Emergence of Neuronal Groups on a Self-Organized Spiking Neurons Network Based on Genetic Algorithm
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 ne...
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creator | Soares, G E Borges, H E Gomes, R M Oliveira, G M C |
description | 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. |
doi_str_mv | 10.1109/SBRN.2010.16 |
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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.</abstract><pub>IEEE</pub><doi>10.1109/SBRN.2010.16</doi><tpages>6</tpages></addata></record> |
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subjects | Artificial neural networks Biological system modeling Computational modeling Frequency synchronization genetic algorithm Mathematical model neural networks Neurons spiking neuron Wave functions |
title | Emergence of Neuronal Groups on a Self-Organized Spiking Neurons Network Based on Genetic Algorithm |
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