Heteroclinic cycles in Hopfield networks
Dynamical Systems
2016-03-23 v1
Abstract
Learning or memory formation are associated with the strengthening of the synaptic connections between neurons according to a pattern reflected by the input. According to this theory a retained memory sequence is associated to a dynamic pattern of the associated neural circuit. In this work we consider a class of network neuron models, known as Hopfield networks, with a learning rule which consists of transforming an information string to a coupling pattern. Within this class of models we study dynamic patterns, known as robust heteroclinic cycles, and establish a tight connection between their existence and the structure of the coupling.
Keywords
Cite
@article{arxiv.1411.3909,
title = {Heteroclinic cycles in Hopfield networks},
author = {Pascal Chossat and Martin Krupa},
journal= {arXiv preprint arXiv:1411.3909},
year = {2016}
}