Emergence of synchronicity in a self-organizing spiking neuron network: an approach via genetic algorithms |
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Authors: | Gabriela E Soares Henrique E Borges Rogério M Gomes Gustavo M Zeferino Ant?nio P Braga |
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Affiliation: | 1. Laborat??rio de Sistemas Inteligentes??LSI-CEFET-MG, Av. Amazonas 7675, CEP 30.510-000, Belo Horizonte, MG, Brazil 2. Universidade Federal de Minas Gerais, Av. Ant?nio Carlos 6627, CEP 31270-010, Belo Horizonte, MG, Brazil
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Abstract: | Based on the Theory of Neuronal Group Selection (TNGS), we have investigated the emergence of synchronicity in a network composed of spiking neurons via genetic algorithm. The TNGS establishes that a neuronal group is the most basic unit in the cortical area of the brain and, as a rule, it is not formed by a single neuron, but by a cluster of tightly coupled neural cells which fire and oscillate in synchrony at a predefined frequency. Thus, this paper describes a method of tuning the parameters of the Izhikevich spiking neuron model through genetic algorithm in order to enable the self-organization of the neural network. Computational experiments were performed considering a network composed of neurons of the same type and another composed of neurons of different types. |
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