A simple chaotic neuron model: stochastic behavior of neural networks.
We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relationship between EEG and neuron dynamics, as well as methods of signal analysis. We propose 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 chaotic behavior. The correlation of the EEG-like signals was.92, smaller than those reported by others. It was concluded that this neuron model may provide valuable clues about the dynamic behavior of neural systems.
Aydiner
Ekrem
E
Department of Physics, Faculty of Arts and Sciences, University of Cukurova, Adana, Turkey. ekol@cu.edu.tr
Vural
Adil M
AM
Ozcelik
Bekir
B
Kiymac
Kerim
K
Tan
Uner
U
D004569:Electroencephalography; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology