Dynamical characteristics common to neuronal competition models.

Dynamical characteristics common to neuronal competition models. Research Abstract Details 

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Dynamical characteristics common to neuronal competition models. Abstract Text:

Asya Shpiro,Rodica Curtu,John Rinzel,Nava Rubin,

Models implementing neuronal competition by reciprocally inhibitory populations are widely used to characterize bistable phenomena such as binocular rivalry. We find common dynamical behavior in several models of this general type, which differ in their architecture in the form of their gain functions, and in how they implement the slow process that underlies alternating dominance. We focus on examining the effect of the input strength on the rate (and existence) of oscillations. In spite of their differences, all considered models possess similar qualitative features, some of which we report here for the first time. Experimentally, dominance durations have been reported to decrease monotonically with increasing stimulus strength (such as Levelt's "Proposition IV"). The models predict this behavior; however, they also predict that at a lower range of input strength dominance durations increase with increasing stimulus strength. The nonmonotonic dependency of duration on stimulus strength is common to both deterministic and stochastic models. We conclude that additional experimental tests of Levelt's Proposition IV are needed to reconcile models and perception.

Dynamical characteristics common to neuronal competition models. Publishing Authors By Initials

A Shpiro,R Curtu,J Rinzel,N Rubin,

For similar vision, binocular research abstracts see: vision, binocular research

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Dynamical characteristics common to neuronal competition models. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Journal of neurophysiology

VOLUME: 97

Page Numbers: 462-73

Journal Abbreviation: J. Neurophysiol.

ISSN: 0022-3077

DAY: 25

MONTH: 10

YEAR: 2006

Dynamical characteristics common to neuronal competition models. Information

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LANGUAGE: eng

NlmUniqueID: 375404

Dynamical characteristics common to neuronal competition models. Keywords Mesh Terms:

KEYWORDS: Vision, Binocular

MESH TERMS: physiology

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Grant and Affiliation Information for Dynamical characteristics common to neuronal competition models.

AFFILIATION: Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003, USA. avs203@nyu.edu

Country: United States

AGENCY: United States NEI

GRANT: EY 14030

ACRONYM: EY

MEDLINETA: J Neurophysiol

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