Instabilities in attractor networks with fast synaptic fluctuations and partial updating of the neurons activity

Authors:
J. J. Torres;J. Marro;J. M. Cortes;B. Wemmenhove
Affiliations:
Institute "Carlos I" for Theoretical and Computational Physics, and Departamento de Electromagnetismo y Física de la Materia, Universidad de Granada, E-18071, Granada, Spain;Institute "Carlos I" for Theoretical and Computational Physics, and Departamento de Electromagnetismo y Física de la Materia, Universidad de Granada, E-18071, Granada, Spain;Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, EH1 2QL, UK;Department of Biophysics and SNN, Radboud University, 6525 EZ Nijmegen, The Netherlands
Venue:
Neural Networks
Year:
2008

Citing 6
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Abstract

We present and study a probabilistic neural automaton in which the fraction of simultaneously-updated neurons is a parameter, @r@?(0,1). For small @r, there is relaxation towards one of the attractors and a great sensibility to external stimuli and, for @r=@r"c, itinerancy among attractors. Tuning @r in this regime, oscillations may abruptly change from regular to chaotic and vice versa, which allows one to control the efficiency of the searching process. We argue on the similarity of the model behavior with recent observations, and on the possible role of chaos in neurobiology.