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  Primary Visual Cortex as a Saliency Map: A Parameter-Free Prediction and Its Test by Behavioral Data

Zhe, L., & Zhaoping, L. (2015). Primary Visual Cortex as a Saliency Map: A Parameter-Free Prediction and Its Test by Behavioral Data. PLoS Computational Biology, 11(10), 1-39. doi:10.1371/journal.pcbi.1004375.

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Zhe, L, Author
Zhaoping, L1, Author           
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1External Organizations, ou_persistent22              

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 Abstract: It has been hypothesized that neural activities in the primary visual cortex (V1) represent a saliency map of the visual field to exogenously guide attention. This hypothesis has so far provided only qualitative predictions and their confirmations. We report this hypothesis’ first quantitative prediction, derived without free parameters, and its confirmation by human behavioral data. The hypothesis provides a direct link between V1 neural responses to a visual location and the saliency of that location to guide attention exogenously. In a visual input containing many bars, one of them saliently different from all the other bars which are identical to each other, saliency at the singleton’s location can be measured by the shortness of the reaction time in a visual search for singletons. The hypothesis predicts quantitatively the whole distribution of the reaction times to find a singleton unique in color, orientation, and motion direction from the reaction times to find other types of singletons. The prediction matches human reaction time data. A requirement for this successful prediction is a data-motivated assumption that V1 lacks neurons tuned simultaneously to color, orientation, and motion direction of visual inputs. Since evidence suggests that extrastriate cortices do have such neurons, we discuss the possibility that the extrastriate cortices play no role in guiding exogenous attention so that they can be devoted to other functions like visual decoding and endogenous attention.

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 Dates: 2015-10
 Publication Status: Published online
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 Identifiers: DOI: 10.1371/journal.pcbi.1004375
eDoc: e1004375
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 11 (10) Sequence Number: - Start / End Page: 1 - 39 Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1