Phase equation for patterns of orientation selectivity in a neural field model of visual cortex
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Published version
Author(s)
Carroll, Samuel R
Bressloff, Paul C
Type
Journal Article
Abstract
In this paper we consider a neural field equation on LR2 × S1, which models the activity of populations of spatially organized, orientation selective neurons. In particular, we show how spatially
organized patterns of orientation tuning can emerge due to the presence of weak, long-range horizontal connections and how such patterns can be analyzed in terms of a reduced phase equation. The
latter is formally identical to the phase equation obtained in the study of weakly coupled oscillators,
except that now the spatially distributed phase represents the peak of an orientation tuning curve
(stationary pulse or bump on S1) of neural populations at different locations in R2. We then carry
out a detailed analysis of the existence and stability of various solutions to the phase equation and
show that the resulting spatially structured phase patterns are consistent with numerical simulations of the full neural field equations. In contrast to previous studies of neural field models of visual
cortex, we work in the strongly nonlinear regime.
organized patterns of orientation tuning can emerge due to the presence of weak, long-range horizontal connections and how such patterns can be analyzed in terms of a reduced phase equation. The
latter is formally identical to the phase equation obtained in the study of weakly coupled oscillators,
except that now the spatially distributed phase represents the peak of an orientation tuning curve
(stationary pulse or bump on S1) of neural populations at different locations in R2. We then carry
out a detailed analysis of the existence and stability of various solutions to the phase equation and
show that the resulting spatially structured phase patterns are consistent with numerical simulations of the full neural field equations. In contrast to previous studies of neural field models of visual
cortex, we work in the strongly nonlinear regime.
Date Issued
2016-01
Date Acceptance
2015-12-03
Citation
SIAM Journal on Applied Dynamical Systems, 2016, 15 (1), pp.60-83
ISSN
1536-0040
Publisher
Society for Industrial and Applied Mathematics
Start Page
60
End Page
83
Journal / Book Title
SIAM Journal on Applied Dynamical Systems
Volume
15
Issue
1
Copyright Statement
© 2016, Society for Industrial and Applied Mathematics.
Identifier
http://dx.doi.org/10.1137/15m1016758
Publication Status
Published
Date Publish Online
2016-01-20