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Modeling the tonotopic map using a two-dimensional array of neural oscillators.

Dipayan Biswas1, V Srinivasa Chakravarthy1, Asit Tarsode1,2

  • 1Laboratory for Computational Neuroscience, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.

Frontiers in Computational Neuroscience
|September 12, 2022
PubMed
Summary

We introduce the Oscillatory Tonotopic Self-Organizing Map (OTSOM), a novel model for auditory processing. This map uses coupled Hopf oscillators to achieve both frequency and phase tuning, mimicking mammalian auditory cortices.

Keywords:
Hopf oscillatorentrainmentinterferencemodified power couplingresonanceself-organizing mapsynchronizationtonotopy

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Area of Science:

  • Computational Neuroscience
  • Auditory Processing
  • Artificial Neural Networks

Background:

  • Tonotopic maps in the brain organize sound frequencies.
  • Existing models lack robust phase tuning mechanisms.
  • Hopf oscillators naturally exhibit frequency resonance.

Purpose of the Study:

  • To develop a novel computational model for tonotopic mapping.
  • To enable simultaneous frequency and phase tuning in an artificial map.
  • To approximate the tonotopic organization in mammalian auditory cortices.

Main Methods:

  • Utilizing a 2D array of Hopf oscillators.
  • Implementing a modified power coupling scheme for phase tuning.
  • Employing a two-stage training process for frequency and phase adaptation.

Main Results:

  • The Oscillatory Tonotopic Self-Organizing Map (OTSOM) demonstrates Fourier-like signal decomposition.
  • Achieved resonant frequency tuning emerges naturally from oscillator dynamics.
  • Successfully demonstrated phase tuning via modified power coupling.

Conclusions:

  • The OTSOM model provides a biologically plausible mechanism for auditory processing.
  • It offers a unified approach to frequency and phase representation.
  • The model serves as a potential approximation for mammalian auditory cortex tonotopy.