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Differences in EEG Event-Related Potentials during Dual Task in Parkinson’s Disease Carriers and Non-Carriers of the G2019S-LRRK2 Mutation

Authors :
Eden Shkury
Shani Danziger-Schragenheim
Zoya Katzir
Yael Ezra
Nir Giladi
Anat Mirelman
Inbal Maidan
Source :
Sensors, Vol 23, Iss 19, p 8266 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Background: The G2019S-LRRK2 gene mutation is a common cause of hereditary Parkinson’s disease (PD), associated with a higher frequency of the postural instability gait difficulty (PIGD) motor phenotype yet with preserved cognition. This study investigated neurophysiological changes during motor and cognitive tasks in PD patients with and without the G2019S-LRRK2 mutation. Methods: 33 iPD patients and 22 LRRK2-PD patients performed the visual Go/NoGo task (VGNG) during sitting (single-task) and walking (dual-task) while wearing a 64-channel EEG cap. Event-related potentials (ERP) from Fz and Pz, specifically N200 and P300, were extracted and analyzed to quantify brain activity patterns. Results: The LRRK2-PD group performed better in the VGNG than the iPD group (group*task; p = 0.05). During Go, the iPD group showed reduced N2 amplitude and prolonged N2 latency during walking, whereas the LRRK2-PD group showed only shorter latency (group*task p = 0.027). During NoGo, opposite patterns emerged; the iPD group showed reduced N2 and increased P3 amplitudes during walking while the LRRK2-PD group demonstrated increased N2 and reduced P3 (N2: group*task, p = 0.010, P3: group*task, p = 0.012). Conclusions: The LRRK2-PD group showed efficient early cognitive processes, reflected by N2, resulting in greater neural synchronization and prominent ERPs. These processes are possibly the underlying mechanisms for the observed better cognitive performance as compared to the iPD group. As such, future applications of intelligent medical sensing should be capable of capturing these electrophysiological patterns in order to enhance motor–cognitive functions.

Details

Language :
English
ISSN :
14248220
Volume :
23
Issue :
19
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.1378bb62dae4f5abf8f82d2331e42b7
Document Type :
article
Full Text :
https://doi.org/10.3390/s23198266