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Updated: Jun 13, 2026
Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation
Published on: July 16, 2014
The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates
Martin Lamoš1, Martina Bočková1,2, Sabina Goldemundová1
1Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
Abstract:
Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.
Insights
EEG microstates reveal brain network changes in Parkinson's disease (PD) patients. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) altered these microstates, correlating with symptom improvement.
Area of Science:
- Neuroscience
- Clinical Neurology
- Biomarkers
Background:
- Deep brain stimulation (DBS) is a key treatment for Parkinson's disease (PD), but its precise effects on cortical networks are not fully understood.
- Functional magnetic resonance imaging (fMRI) has been used to study these effects, but high-density electroencephalography (EEG) offers complementary insights and potential biomarkers.
- EEG microstates provide a method to analyze the spatiotemporal dynamics of large-scale brain networks.
Purpose of the Study:
- To investigate EEG microstate alterations in Parkinson's disease patients.
- To evaluate the impact of subthalamic nucleus (STN) DBS on these microstates.
- To correlate microstate dynamics with clinical and neuropsychological outcomes in PD patients.
Main Methods:
- Resting-state high-density EEG was recorded from 37 PD patients during both OFF and ON STN-DBS conditions.
- EEG microstate analysis was performed on patient data and compared to a matched healthy control group.
- Microstate parameters were correlated with clinical (UPDRS) and neuropsychological scores.
Main Results:
- Two distinct EEG microstates differed between PD patients and healthy controls.
- A specific microstate showed altered parameters in PD patients OFF DBS, which normalized towards healthy values when ON DBS.
- This microstate's beta power was highest in PD patients OFF DBS and lowest in controls, with sources localized to the supplementary motor area.
- Changes in microstate parameters correlated significantly with UPDRS and neuropsychological scores.
Conclusions:
- EEG microstates effectively capture disease-specific alterations in brain network dynamics in Parkinson's disease.
- The study demonstrates that STN-DBS influences these spatiotemporal network dynamics, correlating with motor symptom improvement.
- This EEG microstate approach holds promise for identifying biomarkers related to both motor and non-motor symptoms in PD, potentially aiding treatment assessment.
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