Coding strategy for surface luminance switches in the primary visual cortex of the awake monkey

Yi Yang, Tian Wang, Yang Li, Weifeng Dai, Guanzhong Yang, Chuanliang Han, Yujie Wu and Dajun Xing ()
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Yi Yang: Beijing Normal University
Tian Wang: Beijing Normal University
Yang Li: Beijing Normal University
Weifeng Dai: Beijing Normal University
Guanzhong Yang: Beijing Normal University
Chuanliang Han: Beijing Normal University
Yujie Wu: Beijing Normal University
Dajun Xing: Beijing Normal University

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Both surface luminance and edge contrast of an object are essential features for object identification. However, cortical processing of surface luminance remains unclear. In this study, we aim to understand how the primary visual cortex (V1) processes surface luminance information across its different layers. We report that edge-driven responses are stronger than surface-driven responses in V1 input layers, but luminance information is coded more accurately by surface responses. In V1 output layers, the advantage of edge over surface responses increased eight times and luminance information was coded more accurately at edges. Further analysis of neural dynamics shows that such substantial changes for neural responses and luminance coding are mainly due to non-local cortical inhibition in V1’s output layers. Our results suggest that non-local cortical inhibition modulates the responses elicited by the surfaces and edges of objects, and that switching the coding strategy in V1 promotes efficient coding for luminance.

Date: 2022
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DOI: 10.1038/s41467-021-27892-3

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