EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance
Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we belie...
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| Published in | Brain topography Vol. 37; no. 3; pp. 377 - 387 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.05.2024
Springer Nature B.V |
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| Online Access | Get full text |
| ISSN | 0896-0267 1573-6792 1573-6792 |
| DOI | 10.1007/s10548-023-00939-y |
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| Abstract | Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness. |
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| AbstractList | Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness. Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness. |
| Author | Toplutaş, Eren Aydın, Fatma Hanoğlu, Lütfü |
| Author_xml | – sequence: 1 givenname: Eren surname: Toplutaş fullname: Toplutaş, Eren email: erentoplutas@gmail.com organization: Department of Neurology, Istanbul Eyupsultan Public Hospital, Program of Neuroscience Ph.D., Graduate School of Health Sciences,, Istanbul Medipol University – sequence: 2 givenname: Fatma surname: Aydın fullname: Aydın, Fatma organization: Program of Neuroscience Ph.D., Graduate School of Health Sciences,, Istanbul Medipol University – sequence: 3 givenname: Lütfü surname: Hanoğlu fullname: Hanoğlu, Lütfü organization: Department of Neurology, School of Medicine, Istanbul Medipol University, Neuroimaging and Neuromodulation Lab, Clinical Electrophysiology, REMER, Istanbul Medipol University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36735192$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1007_s10548_023_01004_4 crossref_primary_10_1088_1741_2552_ad7904 crossref_primary_10_1111_cns_70220 crossref_primary_10_1016_j_neulet_2024_137986 crossref_primary_10_3389_fnins_2023_1306120 crossref_primary_10_1007_s10548_024_01037_3 crossref_primary_10_3389_fnins_2023_1257511 crossref_primary_10_1016_j_matt_2024_05_023 |
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| Keywords | Vegetative state Microstate D EEG microstate analysis Minimally conscious state Disorders of consciousness |
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| SubjectTerms | Biomedical and Life Sciences Biomedicine Clinical Relevance Consciousness Consciousness - physiology Consciousness Disorders - diagnosis EEG Electroencephalography Humans Neurology Neurosciences Original Paper Patients Persistent Vegetative State Prospective Studies Psychiatry |
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| Title | EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance |
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