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eNeuroNeurosciencePeer-reviewed journal article

Contributions of distinct auditory cortical inhibitory neuron types to the detection of sounds in background noise

Anna A. LakuninaiD, Nadav MenasheiD, Santiago JaramilloiD

PDFDOIPreprint

Abstract

The ability to separate background noise from relevant acoustic signals is essential for appropriate sound-driven behavior in natural environments. Examples of this separation are apparent in the auditory system, where neural responses to behaviorally relevant stimuli become increasingly noise-invariant along the ascending auditory pathway. However, the mechanisms that underlie this reduction in responses to background noise are not well understood. To address this gap in knowledge, we first evaluated the effects of auditory cortical inactivation on mice of both sexes trained to perform a simple auditory signal-in-noise detection task, and found that outputs from the auditory cortex are important for the detection of auditory stimuli in noisy environments. Next, we evaluated the contributions of the two most common cortical inhibitory cell types, parvalbumin-expressing (PV+) and somatostatin-expressing (SOM+) interneurons, to the perception of masked auditory stimuli. We found that inactivation of either PV+ or SOM+ cells resulted in a reduction in the ability of mice to determine the presence of auditory stimuli masked by noise. These results indicate that a disruption of auditory cortical network dynamics by either of these two types of inhibitory cells is sufficient to impair the ability to separate acoustic signals from noise. Significance StatementAppropriate behavior in a natural environment relies on the ability to separate background noise from relevant signals. We found that auditory cortical inhibitory neurons play a causal role in separating environmental noise from behaviorally relevant auditory signals. These results advance our understanding of the computations performed by the auditory system to decompose and analyze acoustic stimuli in the presence of noise.

Citations
15
FWCI
1.55
Field percentile
top 19%

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