Differential representation of spectral and temporal information by primary auditory cortex neurons in awake cats: Relevance to auditory scene analysis

Abstract

We investigated how the primary auditory cortex (AI) neurons encode the two major requisites for auditory scene analysis, i.e., spectral and temporal information. Single-unit activities in awake cats AI were studied by presenting 0.5-s-long tone bursts and click trains. First of all, the neurons ( n = 92) were classified into 3 types based on the time-course of excitatory responses to tone bursts: 1) phasic cells (P-cells; 26%), giving only transient responses; 2) tonic cells (T-cells; 34%), giving sustained responses with little or no adaptation; and 3) phasic-tonic cells (PT-cells; 40%), giving sustained responses with some tendency of adaptation. Other tone–response variables differed among cell types. For example, P-cells showed the shortest latency and smallest spiking jitter while T-cells had the sharpest frequency tuning. PT-cells generally fell in the intermediate between the two extremes. Click trains also revealed between-neuron-type differences for the emergent probability of excitatory responses (P-cells > PT-cells > T-cells) and their temporal features. For example, a substantial fraction of P-cells conducted stimulus-locking responses, but none of the T-cells did. f r -dependency characteristics of the stimulus locking resembled that reported for “comodulation masking release,” a behavioral model of auditory scene analysis. Each type neurons were omnipresent throughout the AI and none of them showed intrinsic oscillation. These findings suggest that: 1) T-cells preferentially encode spectral information with a rate-place code and 2) P-cells preferentially encode acoustic transients with a temporal code whereby rate-place coded information is potentially bound for scene analysis.