On the Formation of Persistent States in Neuronal Network Models of Feature Selectivity

Authors

Evan Haskell, University of UtahFollow
Paul C. Bressloff, University of Utah

Document Type

Article

Publication Date

6-1-2003

Publication Title

Journal of Integrative Neuroscience

Keywords

Neuronal dynamics, Feature selectivity, Persistent states, Working memory

ISSN

0219-6352

Volume

2

Issue/No.

1

First Page

103

Last Page

125

Abstract

We study the existence and stability of localized activity states in neuronal network models of feature selectivity with either a ring or spherical topology. We find that the neural field has mono-stable, bi-stable, and tri-stable regimes depending on the parameters of the weighting function. In the case of homogeneous inputs, these localized activity states are marginally stable with respect to rotations. The response of a stable equilibrium to an inhomogeneous input is also determined

NSUWorks Citation

Haskell, Evan and Bressloff, Paul C., "On the Formation of Persistent States in Neuronal Network Models of Feature Selectivity" (2003). Mathematics Faculty Articles. 88.
https://nsuworks.nova.edu/math_facarticles/88

DOI

10.1142/S0219635203000202