Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS
The electroencephalogram (EEG) rhythm and functional near-infrared spectroscopy (fNIRS) activation levels have not been compared between a healthy control group (HCG) and methamphetamine user group (MUG) with different addiction histories. This study used 64-electrode EEG and fNIRS to conduct an exp...
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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2024-05-01
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| Series: | Journal of Innovative Optical Health Sciences |
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| Online Access: | https://www.worldscientific.com/doi/10.1142/S1793545823500293 |
| _version_ | 1827289528440717312 |
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| author | Xuelin Gu Xiaoou Li Banghua Yang |
| author_facet | Xuelin Gu Xiaoou Li Banghua Yang |
| author_sort | Xuelin Gu |
| collection | DOAJ |
| description | The electroencephalogram (EEG) rhythm and functional near-infrared spectroscopy (fNIRS) activation levels have not been compared between a healthy control group (HCG) and methamphetamine user group (MUG) with different addiction histories. This study used 64-electrode EEG and fNIRS to conduct an experiment that analyzed the resting and craving states. The EEG and fNIRS data of 56 participants were collected, including 14 healthy participants, 14 methamphetamine users with an addiction history of 0.5–5 years, 14 users with an addiction history of 5–10 years, and 14 users with an addiction history of 10–15 years. Isolated effective coherence (iCoh) within the brain network was used to process the EEG data. Statistical analysis was performed to compare differences in iCoh among the delta, theta, alpha, beta, and gamma bands and explore oxyhemoglobin activation levels in the ventrolateral prefrontal cortex, dorsolateral prefrontal cortex, orbitofrontal cortex, and frontopolar prefrontal cortex (FPC) of the control group. Finally, the Kmeans, Gaussian mixed model (GMM), linear discriminant analysis (LDA), support vector machine (SVM), Bayes, and convolutional neural networks (CNN) algorithms were used to classify methamphetamine users based on drug and neutral images. A 3-class accuracy was achieved. Changes in EEG and fNIRS activation levels of HCG and MUG with varied addiction histories were demonstrated. |
| first_indexed | 2024-04-24T11:52:06Z |
| format | Article |
| id | doaj.art-43aeeff3c82f4db3978ff62685f79fed |
| institution | Directory Open Access Journal |
| issn | 1793-5458 1793-7205 |
| language | English |
| last_indexed | 2024-04-24T11:52:06Z |
| publishDate | 2024-05-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | Journal of Innovative Optical Health Sciences |
| spelling | doaj.art-43aeeff3c82f4db3978ff62685f79fed2024-04-09T07:13:16ZengWorld Scientific PublishingJournal of Innovative Optical Health Sciences1793-54581793-72052024-05-01170310.1142/S1793545823500293Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRSXuelin Gu0Xiaoou Li1Banghua Yang2College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, P. R. ChinaCollege of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai 201318, P. R. ChinaSchool of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai 200444, P. R. ChinaThe electroencephalogram (EEG) rhythm and functional near-infrared spectroscopy (fNIRS) activation levels have not been compared between a healthy control group (HCG) and methamphetamine user group (MUG) with different addiction histories. This study used 64-electrode EEG and fNIRS to conduct an experiment that analyzed the resting and craving states. The EEG and fNIRS data of 56 participants were collected, including 14 healthy participants, 14 methamphetamine users with an addiction history of 0.5–5 years, 14 users with an addiction history of 5–10 years, and 14 users with an addiction history of 10–15 years. Isolated effective coherence (iCoh) within the brain network was used to process the EEG data. Statistical analysis was performed to compare differences in iCoh among the delta, theta, alpha, beta, and gamma bands and explore oxyhemoglobin activation levels in the ventrolateral prefrontal cortex, dorsolateral prefrontal cortex, orbitofrontal cortex, and frontopolar prefrontal cortex (FPC) of the control group. Finally, the Kmeans, Gaussian mixed model (GMM), linear discriminant analysis (LDA), support vector machine (SVM), Bayes, and convolutional neural networks (CNN) algorithms were used to classify methamphetamine users based on drug and neutral images. A 3-class accuracy was achieved. Changes in EEG and fNIRS activation levels of HCG and MUG with varied addiction histories were demonstrated.https://www.worldscientific.com/doi/10.1142/S1793545823500293Drug addiction historyelectroencephalogramfunctional near-infrared spectroscopyisolated effective coherenceaddiction history classification |
| spellingShingle | Xuelin Gu Xiaoou Li Banghua Yang Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS Journal of Innovative Optical Health Sciences Drug addiction history electroencephalogram functional near-infrared spectroscopy isolated effective coherence addiction history classification |
| title | Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS |
| title_full | Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS |
| title_fullStr | Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS |
| title_full_unstemmed | Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS |
| title_short | Comparison of brain functions between healthy participants and methamphetamine users with various addiction histories: Data analysis based on EEG and fNIRS |
| title_sort | comparison of brain functions between healthy participants and methamphetamine users with various addiction histories data analysis based on eeg and fnirs |
| topic | Drug addiction history electroencephalogram functional near-infrared spectroscopy isolated effective coherence addiction history classification |
| url | https://www.worldscientific.com/doi/10.1142/S1793545823500293 |
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