Presentation	2010-03-09 Probabilistic Interpretation of Border-ownership Signals in Early Visual Cortex Haruo HOSOYA,
PDF Download Page	PDF download Page Link
Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	Several recent model studies of visual cortex have used Bayesian networks and their belief propagation algorithms, and successfiully explained various physiological properties. This paper shows that a similar model can also explain another property called border-ownership, one of contextual effects in early visual cortex reported by Zhou et al. We show that border-ownership signals can be interpreted as posterior joint probabilities of a low-level edge property and a high-level figure property, and can readily be found in a typical hierarchical Bayesian network mimicking early visual cortex, under certain conditions. We also present the result of a computer simulation that model neurons in our Bayesian network can reproduce response properties qualitatively similar to physiological data.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)
Paper #	NC2009-100
Date of Issue

Conference Information
Committee	NC
Conference Date	2010/3/2(1days)
Place (in Japanese)	(See Japanese page)
Place (in English)
Topics (in Japanese)	(See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To	Neurocomputing (NC)
Language	ENG
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Probabilistic Interpretation of Border-ownership Signals in Early Visual Cortex
Sub Title (in English)
Keyword(1)
1st Author's Name	Haruo HOSOYA
1st Author's Affiliation	Faculty of Science, The University of Tokyo()
Date	2010-03-09
Paper #	NC2009-100
Volume (vol)	vol.109
Number (no)	461
Page	pp.pp.-
#Pages	6
Date of Issue