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Predictive coding as a model of biased competition in visual attention

期刊

VISION RESEARCH
卷 48, 期 12, 页码 1391-1408

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.visres.2008.03.009

关键词

neural networks; cortical circuits; cortical feedback; attention; binding problem

资金

  1. EPSRC [EP/D062225/1] Funding Source: UKRI
  2. Engineering and Physical Sciences Research Council [EP/D062225/1, GR/S81339/01] Funding Source: researchfish

向作者/读者索取更多资源

Attention acts, through cortical feedback pathways, to enhance the response of cells encoding expected or predicted information. Such observations are inconsistent with the predictive coding theory of cortical function which proposes that feedback acts to suppress information predicted by higher-level cortical regions. Despite this discrepancy, this article demonstrates that the predictive coding model can be used to simulate a number of the effects of attention. This is achieved via a simple mathematical rearrangement of the predictive coding model, which allows it to be interpreted as a form of biased competition model. Nonlinear extensions to the model are proposed that enable it to explain a wider range of data. (C) 2008 Elsevier Ltd. All Fights reserved.

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