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Temporal asymmetries in auditory coding and perception reflect multi-layered nonlinearities.

Thomas Deneux1, Alexandre Kempf1, Aurélie Daret1

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Summary
This summary is machine-generated.

Auditory cortex shows asymmetric responses to sound intensity changes, with stronger activity for increasing sounds. This neural asymmetry reflects how the brain processes sound

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Area of Science:

  • Neuroscience
  • Auditory Neuroscience
  • Computational Neuroscience

Background:

  • Sound recognition depends on both spectral and temporal acoustic features.
  • Perception of sounds is asymmetric, significantly impacted by temporal reversals.
  • Understanding the neural basis of auditory temporal processing is crucial.

Purpose of the Study:

  • To investigate the coding principles of auditory temporal asymmetries in the brain.
  • To explore how the auditory cortex represents sounds with different temporal structures.

Main Methods:

  • Recorded activity from a large population of auditory cortex neurons in awake mice using two-photon calcium imaging.
  • Presented sounds with intensity ramping up or down.
  • Analyzed cortical population responses and compared different computational models.

Main Results:

  • Observed clear asymmetries in auditory cortex population responses, with stronger neural activity for up-ramping sounds.
  • Identified spatially clustered neuronal ensembles that detect specific combinations of spectral and intensity modulation features.
  • Demonstrated that cortical responses arise from multi-layered nonlinearities, creating divergent representations for sounds with similar spectral but different temporal characteristics.

Conclusions:

  • The auditory cortex exhibits asymmetric neural processing reflecting perceptual saliency of sound intensity changes.
  • Auditory cortex utilizes a population code based on ensembles detecting complex spectro-temporal features.
  • Nonlinear processing in the auditory cortex generates distinct neural representations for sounds differing in temporal structure, challenging standard receptive field models.