Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes

Investigating the physiological mechanisms in the motor cortex during rehabilitation exercises is crucial for assessing stroke patients' progress. This study developed a single-channel Jansen neural mass model to explore the relationship between model parameters and motor cortex mechanisms. Firstly, EEG signals were recorded from 11 healthy participants under 20%, 40%, and 60% maximum voluntary contraction, and alpha rhythm power spectral density characteristics were extracted using the Welch power spectrum method. Furthermore, a single-channel neural mass model was constructed to analyze the impact of parameter variations on the average power of simulated signals. Finally, model parameters were adjusted to achieve feature fitting between the simulated signals and the average power of the alpha rhythm. Results showed that alpha rhythm average power in the contralateral cortical regions increased with higher grip force levels. Similarly, the power of the simulated signals also increased with specific parameter (<i>J</i>, <i>Ge</i>, and <i>Gi</i>) increases, closely approximating the measured EEG signal changes. The findings suggest that increasing grip force activates more motor neurons in the motor cortex and raises their firing rate. Neural mass modeling provides a computational neuroscience approach to understanding the dynamic changes in alpha rhythms in the motor cortex under different grip force levels.

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Publication Details

Journal
Sensors
Published
2024-12-25
DOI
https://doi.org/10.3390/s25010056
Citations
4
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.37

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article

Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes

Penghu Wei, Yuanyuan Zhang, Guoguang Zhao, Ping Xie et al.
4 citations
Sensors
EEG and Brain-Computer Interfaces
1.37
article

Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes

Penghu Wei, Yuanyuan Zhang, Guoguang Zhao, Ping Xie, Hang Xu, Zhaoying Li, Ziang Song
article en
4 citations

Abstract

Investigating the physiological mechanisms in the motor cortex during rehabilitation exercises is crucial for assessing stroke patients' progress. This study developed a single-channel Jansen neural mass model to explore the relationship between model parameters and motor cortex mechanisms. Firstly, EEG signals were recorded from 11 healthy participants under 20%, 40%, and 60% maximum voluntary contraction, and alpha rhythm power spectral density characteristics were extracted using the Welch power spectrum method. Furthermore, a single-channel neural mass model was constructed to analyze the impact of parameter variations on the average power of simulated signals. Finally, model parameters were adjusted to achieve feature fitting between the simulated signals and the average power of the alpha rhythm. Results showed that alpha rhythm average power in the contralateral cortical regions increased with higher grip force levels. Similarly, the power of the simulated signals also increased with specific parameter (<i>J</i>, <i>Ge</i>, and <i>Gi</i>) increases, closely approximating the measured EEG signal changes. The findings suggest that increasing grip force activates more motor neurons in the motor cortex and raises their firing rate. Neural mass modeling provides a computational neuroscience approach to understanding the dynamic changes in alpha rhythms in the motor cortex under different grip force levels.

SensorsVol. 25(1)
Capital Medical University (CN), Yanshan University (CN)
Beijing Municipal Science and Technology Commission
Good health and well-being
Openalex Percentile: Top 18%
EEG and Brain-Computer Interfaces
1.37
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