An Electroencephalography Profile of Paroxysmal Kinesigenic Dyskinesia.
functional connectivity
high-density electroencephalogram
oscillatory activity
paroxysmal kinesigenic dyskinesia
Journal
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
ISSN: 2198-3844
Titre abrégé: Adv Sci (Weinh)
Pays: Germany
ID NLM: 101664569
Informations de publication
Date de publication:
16 Jan 2024
16 Jan 2024
Historique:
revised:
24
11
2023
received:
03
09
2023
medline:
16
1
2024
pubmed:
16
1
2024
entrez:
16
1
2024
Statut:
aheadofprint
Résumé
Paroxysmal kinesigenic dyskinesia (PKD) is associated with a disturbance of neural circuit and network activities, while its neurophysiological characteristics have not been fully elucidated. This study utilized the high-density electroencephalogram (hd-EEG) signals to detect abnormal brain activity of PKD and provide a neural biomarker for its clinical diagnosis and PKD progression monitoring. The resting hd-EEGs are recorded from two independent datasets and then source-localized for measuring the oscillatory activities and function connectivity (FC) patterns of cortical and subcortical regions. The abnormal elevation of theta oscillation in wildly brain regions represents the most remarkable physiological feature for PKD and these changes returned to healthy control level in remission patients. Another remarkable feature of PKD is the decreased high-gamma FCs in non-remission patients. Subtype analyses report that increased theta oscillations may be related to the emotional factors of PKD, while the decreased high-gamma FCs are related to the motor symptoms. Finally, the authors established connectome-based predictive modelling and successfully identified the remission state in PKD patients in dataset 1 and dataset 2. The findings establish a clinically relevant electroencephalography profile of PKD and indicate that hd-EEG can provide robust neural biomarkers to evaluate the prognosis of PKD.
Identifiants
pubmed: 38227367
doi: 10.1002/advs.202306321
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2306321Subventions
Organisme : Shanghai Municipal Health Commission
ID : 2022LJ011
Organisme : National Natural Science Foundation of China
ID : 82371255
Organisme : National Natural Science Foundation of China
ID : 82201398
Organisme : National Natural Science Foundation of China
ID : 82071258
Organisme : National Natural Science Foundation of China
ID : 81870889
Organisme : Shanghai Hospital Development Center
ID : SHDC2022CRD037
Organisme : Science and Technology Commission of Shanghai Municipality
ID : 23XD1402500
Organisme : Science and Technology Commission of Shanghai Municipality
ID : 23DZ2291500
Informations de copyright
© 2024 The Authors. Advanced Science published by Wiley-VCH GmbH.
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