Nejvíce citovaný článek - PubMed ID 22938795
Oscillatory changes in cognitive networks activated during a three-stimulus visual paradigm: an intracerebral study
The aim of this work was to study the effect of deep brain stimulation of the subthalamic nucleus (STN-DBS) on the subnetwork of subcortical and cortical motor regions and on the whole brain connectivity using the functional connectivity analysis in Parkinson's disease (PD). The high-density source space EEG was acquired and analyzed in 43 PD subjects in DBS on and DBS off stimulation states (off medication) during a cognitive-motor task. Increased high gamma band (50-100 Hz) connectivity within subcortical regions and between subcortical and cortical motor regions was significantly associated with the Movement Disorders Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III improvement after DBS. Whole brain neural correlates of cognitive performance were also detected in the high gamma (50-100 Hz) band. A whole brain multifrequency connectivity profile was found to classify optimal and suboptimal responders to DBS with a positive predictive value of 0.77, negative predictive value of 0.55, specificity of 0.73, and sensitivity of 0.60. Specific connectivity patterns related to PD, motor symptoms improvement after DBS, and therapy responsiveness predictive connectivity profiles were uncovered.
- Klíčová slova
- Connectivity patterns, Deep brain stimulation, EEG, Functional connectivity, Parkinson’s disease, Subthalamic nucleus,
- MeSH
- elektroencefalografie metody MeSH
- hluboká mozková stimulace * metody MeSH
- lidé středního věku MeSH
- lidé MeSH
- mozek patofyziologie diagnostické zobrazování MeSH
- nucleus subthalamicus * patofyziologie MeSH
- Parkinsonova nemoc * terapie patofyziologie MeSH
- senioři MeSH
- výsledek terapie MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
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.
- Klíčová slova
- deep brain stimulation, high-density EEG, network analysis, subthalamic nucleus,
- MeSH
- elektroencefalografie MeSH
- hluboká mozková stimulace * MeSH
- hodnocení výsledků zdravotní péče MeSH
- lidé středního věku MeSH
- lidé MeSH
- mozková kůra patofyziologie MeSH
- nervová síť patofyziologie MeSH
- nucleus subthalamicus patofyziologie MeSH
- Parkinsonova nemoc patofyziologie terapie MeSH
- psychomotorický výkon fyziologie MeSH
- senioři MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH