Expectation of self-generated sounds drives predictive processing in mouse auditory cortex

Behavior exerts a strong influence over sensory responses in the brain. In the auditory cortex, neural responses to self-generated sounds are suppressed, suggesting that prediction may play a critical role in local sensory processing. However, it is unclear whether this phenomenon derives from a pre...

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Veröffentlicht in:The Journal of the Acoustical Society of America 2021-10, Vol.150 (4), p.A106-A106
Hauptverfasser: Schneider, David, Audette, Nicholas, Zhou, WenXi
Format: Artikel
Sprache:eng
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Zusammenfassung:Behavior exerts a strong influence over sensory responses in the brain. In the auditory cortex, neural responses to self-generated sounds are suppressed, suggesting that prediction may play a critical role in local sensory processing. However, it is unclear whether this phenomenon derives from a precise movement-based prediction or how it affects the neural representation of incoming stimuli. We address these questions by designing a behavioral paradigm where mice learn to expect the predictable acoustic consequences of a simple forelimb movement. Dense neuronal recordings from auditory cortex revealed suppression of neural responses that was strongest for the expected tone during a narrow time window surrounding the specific sound-associated movement. Predictive suppression was concentrated in layers 2/3 and 5, preceded by the arrival of movement information in deep layers, and driven by motor-sensory coupling rather than task engagement, behavioral relevance, or reward association. Despite large-scale suppression at the population level, the auditory cortex retained a sparse representation of the expected self-generated sounds, while a substantial population of auditory cortex neurons in L2/3 and L5 encoded prediction errors. These findings illustrate that expectation, learned through motor-sensory experience, drives layer-specific predictive processing in the mouse auditory cortex.
ISSN:0001-4966
1520-8524
DOI:10.1121/10.0007779