A Simple Chaotic Neuron Model : Stochastic Behavior of Neural Networks
Statistical Mechanics
2007-05-23 v1 Disordered Systems and Neural Networks
q-bio
Abstract
We have shortly reviewed the occurrence of the post-synaptic potentials between neurons, the relation between EEG and neuron dynamics, as well as methods of signal analysis. We supposed a simple stochastic model representing electrical activity of neuronal systems. The model is constructed using the Monte Carlo simulation technique. The results yielded EEG-like signals with their phase portraits in three-dimensional space. The Lyapunov exponent was positive, indicating a chaotic behavior. The correlation dimension of the EEG-like signals was found to be .92, which was smaller than those reported by others. It was concluded that this neuron model may provide valuable clues about the dynamic behavior of neural systems.
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Cite
@article{arxiv.cond-mat/0211068,
title = {A Simple Chaotic Neuron Model : Stochastic Behavior of Neural Networks},
author = {Ekrem Aydiner and Adil M. Vural and Bekir Ozcelik and Kerim Kiymac and Uner Tan},
journal= {arXiv preprint arXiv:cond-mat/0211068},
year = {2007}
}
Comments
14 pages, 6 figures