document: On optimality in auditory information processing We study limits for the detection and estimation of weak sinusoidal signals in the primary part of the mammalian auditory system using a stochastic Fitzhugh-Nagumo model and an action-recovery model for synaptic depression . Our overall model covers the chain from a hair cell to a point just after the synaptic connection with a cell in the cochlear nucleus . The information processing performance of the system is evaluated using so-called phi - divergences from statistics that quantify `` dissimilarity '' between probability measures and are intimately related to a number of fundamental limits in statistics and information theory -LRB- IT -RRB- . We show that there exists a set of parameters that can optimize several important phi - divergences simultaneously and that this set corresponds to a constant quiescent firing rate -LRB- QFR -RRB- of the spiral ganglion neuron . The optimal value of the QFR is frequency dependent but is essentially independent of the amplitude of the signal -LRB- for small amplitudes -RRB- . Consequently , optimal processing according to several standard IT criteria can be accomplished for this model if and only if the parameters are `` tuned '' to values that correspond to one and the same QFR . This offers a new explanation for the QFR and can provide new insight into the role played by several other parameters of the peripheral auditory system
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