Selectivity to acoustic features of human speech in the auditory cortex of the mouse

A better understanding of the neural mechanisms of speech processing can have a major impact in the development of strategies for language learning and in addressing disorders that affect speech comprehension. Technical limitations in research with human subjects hinder a comprehensive exploration of these processes, making animal models essential for advancing the characterization of how neural circuits make speech perception possible. Here, we investigated the mouse as a model organism for studying speech processing and explored whether distinct regions of the mouse auditory cortex are sensitive to specific acoustic features of speech. We found that mice can learn to categorize frequency-shifted human speech sounds based on differences in formant transitions (FT) and voice onset time (VOT). Moreover, neurons across various auditory cortical regions were selective to these speech features, with a higher proportion of speech-selective neurons in the dorso-posterior region. Last, many of these neurons displayed mixed-selectivity for both features, an attribute that was most common in dorsal regions of the auditory cortex. Our results demonstrate that the mouse serves as a valuable model for studying the detailed mechanisms of speech feature encoding and neural plasticity during speech-sound learning.