ArticleFrontiers in neuroscience2023
EEG-based biomarkers for optimizing deep brain stimulation contact configuration in Parkinson's disease.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Clinical utility of evoked potentials for programming subthalamic deep brain stimulation in Parkinsons disease.NPJ Parkinson's disease · 2026Review
- Electrophysiological Biomarkers Reflect Target Engagement and Response Using Deep Brain Stimulation for Obsessive-Compulsive Disorder.Biological psychiatry global open science · 2026Article
- Survey of common deep brain stimulation programming practices by experts in Parkinson's Disease.Journal of neurology · 2024Article
- Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson's disease.NPJ Parkinson's disease · 2024Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Subthalamic deep brain stimulation (STN-DBS) is a neurosurgical therapy to treat Parkinson's disease (PD). Optimal therapeutic outcomes are not achieved in all patients due to increased DBS technological complexity; programming time constraints; and delayed clinical response of some symptoms. To streamline the programming process, biomarkers could be used to accurately predict the most effective stimulation configuration. Therefore, we investigated if DBS-evoked potentials (EPs) combined with imaging to perform prediction analyses could predict the best contact configuration. Methods: In 10 patients, EPs were recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. In two patients, we recorded from both hemispheres, resulting in recordings from a total of 12 hemispheres. A monopolar review was performed by stimulating on each contact and measuring the therapeutic window. CT and MRI data were collected. Prediction models were created to assess how well the EPs and imaging could predict the best contact configuration. Results: EPs at 3 ms and at 10 ms were recorded. The prediction models showed that EPs can be combined with imaging data to predict the best contact configuration and hence, significantly outperformed random contact selection during a monopolar review. Conclusion: EPs can predict the best contact configuration. Ultimately, these prediction tools could be implemented into daily practice to ease the DBS programming of PD patients.
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