Publication details

Cortical network organization reflects clinical response to subthalamic nucleus deep brain stimulation in Parkinson's disease

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Authors

BOČKOVÁ Martina VÝTVAROVÁ Eva LAMOŠ Martin KLIMES P. JURAK P. HALAMEK J. GOLDEMUNDOVÁ Sabina BALÁŽ Marek REKTOR Ivan

Year of publication 2021
Type Article in Periodical
Magazine / Source Human Brain mapping
MU Faculty or unit

Central European Institute of Technology

Citation
Web https://onlinelibrary.wiley.com/doi/10.1002/hbm.25642
Doi http://dx.doi.org/10.1002/hbm.25642
Keywords deep brain stimulation; high-density EEG; network analysis; subthalamic nucleus
Description The degree of response to subthalamic nucleus deep brain stimulation (STN-DBS) is individual and hardly predictable. We hypothesized that DBS-related changes in cortical network organization are related to the clinical effect. Network analysis based on graph theory was used to evaluate the high-density electroencephalography (HDEEG) recorded during a visual three-stimuli paradigm in 32 Parkinson's disease (PD) patients treated by STN-DBS in stimulation "off" and "on" states. Preprocessed scalp data were reconstructed into the source space and correlated to the behavioral parameters. In the majority of patients (n = 26), STN-DBS did not lead to changes in global network organization in large-scale brain networks. In a subgroup of suboptimal responders (n = 6), identified according to reaction times (RT) and clinical parameters (lower Unified Parkinson's Disease Rating Scale [UPDRS] score improvement after DBS and worse performance in memory tests), decreased global connectivity in the 1-8 Hz frequency range and regional node strength in frontal areas were detected. The important role of the supplementary motor area for the optimal DBS response was demonstrated by the increased node strength and eigenvector centrality in good responders. This response was missing in the suboptimal responders. Cortical topologic architecture is modified by the response to STN-DBS leading to a dysfunction of the large-scale networks in suboptimal responders.
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