The Contribution of Spike Threshold to Acoustic Feature Selectivity, Spike Information Content, and Information Throughput

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Abstract
Hypotheses of sensory coding range from the notion of nonlinear “feature detectors” to linear rate coding strategies. Here, we report that auditory neurons exhibit a novel trade-off in the relationship between sound selectivity and the information that can be communicated to a postsynaptic cell. Recordings from the cat inferior colliculus show that neurons with the lowest spike rates reliably signal the occurrence of stereotyped stimulus features, whereas those with high response rates exhibit lower selectivity. The highest information conveyed by individual action potentials comes from neurons with low spike rate and high selectivity. Surprisingly, spike information is inversely related to spike rates, following a trend similar to that of feature selectivity. Information per time interval, however, was proportional to measured spike rates. A neuronal model based on the spike threshold of the synaptic drive accurately accounts for this trade-off: higher thresholds enhance the spiking fidelity at the expense of limiting the total communicated information. Such a constraint on the specificity and throughput creates a continuum in the neural code with two extreme forms of information transfer that likely serve complementary roles in the representation of the auditory environment.