4.3 Article

Cross-fixation interactions of orientations suggest high-to-low-level decoding in visual working memory

期刊

VISION RESEARCH
卷 190, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.visres.2021.107963

关键词

Visual decoding; Perceptual bias; Memory noise; Retrospective Bayesian

资金

  1. NSF [1754211]
  2. AFOSR [FA9550-15-1-0439]
  3. Irving Weinstein Foundation Inc.
  4. Division Of Behavioral and Cognitive Sci
  5. Direct For Social, Behav & Economic Scie [1754211] Funding Source: National Science Foundation

向作者/读者索取更多资源

Sensory encoding progresses from low- to high-level features, while decoding of sensory responses is less understood but is assumed to follow the same hierarchy. A study found evidence against the assumption and suggested that visual decoding may often follow a high-to-low-level hierarchy, with higher-level constraints introducing interactions among lower-level features.
Sensory encoding (how stimuli evoke sensory responses) is known to progress from low- to high-level features. Decoding (how responses lead to perception) is less understood but is often assumed to follow the same hierarchy. Accordingly, orientation decoding must occur in low-level areas such as V1, without cross-fixation interactions. However, a study, Ding, Cueva, Tsodyks, and Qian (2017), provided evidence against the assumption and proposed that visual decoding may often follow a high-to-low-level hierarchy in working memory, where higher-to-lower-level constraints introduce interactions among lower-level features. If two orientations on opposite sides of the fixation are both task relevant and enter working memory, then they should interact with each other. We indeed found the predicted cross-fixation interactions (repulsion and correlation) between orientations. Control experiments and analyses ruled out alternative explanations such as reporting bias and adaptation across trials on the same side of the fixation. Moreover, we explained the data using a retrospective high-to-low-level Bayesian decoding framework.

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