Chirp sensitivity and vowel coding in the inferior colliculus

Abstract

The inferior colliculus (IC) is an important brain region to understand neural encoding of complex sounds due to its diverse sound-feature sensitivities, including features that are affected by peripheral nonlinearities. Recent physiological studies in rabbit IC demonstrate that IC neurons are sensitive to chirp direction and velocity. Fast spectrotemporal changes, known as chirps, are contained within pitch-periods of natural vowels. Here, we use a combination of physiological and modeling strategies to assess the impact of chirp-sensitivity on vowel coding. Neural responses to vowel stimuli were recorded and vowel-token identification was evaluated based on average-rate and spike-timing metrics. Response timing was found to result in higher identification accuracy than rate. Additionally, rate bias towards low-velocity chirps, independent of chirp direction, was shown to correlate with higher vowel-identification accuracy based on timing. Also, direction bias in response to chirps of high velocity was shown to correlate with vowel-identification accuracy based on both rate and timing. Responses to natural-vowel tokens of individual neurons were simulated using an IC model with controllable chirp sensitivity. Responses of upward-biased, downward-biased, and non-selective model neurons were generated. Manipulating chirp sensitivity influenced response profiles across natural vowel tokens and vowel discrimination based on model-neuron responses. More work is needed to match all features of model responses to those of physiological recordings.

Keywords: Auditory physiology; Computational model; Frequency sweeps; Rate-velocity functions.