Informace o publikaci

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

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

Rok publikování 2021
Druh Článek v odborném periodiku
Časopis / Zdroj Human Brain mapping
Fakulta / Pracoviště MU

Středoevropský technologický institut

Citace
www https://onlinelibrary.wiley.com/doi/10.1002/hbm.25642
Doi http://dx.doi.org/10.1002/hbm.25642
Klíčová slova deep brain stimulation; high-density EEG; network analysis; subthalamic nucleus
Popis 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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