PT  - JOURNAL ARTICLE
AU  - Alexander Lavin
AU  - J. Swaroop Guntupalli
AU  - Miguel Lázaro-Gredilla
AU  - Wolfgang Lehrach
AU  - Dileep George
TI  - Explaining Visual Cortex Phenomena using Recursive Cortical Network
AID  - 10.1101/380048
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 380048
4099  - http://biorxiv.org/content/early/2018/07/30/380048.short
4100  - http://biorxiv.org/content/early/2018/07/30/380048.full
AB  - The connectivity and information pathways of visual cortex are well studied, as are observed physiological phenomena, yet a cohesive model for explaining visual cortex processes remains an open problem. For a comprehensive understanding, we need to build models of the visual cortex that are capable of robust real-world performance, while also being able to explain psychophysical and physiological observations. To this end, we demonstrate how the Recursive Cortical Network (George et al., 2017) can be used as a computational model to reproduce and explain subjective contours, neon color spreading, occlusion vs. deletion, and the border-ownership competition phenomena observed in the visual cortex.