September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Information Value Underlies Priority in Feature Based Attention
Author Affiliations
  • Phillip Witkowski
    University of California, Daivs
    Center for Mind and Brain, University of California, Davis
  • Joy Geng
    University of California, Daivs
    Center for Mind and Brain, University of California, Davis
Journal of Vision September 2021, Vol.21, 2318. doi:https://doi.org/10.1167/jov.21.9.2318
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      Phillip Witkowski, Joy Geng; Information Value Underlies Priority in Feature Based Attention. Journal of Vision 2021;21(9):2318. https://doi.org/10.1167/jov.21.9.2318.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Recent research on attentional templates suggests that representations of target items held in WM are not static representations of past stimuli, but dynamic representations that prioritize task-relevant information in the environment. However, complex environments may obfuscate which source of information is best to prioritize, meaning the visual system must make judgments about the predictability of information (information value) to efficiently allocate attention. How these these predictions are generated and how they relate to the allocation of attention are still poorly understood. To determine the relationship between information value and feature based attention, we designed an online search task for a target object defined by an orientation and color. At the start of each trial, participants (N=240) were cued with the most likely features of the target, but knew these features could change to any within a distribution of possible values. Target color was always sampled from a distribution with high uncertainty (SD=55), but the target orientation was drawn either low-variability (SD=10), medium-variability (SD=25), or high-variability (SD=40) distribution. A separate group of participants were allocated to a control condition each feature was drawn from identical t-distributions with low-variability (SD=10). Interleaved were 18 probe trials which asked participants to rate the likelihood of possible targets, gauging participants knowledge of the underlying feature distribution. Results showed that attention to each target target orientation was enhanced when its relative information value was high, while color was suppressed, mirroring participants knowledge of each feature distribution. Attention to either feature returned to baseline when the information values were approximately equal. These results point to a critical role of information value in feature based prioritization in the attentional template.

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