ArticleNPJ Parkinson's disease2026
DBSsync: combining intracranial and multimodal data to investigate new biomarkers in Parkinson's disease.
Article in NPJ Parkinson's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
Implanted deep brain stimulation devices are now capable of chronically recording activity from intracranial brain areas during stimulation. This new type of data has the potential to increase our understanding of disease-related brain activity and its modulation in response to therapy or other types of stimuli. With the innovative approach of adaptive deep brain stimulation now clinically available, multimodal characterization of neural biomarkers becomes of utmost importance to define optimal feedback signals for adaptive brain stimulation and allow for better fine-tuning of stimulation parameters. To investigate these biomarkers, we developed DBSsync, a paradigm and an open-source Python toolbox with its graphical user interface for temporally precise synchronization of intracranial recordings with external data, allowing for multimodal research protocols. DBSsync achieves a temporal precision of 8 ms and incorporates cardiac artifact removal methods to facilitate intracranial data preprocessing, thus enabling the integration and precise synchronization of multiple brain signals with external sensors and various behavioral timeline data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.