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The present article aims to analyze the propagation of a travelling wave across the surface of the human cerebral cortex during stimulation of the median nerve. The main objectives of the work are to determine the location of the epicentre of wave propagation and its speed under the hypothesis of directional variations in the excitation and inhibition parameters. In this study, we use an Amari-type mathematical model as the base of our parameters reconstruction approach. We consider the speed of a travelling wave to vary depending on the direction of propagation. We integrate the model with an anatomical representation of the cortex derived by magnetic resonance imaging to reconstruct the wave that corresponds to experimental magnetoencephalography (MEG) data. We also evaluate the difference between the reconstructed wave and the real MEG measurements. This paper introduces a method to address this issue and explores its implications for understanding brain function.

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On Reconstruction of Cortical Traveling Wave Parameters from MEG Data Using Neural Field Equations with Directionally Variable Excitation and Inhibition Parameters

  • 会议论文

  • 发表日期：

    2026年

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  • Ivan Malkov,
  • Evgenii Burlakov,
  • Vitaly Verkhlyutov,
  • Vadim Ushakov

摘要

The present article aims to analyze the propagation of a travelling wave across the surface of the human cerebral cortex during stimulation of the median nerve. The main objectives of the work are to determine the location of the epicentre of wave propagation and its speed under the hypothesis of directional variations in the excitation and inhibition parameters. In this study, we use an Amari-type mathematical model as the base of our parameters reconstruction approach. We consider the speed of a travelling wave to vary depending on the direction of propagation. We integrate the model with an anatomical representation of the cortex derived by magnetic resonance imaging to reconstruct the wave that corresponds to experimental magnetoencephalography (MEG) data. We also evaluate the difference between the reconstructed wave and the real MEG measurements. This paper introduces a method to address this issue and explores its implications for understanding brain function.