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Mechanisms of Noise-Induced Improvement in Light-Intensity Encoding in Hermissenda Photoreceptor Network

Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah

Submitted 29 November 2006; accepted in final form 11 November 2007

In a companion paper we showed that random channel and synaptic noise improve the ability of a biologically realistic, GENESIS-based computational model of the Hermissenda eye to encode light intensity. In this paper we explore mechanisms for noise-induced improvement by examining contextual spike-timing relationships among neurons in the photoreceptor network. In other systems, synaptically connected pairs of spiking cells can develop phase-locked spike-timing relationships at particular, well-defined frequencies. Consequently, domains of stability (DOS) emerge in which an increase in the frequency of inhibitory postsynaptic potentials can paradoxically increase, rather than decrease, the firing rate of the postsynaptic cell. We have extended this analysis to examine DOS as a function of noise amplitude in the exclusively inhibitory Hermissenda photoreceptor network. In noise-free simulations, DOS emerge at particular firing frequencies of type B and type A photoreceptors, thus producing a nonmonotonic relationship between their firing rates and light intensity. By contrast, in the noise-added conditions, an increase in noise amplitude leads to an increase in the variance of the interspike interval distribution for a given cell; in turn, this blocks the emergence of phase locking and DOS. These noise-induced changes enable the eye to better perform one of its basic tasks: encoding light intensity. This effect is independent of stochastic resonance, which is often used to describe perithreshold stimuli. The constructive role of noise in biological signal processing has implications both for understanding the dynamics of the nervous system and for the design of neural interface devices.