions between proximal memoranda. To combat remapping, we cued participants to report either a memory item or its precise location - with this report cue presented only after a memory maintenance period. Our results suggest that, similar to visual perceptual crowding, location-bound visual memoranda interact with one another when remapping is prevented. Thus, our results support at least a flexible form of the sensory recruitment model.

Feature-specificity in visual statistical summary processing.

Visual statistical summary processing enables people to extract the average feature of a set of items rapidly and accurately. Previous studies have demonstrated independent mechanisms for summarizing low (e.g. color, orientation) and high-level (facial identity, emotion) visual information. However, no study to date has conclusively determined whether there are feature-specific summarization mechanisms for low-level features or whether there are low-level, feature agnostic summarization mechanisms. To address this issue, we asked participants to report either the average orientation or the average size from a set of lines where both features varied. Participants completed these tasks either in single-task or mixed-task conditions; in the latter, successful performance required extraction of both summaries concurrently. If there were feature-specific summarization mechanisms that could operate in parallel, then errors in mean size and mean orientation tasks should be independent, in both single and mixed task conditions. On the other hand, a central domain-general mechanism for low-level summarization would imply a correlation between errors for both features and greater error in the mixed than single task trials. In Experiment 1, we found that there was no correlation between the mean size and mean orientation errors and performance was similar across single and mixed-task conditions, suggesting that there may be independent summarization mechanisms for size and orientation features. To further test the feature-specificity account, in Experiment 2 and 3 (with mask), we manipulated the display duration to determine whether there were any differences in the summarization of earlier (orientation) vs. later (size) features. While these experiments replicated the pattern of results observed in Experiment 1, at shorter display durations, no differences emerged across features. We argue that our data is consistent with independent, multi-level feature-specific statistical summary mechanisms for low-level visual features.