Information theory quantifies the ultimate limits on reliable information transfer by means of the channel capacity. However, the channel capacity is known to be an asymptotic quantity, assuming unlimited metabolic cost and computational power. We investigate a single-compartment Hodgkin-Huxley type neuronal model under the spike-rate coding scheme and address how the metabolic cost and the decoding complexity affects the optimal information transmission. We find that the sub-threshold stimulation regime, although attaining the smallest capacity, allows for the most efficient balance between the information transmission and the metabolic cost. Furthermore, we determine post-synaptic firing rate histograms that are optimal from the information-theoretic point of view, which enables the comparison of our results with experimental data.

Institute of Physiology of the Czech Academy of Sciences Videnska 1083 14220 Prague 4 Czech Republic

Principles of Informatics Research Division National Institute of Informatics 2 1 2 Hitotsubashi Chiyoda ku Tokyo Japan; Department of Informatics Graduate University for Advanced Studies 2 1 2 Hitotsubashi Chiyoda ku Tokyo Japan

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