Journal
VISION RESEARCH
Volume 116, Issue -, Pages 241-257Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.visres.2015.04.004
Keywords
Attention models; Biased competition; Scaling vs. sharpening of tuning curves; Contrast vs. response gain; Surround suppression
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Funding
- German Research Foundation [DFG HA2630/6-1, PAK 270/1, PAK 270/2]
- European Project FP7-NBIS Spatial Cognition [600785]
- Research Training Group Crossworlds [GRK1780]
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Computational models of visual attention have replicated a large number of data from visual attention experiments. However, typically each computational model has been shown to account for only a few data sets. We developed a novel model of attention, particularly focused on explaining single cell recordings in multiple brain areas, to better understand the underlying computational circuits of attention involved in spatial- and feature-based biased competition, modulation of the contrast response function, modulation of the neuronal tuning curve, and modulation of surround suppression. In contrast to previous models, we use a two layer structure inspired by the layered cortical architecture which implements amplification, divisive normalization and suppression as well as spatial pooling. (C) 2015 Elsevier Ltd. All rights reserved.
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