Dynamical patterns of EEG connectivity unveil Parkinson’s disease progression: insights from machine learning analysis

Dynamical patterns of EEG connectivity unveil Parkinson’s disease progression: insights from machine learning analysis

Parkinson’s disease (PD) is a multifactorial neurodegenerative disorder with complex progression. This study aims to analyze electroencephalography (EEG) connectivity patterns to better understand PD progression and stage of the disease using machine learning. Resting-state, eyes-closed EEG recordin...

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Bibliographic Details
Main Authors: Caroline L Alves, Loriz Francisco Sallum, Francisco Aparecido Rodrigues, Thaise G L de O Toutain, Patrícia Maria de Carvalho Aguiar, Michael Moeckel
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Journal of Physics: Complexity
Subjects:
brain network
Parkinson disease
age stage
machine learning
Online Access:https://doi.org/10.1088/2632-072X/adf58a
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https://doi.org/10.1088/2632-072X/adf58a

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