Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker
ObjectivesA huge population, especially the elderly, suffers from otogenic vertigo. However, the multi-modal vestibular network changes, secondary to periphery vestibular dysfunction, have not been fully elucidated. We aim to identify potential microstate electroencephalography (EEG) signatures for...
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2022.914920/full |
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| author | Yi-Ni Li Wen Lu Jie Li Ming-Xian Li Jia Fang Tao Xu Ti-Fei Yuan Di Qian Hai-Bo Shi Shan-Kai Yin |
| author_facet | Yi-Ni Li Wen Lu Jie Li Ming-Xian Li Jia Fang Tao Xu Ti-Fei Yuan Di Qian Hai-Bo Shi Shan-Kai Yin |
| author_sort | Yi-Ni Li |
| collection | DOAJ |
| description | ObjectivesA huge population, especially the elderly, suffers from otogenic vertigo. However, the multi-modal vestibular network changes, secondary to periphery vestibular dysfunction, have not been fully elucidated. We aim to identify potential microstate electroencephalography (EEG) signatures for otogenic vertigo in this study.Materials and MethodsPatients with recurrent otogenic vertigo and age-matched healthy adults were recruited. We performed 256-channel EEG recording of all participants at resting state. Neuropsychological questionnaires and vestibular function tests were taken as a measurement of patients’ symptoms and severity. We clustered microstates into four classes (A, B, C, and D) and identified their dynamic and syntax alterations of them. These features were further fed into a support vector machine (SVM) classifier to identify microstate signatures for vertigo.ResultsWe compared 40 patients to 45 healthy adults, finding an increase in the duration of Microstate A, and both the occurrence and time coverage of Microstate D. The coverage and occurrence of Microstate C decreased significantly, and the probabilities of non-random transitions between Microstate A and D, as well as Microstate B and C, also changed. To distinguish the patients, the SVM classifier, which is built based on these features, got a balanced accuracy of 0.79 with a sensitivity of 0.78 and a specificity of 0.8.ConclusionThere are several temporal dynamic alterations of EEG microstates in patients with otogenic vertigo, especially in Microstate D, reflecting the underlying process of visual-vestibular reorganization and attention redistribution. This neurophysiological signature of microstates could be used to identify patients with vertigo in the future. |
| first_indexed | 2024-04-13T21:51:38Z |
| format | Article |
| id | doaj.art-3edd49a6136f46ef95d2c7c0c6f5941f |
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| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-04-13T21:51:38Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-3edd49a6136f46ef95d2c7c0c6f5941f2022-12-22T02:28:24ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652022-06-011410.3389/fnagi.2022.914920914920Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease MarkerYi-Ni Li0Wen Lu1Jie Li2Ming-Xian Li3Jia Fang4Tao Xu5Ti-Fei Yuan6Di Qian7Hai-Bo Shi8Shan-Kai Yin9Department of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Anesthesiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Otolaryngology, People’s Hospital of Longhua, Shenzhen, ChinaDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Otorhinolaryngology Head and Neck Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, ChinaObjectivesA huge population, especially the elderly, suffers from otogenic vertigo. However, the multi-modal vestibular network changes, secondary to periphery vestibular dysfunction, have not been fully elucidated. We aim to identify potential microstate electroencephalography (EEG) signatures for otogenic vertigo in this study.Materials and MethodsPatients with recurrent otogenic vertigo and age-matched healthy adults were recruited. We performed 256-channel EEG recording of all participants at resting state. Neuropsychological questionnaires and vestibular function tests were taken as a measurement of patients’ symptoms and severity. We clustered microstates into four classes (A, B, C, and D) and identified their dynamic and syntax alterations of them. These features were further fed into a support vector machine (SVM) classifier to identify microstate signatures for vertigo.ResultsWe compared 40 patients to 45 healthy adults, finding an increase in the duration of Microstate A, and both the occurrence and time coverage of Microstate D. The coverage and occurrence of Microstate C decreased significantly, and the probabilities of non-random transitions between Microstate A and D, as well as Microstate B and C, also changed. To distinguish the patients, the SVM classifier, which is built based on these features, got a balanced accuracy of 0.79 with a sensitivity of 0.78 and a specificity of 0.8.ConclusionThere are several temporal dynamic alterations of EEG microstates in patients with otogenic vertigo, especially in Microstate D, reflecting the underlying process of visual-vestibular reorganization and attention redistribution. This neurophysiological signature of microstates could be used to identify patients with vertigo in the future.https://www.frontiersin.org/articles/10.3389/fnagi.2022.914920/fullvertigoEEGneural networkmicrostatesupport vector machine (SVM) |
| spellingShingle | Yi-Ni Li Wen Lu Jie Li Ming-Xian Li Jia Fang Tao Xu Ti-Fei Yuan Di Qian Hai-Bo Shi Shan-Kai Yin Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker Frontiers in Aging Neuroscience vertigo EEG neural network microstate support vector machine (SVM) |
| title | Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker |
| title_full | Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker |
| title_fullStr | Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker |
| title_full_unstemmed | Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker |
| title_short | Electroencephalography Microstate Alterations in Otogenic Vertigo: A Potential Disease Marker |
| title_sort | electroencephalography microstate alterations in otogenic vertigo a potential disease marker |
| topic | vertigo EEG neural network microstate support vector machine (SVM) |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2022.914920/full |
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