Comparison of auditory-vocal interactions across multiple types of vocalizations in marmoset auditory cortex

狨猴听觉皮层中多种发声类型下听觉-发声相互作用的比较

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Abstract

Auditory-vocal interaction, the modulation of auditory sensory responses during vocal production, is an important but poorly understood neurophysiological phenomenon in nonhuman primates. This sensory-motor processing has important behavioral implications for self-monitoring during vocal production as well as feedback-mediated vocal control for both animals and humans. Previous studies in marmosets have shown that a large portion of neurons in the auditory cortex are suppressed during self-produced vocalization but have primarily focused on a single type of isolation vocalization. The present study expands previous analyses to compare auditory-vocal interaction of cortical responses between different types of vocalizations. We recorded neurons from the auditory cortex of unrestrained marmoset monkeys with implanted electrode arrays and showed that auditory-vocal interactions generalize across vocalization types. We found the following: 1) Vocal suppression and excitation are a general phenomenon, occurring for all four major vocalization types. 2) Within individual neurons, suppression was the more general response, occurring for multiple vocalization types, while excitation tended to be more specific to a single vocalization type. 3) A subset of neurons changed their responses between different types of vocalization, most often from strong suppression or excitation for one vocalization to unresponsive for another, and only rarely from suppression to excitation. 4) Differences in neural responses between vocalization types were weakly correlated with passive response properties, measured by playbacks of acoustic stimuli including recorded vocalizations. These results indicate that vocalization-induced modulation of the auditory cortex is a general phenomenon applicable to all vocalization types, but variations within individual neurons suggest possible vocalization-specific coding.

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