Neural Comput - Information transfer through stochastic transmission of a linear combination of rates.

Tópicos

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Resumo

In this work, the Shannon information transfer rate due to the transmission of a linear combination of the firing rates of a number of afferent neurons is examined. The transmission of this linear combination (transfer statistic) takes place through a stochastic firing process, while a rate code is assumed. Constraints are imposed on the transmission process by the requirement that the coefficient of variation for the transfer statistic is small and by the relative variance of the individual terms in the calculation of the statistic. In the regime of no noise or signal correlations among the input neurons, simulations suggest that information transfer for fixed overall input is favored when there are few high-firing neurons, as opposed to more lower-firing neurons. Signal correlations among low-firing neurons can result in aggregates of high firing rates, improving in this way information transfer and calculational robustness. Under reasonable rate code assumptions, information transfer rates obtained are of the order 3 to 10 bit/sec.

Resumo Limpo

work shannon inform transfer rate due transmiss linear combin fire rate number affer neuron examin transmiss linear combin transfer statist take place stochast fire process rate code assum constraint impos transmiss process requir coeffici variat transfer statist small relat varianc individu term calcul statist regim nois signal correl among input neuron simul suggest inform transfer fix overal input favor highfir neuron oppos lowerfir neuron signal correl among lowfir neuron can result aggreg high fire rate improv way inform transfer calcul robust reason rate code assumpt inform transfer rate obtain order bitsec

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