Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025
Altered electroencephalography-based source functional connectivity in patients with generalized anxiety disorder.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chu Che-Sheng, Lin Yen-Yue, Chia-Yu Huang Cathy, Chung Yong-An, Youngju Park Sonya, Chang Wei-Chou, Chang Chuan-Chia, Chang Hsin-An
Аннотация
OBJECTIVE: To explore the neurophysiological markers of generalized anxiety disorder (GAD), we performed electroencephalography (EEG) in patients with GAD and assessed lagged phase synchronization (LPS), a measure of brain functional connectivity (FC).
METHODS: Cortical EEG sources were modelled by exact low resolution brain electromagnetic tomography (eLORETA). Graph theory analyses were applied to undirected and weighted networks obtained by LPS to explore the FC differences between patients with GAD and controls. The association between the abnormal parameters and disease symptomatology was examined.
RESULTS: Compared to controls (n = 89), the GAD group (n = 104) showed higher brain connectivity in beta-2 (18.5-21 Hz) between the left cingulate gyrus and the right postcentral gyrus (PcG) and in beta-3 (21.5-30 Hz) between the brain hemispheres in several regions, particularly the left PcG. Patients with GAD showed higher global network efficiency in beta-3. Finally, a positive correlation was observed between a longer duration of illness and greater FC in beta-2 between brain regions.
CONCLUSIONS: The present findings suggest that EEG-sourced measures are useful tools for understanding altered brain connectivity in GAD.
SIGNIFICANCE: EEG could be a valuable biomarker in differentiating patients with GAD from controls and could be a potential predictive tool in future studies.
METHODS: Cortical EEG sources were modelled by exact low resolution brain electromagnetic tomography (eLORETA). Graph theory analyses were applied to undirected and weighted networks obtained by LPS to explore the FC differences between patients with GAD and controls. The association between the abnormal parameters and disease symptomatology was examined.
RESULTS: Compared to controls (n = 89), the GAD group (n = 104) showed higher brain connectivity in beta-2 (18.5-21 Hz) between the left cingulate gyrus and the right postcentral gyrus (PcG) and in beta-3 (21.5-30 Hz) between the brain hemispheres in several regions, particularly the left PcG. Patients with GAD showed higher global network efficiency in beta-3. Finally, a positive correlation was observed between a longer duration of illness and greater FC in beta-2 between brain regions.
CONCLUSIONS: The present findings suggest that EEG-sourced measures are useful tools for understanding altered brain connectivity in GAD.
SIGNIFICANCE: EEG could be a valuable biomarker in differentiating patients with GAD from controls and could be a potential predictive tool in future studies.