Information transfer with rate-modulated Poisson processes: a simple model for nonstationary stochastic resonance.
Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.
Goychuk
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Institute of Physics, University of Augsburg, Universitätsstrasse 1, D-86135 Augsburg, Germany.
D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002450:Cell Communication / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D007473:Ion Channels / Q000502:physiology*; D008959:Models, Neurological; D015233:Models, Statistical; D009475:Neurons, Afferent / Q000502:physiology*; D017711:Nonlinear Dynamics; D016012:Poisson Distribution; D015398:Signal Transduction / Q000502:physiology; D013269:Stochastic Processes; D009435:Synaptic Transmission / Q000502:physiology*; D013997:Time Factors
D007473:Ion Channels