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Human-Like Modulation Sensitivity Emerging through Optimization to Natural Sound Recognition.

Takuya Koumura1, Hiroki Terashima2, Shigeto Furukawa2

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Summary
This summary is machine-generated.

Human auditory sensitivity to amplitude modulation (AM) likely evolved for natural sound recognition. A computational model optimized for sound recognition showed human-like AM sensitivity in higher layers, mirroring auditory brain regions.

Keywords:
auditorymodulationneural networkneurophysiologypsychophysicssound recognition

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Area of Science:

  • Auditory Neuroscience
  • Computational Auditory Processing
  • Psychoacoustics

Background:

  • Natural sounds possess complex amplitude modulation (AM) patterns crucial for auditory perception.
  • Human sensitivity to AM varies significantly with experimental conditions, lacking a unified explanation.
  • Understanding the neural basis of AM sensitivity is key to deciphering auditory processing.

Purpose of the Study:

  • To investigate the evolutionary and developmental origins of human AM sensitivity.
  • To explore the neural mechanisms underlying AM sensitivity using a computational model.
  • To bridge the gap between psychophysical AM sensitivity and neural representations.

Main Methods:

  • Developed a multilayer neural network optimized for natural sound recognition.
  • Simulated psychophysical experiments to assess AM sensitivity in the model.
  • Conducted simulated neurophysiological experiments to map model layers to auditory brain regions.

Main Results:

  • The model, optimized for natural AM statistics, exhibited human-like AM sensitivity in its higher layers.
  • AM sensitivity emerged in the model without explicit design for human-like perception.
  • Simulated neurophysiology revealed correspondences between model layers and auditory midbrain/higher regions.

Conclusions:

  • Human AM sensitivity is likely an emergent property optimized for natural sound recognition during evolution and/or development.
  • Neural firing rates in auditory midbrain and higher regions encode stimulus representations supporting AM sensitivity.
  • This study offers a computational framework linking behavioral and neural data in auditory processing.