Optimizing electrode configurations for EEG mild cognitive impairment detection
Abstract The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the opti...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-024-84277-4 |
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| author | Yi Jiang Xin Zhang Zhiwei Guo Xiaobo Zhou Jiayuan He Ning Jiang |
| author_facet | Yi Jiang Xin Zhang Zhiwei Guo Xiaobo Zhou Jiayuan He Ning Jiang |
| author_sort | Yi Jiang |
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| description | Abstract The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM coding stage, six different electrode configurations were obtained: (1) four electrodes in the occipital lobe (OCL4); (2) three electrodes in the prefrontal lobe (PRL3); (3) four electrodes in the parietal lobe (PLL4), (4) eight electrodes in occipital combined parietal lobe (OPL8), (5) seven electrodes in occipital combined prefrontal lobe (OPL7); and (6) seven electrodes in parietal combined prefrontal lobe (PPL7). A multi-parameter combination-assisted binary logistic regression model was established to distinguish two groups. Receiver operating characteristic (ROC) curves were used to evaluate the MCI diagnostic power of each electrode configuration. The area under curve (AUC) of the ROC of electrode configurations OCL4, PRL3, PLL4, OPL8, OPL7 and PPL7 were 0.765, 0.683, 0.729, 0.83, 0.788, and 0.769, respectively. And the sensitivity of six electrode configurations were 0.962, 0.794, 0.873, 0.943, 0.859, and 0.938, respectively. Among these six configurations, OCL4, i.e. PO3, PO4, PO8, and PO7, had the highest sensitivity 96.2%, which meant that relying solely on these four electrodes of the occipital lobe had the potential to serve as an objective tool for preliminary screening of MCI. The abnormal brain rhythm characteristics of the frontal, parietal, and occipital lobes in the memory encoding stage of MCI provide a new perspective for MCI-WM impairment, which has the potential to be a novel biomarker for the early detection of pathological age-related cognitive decline. Further, a potential four-electrode configuration may be used for a novel detecting and monitoring EEG system of MCI in non-clinical settings. |
| format | Article |
| id | doaj-art-6a29e119d1714018b1b7ca4cf20bd6cb |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-6a29e119d1714018b1b7ca4cf20bd6cb2025-01-05T12:17:14ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-024-84277-4Optimizing electrode configurations for EEG mild cognitive impairment detectionYi Jiang0Xin Zhang1Zhiwei Guo2Xiaobo Zhou3Jiayuan He4Ning Jiang5The National Clinical Research Center for Geriatrics, West China Hospital, Sichuan UniversityThe College of Bioengineering, the Key Laboratory of Biorheological Science and Technology, Ministry of Education, Chongqing UniversityThe National Clinical Research Center for Geriatrics, West China Hospital, Sichuan UniversityCenter for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at HoustonThe National Clinical Research Center for Geriatrics, West China Hospital, Sichuan UniversityThe National Clinical Research Center for Geriatrics, West China Hospital, Sichuan UniversityAbstract The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM coding stage, six different electrode configurations were obtained: (1) four electrodes in the occipital lobe (OCL4); (2) three electrodes in the prefrontal lobe (PRL3); (3) four electrodes in the parietal lobe (PLL4), (4) eight electrodes in occipital combined parietal lobe (OPL8), (5) seven electrodes in occipital combined prefrontal lobe (OPL7); and (6) seven electrodes in parietal combined prefrontal lobe (PPL7). A multi-parameter combination-assisted binary logistic regression model was established to distinguish two groups. Receiver operating characteristic (ROC) curves were used to evaluate the MCI diagnostic power of each electrode configuration. The area under curve (AUC) of the ROC of electrode configurations OCL4, PRL3, PLL4, OPL8, OPL7 and PPL7 were 0.765, 0.683, 0.729, 0.83, 0.788, and 0.769, respectively. And the sensitivity of six electrode configurations were 0.962, 0.794, 0.873, 0.943, 0.859, and 0.938, respectively. Among these six configurations, OCL4, i.e. PO3, PO4, PO8, and PO7, had the highest sensitivity 96.2%, which meant that relying solely on these four electrodes of the occipital lobe had the potential to serve as an objective tool for preliminary screening of MCI. The abnormal brain rhythm characteristics of the frontal, parietal, and occipital lobes in the memory encoding stage of MCI provide a new perspective for MCI-WM impairment, which has the potential to be a novel biomarker for the early detection of pathological age-related cognitive decline. Further, a potential four-electrode configuration may be used for a novel detecting and monitoring EEG system of MCI in non-clinical settings.https://doi.org/10.1038/s41598-024-84277-4Mild cognitive impairmentElectroencephalographyWearable EEG deviceWorking memory |
| spellingShingle | Yi Jiang Xin Zhang Zhiwei Guo Xiaobo Zhou Jiayuan He Ning Jiang Optimizing electrode configurations for EEG mild cognitive impairment detection Scientific Reports Mild cognitive impairment Electroencephalography Wearable EEG device Working memory |
| title | Optimizing electrode configurations for EEG mild cognitive impairment detection |
| title_full | Optimizing electrode configurations for EEG mild cognitive impairment detection |
| title_fullStr | Optimizing electrode configurations for EEG mild cognitive impairment detection |
| title_full_unstemmed | Optimizing electrode configurations for EEG mild cognitive impairment detection |
| title_short | Optimizing electrode configurations for EEG mild cognitive impairment detection |
| title_sort | optimizing electrode configurations for eeg mild cognitive impairment detection |
| topic | Mild cognitive impairment Electroencephalography Wearable EEG device Working memory |
| url | https://doi.org/10.1038/s41598-024-84277-4 |
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