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,...
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| Format: | Article |
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| author | Yuanyuan Zhang Zhaoying Li Hang Xu Ziang Song Ping Xie Penghu Wei Guoguang Zhao |
| author_facet | Yuanyuan Zhang Zhaoying Li Hang Xu Ziang Song Ping Xie Penghu Wei Guoguang Zhao |
| author_sort | Yuanyuan Zhang |
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| description | 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. |
| format | Article |
| id | doaj-art-d24bc8acf4be4dca8006db9940fcaf02 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-d24bc8acf4be4dca8006db9940fcaf022025-01-10T13:20:43ZengMDPI AGSensors1424-82202024-12-012515610.3390/s25010056Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm ChangesYuanyuan Zhang0Zhaoying Li1Hang Xu2Ziang Song3Ping Xie4Penghu Wei5Guoguang Zhao6Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, ChinaDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, ChinaDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, ChinaDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, ChinaKey Laboratory of Measurement Technology and Instrumentation of Hebei Province, Institute of Electric Engineering, Yanshan University, Qinhuangdao 066004, ChinaDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, ChinaDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, ChinaInvestigating 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.https://www.mdpi.com/1424-8220/25/1/56static grip forcecortical motor areaneural mass modelalpha rhythm |
| spellingShingle | Yuanyuan Zhang Zhaoying Li Hang Xu Ziang Song Ping Xie Penghu Wei Guoguang Zhao Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes Sensors static grip force cortical motor area neural mass model alpha rhythm |
| title | Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes |
| title_full | Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes |
| title_fullStr | Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes |
| title_full_unstemmed | Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes |
| title_short | Neural Mass Modeling in the Cortical Motor Area and the Mechanism of Alpha Rhythm Changes |
| title_sort | neural mass modeling in the cortical motor area and the mechanism of alpha rhythm changes |
| topic | static grip force cortical motor area neural mass model alpha rhythm |
| url | https://www.mdpi.com/1424-8220/25/1/56 |
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