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

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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Bibliographische Detailangaben
Hauptverfasser: Soares, G E, Borges, H E, Gomes, R M, Oliveira, G M C
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Artificial neural networks
Biological system modeling
Computational modeling
Frequency synchronization
genetic algorithm
Mathematical model
neural networks
Neurons
spiking neuron
Wave functions
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Beschreibung
Zusammenfassung: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.
ISSN:1522-4899
2375-0235
DOI:10.1109/SBRN.2010.16