Dissociable roles of the auditory midbrain and cortex in processing the statistical features of natural sound textures

Abstract

AbstractIt is well established that sound texture perception takes advantage of a hierarchy of time-averaged statistical features of acoustic stimuli, but much remains unclear about how these statistical features are processed in auditory subcortical and cortical regions. Here, we compared the neural representation of sound textures in the inferior colliculus (IC), and primary and non-primary auditory cortex (AC) of anesthetized rats with texture morph stimuli which gradually add statistical features of increasingly higher order. We generated texture morphs for a representative subset of 13 sound textures, chosen to span the three principal component dimensions of a corpus of 200 natural texture recordings. For each of the 13 texture types, six different exemplar morphs were synthesized using different random seeds. All exemplars of each texture type have the same long term statistics, but they differ in their acoustic waveforms. Meanwhile, different texture types differ in statistical features as well as waveforms. An analysis of transient and ongoing multi-unit responses to our stimulus set showed that the IC units were sensitive to every type of statistical feature, albeit to a varying extent, but only a small proportion of AC units were overtly sensitive to any statistical features. Differences in texture types explained more of the variance of IC neural responses than did differences in exemplars, indicating a degree of “texture-type tuning” in the IC, but this was, perhaps surprisingly, not the case for AC responses. We also evaluated the accuracy of texture type classification from single-trial population activity and found that IC responses became more informative as more summary statistics were included in the texture morphs, while for AC population responses classification performance remained constant, and consistently lower, than for the IC. These results argue against the idea that AC plays an important role in encoding statistical features of natural sound textures.