EEG microstate analysis in patients with disorders of consciousness and its clinical significance

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Küçük Resim

Tarih

2024

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

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.

Açıklama

Anahtar Kelimeler

Disorders of Consciousness, EEG Microstate Analysis, Microstate D, Minimally Conscious State, Vegetative State

Kaynak

Brain Topography

WoS Q Değeri

Q3

Scopus Q Değeri

Q1

Cilt

37

Sayı

3

Künye

Toplutaş, E., Aydın, F. ve Hanoğlu, L. (2024). EEG microstate analysis in patients with disorders of consciousness and its clinical significance. Brain Topography, 37(3), 377-387. http://dx.doi.org/10.1007/s10548-023-00939-y