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JOURNALS // Regular and Chaotic Dynamics // Archive

Regul. Chaotic Dyn., 2016 Volume 21, Issue 1, Pages 97–106 (Mi rcd68)

This article is cited in 6 papers

Synchronization of Heteroclinic Circuits through Learning in Coupled Neural Networks

Anton Selskiia, Valeri A. Makarovab

a N.I. Lobachevsky State University of Nizhny Novgorod, ul. Gagarina 23, Nizhny Novgorod, 603950, Russia
b Instituto de Matemática Interdiciplinar, F. CC. Matemáticas, Universidad Complutense de Madrid, Madrid, 28040, Spain

Abstract: The synchronization of oscillatory activity in neural networks is usually implemented by coupling the state variables describing neuronal dynamics. Here we study another, but complementary mechanism based on a learning process with memory. A driver network, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven network, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner can “copy” the coupling structure and thus synchronize oscillations with the teacher. The replication of the WLC dynamics occurs for intermediate memory lengths only, consequently, the learner network exhibits a phenomenon of learning resonance.

Keywords: synchronization, learning, heteroclinic circuit, neural networks, winner-less competition.

MSC: 34C15, 37C29, 92B20, 92B25

Received: 25.08.2015
Accepted: 01.09.2015

Language: English

DOI: 10.1134/S1560354716010056



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