Emergence of Neuronal Groups on a Self-Organized Spiking Neurons Network Based on Genetic Algorithm

Authors:
Gabriela E. Soares;Henrique E. Borges;Rogerio M. Gomes;Geraldo M. C. Oliveira
Affiliations:
-;-;-;-
Venue:
SBRN '10 Proceedings of the 2010 Eleventh Brazilian Symposium on Neural Networks
Year:
2010

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Emergence of synchronicity in a self-organizing spiking neuron network: an approach via genetic algorithms

Natural Computing: an international journal

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Abstract

Based on the Theory of Neuronal Group Selection (TNGS), proposed by Edelman, a network composed of one hundred Izhikevich spiking neurons is analyzed. In this study, a genetic algorithm is used to estimate the Izhikevich neuron model parameters in order to enable the self-organization of a neural network into a cluster of tightly coupled neural cells which fire and oscillate in synchrony at a predefined frequency.