Information transmission in multi-input-output stochastic neuron models.

M Tsukada; K Obara; R Sato

doi:10.1007/bf00365476

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Information transmission in multi-input-output stochastic neuron models.

M Tsukada·K Obara·R Sato

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Abstract

The Shannon's information theory in multi-way channels (Shannon, 1961) is applied to multi-input-output relations of the stochastic automaton models for interaction of excitatory and inhibitory impulse sequences proposed in the previous papers (Tsukada et al., 1977). In these models, the output spike train depends upon several statistical characteristics (mean frequency, standard deviation, form, order-dependence or order-independence, etc.) of the excitatory and inhibitory input spike trains. By the use of the multiple-access channel in information theory, some stochastic properties of temporal pattern discrimination in neurons are analyzed and discussed with biological systems.

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Action Potentials Humans Models, Neurological Neural Inhibition Neurons Stochastic Processes Synaptic Transmission Journal Article

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M Tsukada, K Obara, R Sato. 1979. Information transmission in multi-input-output stochastic neuron models.. https://doi.org/10.1007/bf00365476

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