title: Derived patterns in binocular rivalry networks.
abstract: Binocular rivalry is the alternation in visual perception that can occur when the two eyes are presented with different images. Wilson proposed a class of neuronal network models that generalize rivalry to multiple competing patterns. The networks are assumed to have learned several patterns, and rivalry is identified with time periodic states that have periods of dominance of different patterns. Here, we show that these networks can also support patterns that were not learned, which we call derived. This is important because there is evidence for perception of derived patterns in the binocular rivalry experiments of Kovács, Papathomas, Yang, and Fehér. We construct modified Wilson networks for these experiments and use symmetry breaking to make predictions regarding states that a subject might perceive. Specifically, we modify the networks to include lateral coupling, which is inspired by the known structure of the primary visual cortex. The modified network models make expected the surprising outcomes observed in these experiments.
authors: Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43210, USA.
authors: Casey O
authors: CO
authors: Diekman
authors: Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43210, USA. mg@mbi.osu.edu.
authors: Martin
authors: M
authors: Golubitsky
authors: Department of Mathematics, Texas Southern University, Houston, TX, 77004, USA.
authors: Yunjiao
authors: Y
authors: Wang
references: Philos Trans R Soc Lond B Biol Sci. 2001 Mar 29;356(1407):299-330
references: 11316482
references: J Comput Neurosci. 2010 Jun;28(3):459-76
references: 20182782
references: Vision Res. 2007 Sep;47(21):2741-50
references: 17764714
references: Trends Cogn Sci. 2006 Nov;10(11):502-11
references: 16997612
references: J Neurophysiol. 2007 Jan;97(1):462-73
references: 17065254
references: Perception. 1980;9(2):223-31
references: 7375329
references: SIAM J Appl Dyn Syst. 2008;7(2):609-649
references: 20953287
references: Nat Rev Neurosci. 2002 Jan;3(1):13-21
references: 11823801
references: Vision Res. 2004 May;44(10):983-91
references: 15031091
references: Vision Res. 1992 Aug;32(8):1471-9
references: 1455720
references: Vis Neurosci. 1990 Jan;4(1):63-73
references: 2265146
references: Perception. 1988;17(2):215-28
references: 3067209
references: Nature. 2001 Aug 30;412(6850):907-10
references: 11528478
references: J Vis. 2007 Jun 21;7(8):10
references: 17685817
references: J Neurosci. 1992 Aug;12(8):3139-61
references: 1322982
references: J Neurophysiol. 2007 Sep;98(3):1125-39
references: 17615138
references: Biol Cybern. 1984;49(3):201-8
references: 6704442
references: J Neurophysiol. 2011 Nov;106(5):2136-50
references: 21775721
references: J Comput Neurosci. 2002 Jan-Feb;12(1):39-53
references: 11932559
references: Proc Natl Acad Sci U S A. 2003 Nov 25;100(24):14499-503
references: 14612564
references: Perception. 2000;29(12):1437-45
references: 11257967
references: Proc Natl Acad Sci U S A. 1996 Dec 24;93(26):15508-11
references: 8986842