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Erschienen in: Cognitive Neurodynamics 3/2021

19.10.2020 | Research Article

Study of EEG microstates in Parkinson’s disease: a potential biomarker?

verfasst von: Anita Pal, Madhuri Behari, Vinay Goyal, Ratna Sharma

Erschienen in: Cognitive Neurodynamics | Ausgabe 3/2021

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Abstract

The spontaneous activity of the brain is dynamic even at rest and the deviation from this normal pattern of dynamics can lead to different pathological states. EEG microstate analysis of resting-state neuronal activity in Parkinson’s disease (PD) could provide insight into altered brain dynamics of patients exhibiting dementia. Resting-state EEG microstate maps were derived from 128 channel EEG data in 20 PD without dementia (PDND), 18 PD with dementia (PDD) and 20 Healthy controls (CON) using Cartool and sLORETA softwares. Microstate map parameters including global explained variance, mean duration, frequency of occurrence (TF) and time coverage were compared statistically among the groups. Eight maps that explained 72% of the topographic variance were identified and only three maps differed significantly across the groups. TF of Map1 was lower in both PDND and PDD (p < 0.001) and that of Map3 (p = 0.02) in PDND compared to control. Cortical sources showed higher activation in precuneus, cuneus and superior parietal lobe (Threshold: Log-F = 1.74, p < 0.05) with maximum activity in the precuneus region (MNI co-ordinates: − 25, − 75, − 40; Log-F = 1.9) in PDND compared to control only for Map1. Lower TF of Map1 (prototypical microstate D) may potentially serve as a biomarker for PD with or without dementia whereas higher activation of precuneus, cuneus and superior parietal lobe at resting-state could favour signal processing, lack of which could be associated with dementia in Parkinson’s disorder.

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Metadaten
Titel
Study of EEG microstates in Parkinson’s disease: a potential biomarker?
verfasst von
Anita Pal
Madhuri Behari
Vinay Goyal
Ratna Sharma
Publikationsdatum
19.10.2020
Verlag
Springer Netherlands
Erschienen in
Cognitive Neurodynamics / Ausgabe 3/2021
Print ISSN: 1871-4080
Elektronische ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-020-09643-0

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