EEG in Parkinson’s Disease: Mechanisms, Biomarkers and Translational Opportunities
Abstract
Parkinson’s disease (PD) is characterized by nigrostriatal dopaminergic degeneration and basal ganglia dysfunction, yet these pathophysiological abnormalities alone do not fully explain its heterogeneous motor and non-motor manifestations. Over recent decades, electroencephalography (EEG) has evolved from a primarily descriptive technique into a quantitative approach for investigating cortical electrophysiological dynamics associated with PD. Accumulating electrophysiological evidence implicates altered oscillatory synchronization and interactions across cortical and subcortical circuits in PD-related dysfunction, suggesting disturbances in the temporal coordination of neural activity. Emerging approaches, including large-scale datasets, multimodal integration, individualized modeling and wearable EEG technologies, offer opportunities for physiological phenotyping and real-world monitoring. However, methodological heterogeneity, limited reproducibility, insufficient external validation and uncertainty regarding clinical utility continue to constrain translation. This Review critically synthesizes EEG-derived measures spanning spectral activity, oscillatory coupling, functional connectivity and dynamic brain states, examining their relationships with motor, cognitive and neuropsychiatric manifestations of PD. By distinguishing mechanistic interpretations, clinical associations and current levels of biomarker validation, it identifies opportunities and requirements for translating EEG-derived measures into reliable tools for individualized assessment and clinical decision-making.
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BibTeX
@misc{ozdemir2026parkinsons,
title = {{EEG in Parkinson’s Disease: Mechanisms, Biomarkers and Translational Opportunities}},
author = {Sümeyye Özdemir and Sahar Allouch and Manon Auffret and Mahmoud Hassan and Marc Vérin},
howpublished = {PsyArXiv},
year = {2026},
month = oct,
doi = {10.31234/osf.io/pqzt9_v1},
url = {https://osf.io/preprints/psyarxiv/pqzt9_v1/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - EEG in Parkinson’s Disease: Mechanisms, Biomarkers and Translational Opportunities
AU - Sümeyye Özdemir
AU - Sahar Allouch
AU - Manon Auffret
AU - Mahmoud Hassan
AU - Marc Vérin
PY - 2026
DA - 2026/10/14
PB - PsyArXiv
DO - 10.31234/osf.io/pqzt9_v1
UR - https://osf.io/preprints/psyarxiv/pqzt9_v1/
AB - Parkinson’s disease (PD) is characterized by nigrostriatal dopaminergic degeneration and basal ganglia dysfunction, yet these pathophysiological abnormalities alone do not fully explain its heterogeneous motor and non-motor manifestations. Over recent decades, electroencephalography (EEG) has evolved from a primarily descriptive technique into a quantitative approach for investigating cortical electrophysiological dynamics associated with PD. Accumulating electrophysiological evidence implicates altered oscillatory synchronization and interactions across cortical and subcortical circuits in PD-related dysfunction, suggesting disturbances in the temporal coordination of neural activity. Emerging approaches, including large-scale datasets, multimodal integration, individualized modeling and wearable EEG technologies, offer opportunities for physiological phenotyping and real-world monitoring. However, methodological heterogeneity, limited reproducibility, insufficient external validation and uncertainty regarding clinical utility continue to constrain translation. This Review critically synthesizes EEG-derived measures spanning spectral activity, oscillatory coupling, functional connectivity and dynamic brain states, examining their relationships with motor, cognitive and neuropsychiatric manifestations of PD. By distinguishing mechanistic interpretations, clinical associations and current levels of biomarker validation, it identifies opportunities and requirements for translating EEG-derived measures into reliable tools for individualized assessment and clinical decision-making.
ER -