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

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 and discriminate these movement-related (reafferent) sounds from environmental sounds is critical to normal hearing(1,2), yet the neural circuits that learn to anticipate the often arbitrary and changeable sounds resulting 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 probe the behavioral consequences of this predictable sensorimotor experience. We found that aVR experience gradually and selectively suppresses 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 behaviorally adaptive, as aVR-experienced mice showed an enhanced ability to detect non-reafferent tones during movement. Together, these findings describe a dynamic sensory filter involving motor cortical inputs to the auditory cortex that can be shaped by experience to selectively suppress predictable acoustic consequences of movement.