A cortical filter that learns to suppress the acoustic consequences of movement

David M. Schneider, Janani Sundararajan and Richard Mooney ()
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David M. Schneider: Duke University School of Medicine
Janani Sundararajan: Duke University School of Medicine
Richard Mooney: Duke University School of Medicine

Nature, 2018, vol. 561, issue 7723, 391-395

Abstract: Abstract Sounds can arise from the environment and also predictably from many of our own movements, such as vocalizing, walking, or playing music. The capacity to anticipate these movement-related (reafferent) sounds and distinguish them from environmental sounds is essential for normal hearing1,2, but the neural circuits that learn to anticipate the often arbitrary and changeable sounds that result from our movements remain largely unknown. Here we developed an acoustic virtual reality (aVR) system in which a mouse learned to associate a novel sound with its locomotor movements, allowing us to identify the neural circuit mechanisms that learn to suppress reafferent sounds and to probe the behavioural consequences of this predictable sensorimotor experience. We found that aVR experience gradually and selectively suppressed auditory cortical responses to the reafferent frequency, in part by strengthening motor cortical activation of auditory cortical inhibitory neurons that respond to the reafferent tone. This plasticity is behaviourally adaptive, as aVR-experienced mice showed an enhanced ability to detect non-reafferent tones during movement. Together, these findings describe a dynamic sensory filter that involves motor cortical inputs to the auditory cortex that can be shaped by experience to selectively suppress the predictable acoustic consequences of movement.

Keywords: Acoustic Virtual Reality; Auditory Cortex; Inter-tone Interval; Holm-Bonferroni Method; Movement-related Inhibition (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1038/s41586-018-0520-5

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