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Prediction of Pathological Subthalamic Nucleus Beta Burst Occurrence in Parkinson's Disease

Abstract:
Background: The corticobasal ganglia network in Parkinson's disease (PD) is characterized by the occurrence of transient episodes of exaggerated beta frequency oscillatory synchrony, known as bursts. Although it is known that bursts of prolonged duration associate closely with motor impairments, the mechanisms leading to burst initiation remain poorly understood. Related to this, current adaptive deep brain stimulation (DBS) approaches reactively deliver stimulation following burst onset but cannot stimulate proactively to prevent bursts from occurring. The discovery of predictive biomarkers could allow for proactive stimulation, thereby offering potential for improvements in therapeutic efficacy. Objectives: We aimed to address this issue, by using deep neural networks to discover features of basal ganglia activity that reliably precede beta burst onset. Methods: We developed a deep learning model to predict burst onset from subthalamic nucleus (STN) activity recordings in PD patients. Our model provides patient‐specific predictions in two independent datasets of STN recordings, including prolonged‐duration recordings from sensing‐enabled DBS devices during naturalistic behaviors. Results: The occurrence of STN beta bursts can be reliably predicted up to 100 ms prior to onset. Importantly, our results reveal that a dip in the beta amplitude—which is likely to be indicative of a phase reset of oscillatory populations occurring between 80 and 100 ms prior to burst onset—is a predictive biomarker for burst occurrence. Conclusions: These findings demonstrate proof‐of‐principle for the feasibility of beta burst prediction and inform the future development of intelligent DBS approaches with the capability of proactive stimulation to prevent beta burst occurrence. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1002/mds.70076

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Institution:
University of Oxford
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Institution:
University of Oxford
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Author
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Institution:
University of Oxford
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Author
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Institution:
University of Oxford
Role:
Author


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Funder identifier:
https://ror.org/04e3zg361
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Funder identifier:
https://ror.org/029chgv08
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Funder identifier:
https://ror.org/04atp4p48
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Funder identifier:
https://ror.org/03x94j517


Publisher:
Wiley
Journal:
Movement Disorders More from this journal
Publication date:
2025-10-03
Acceptance date:
2025-09-18
DOI:
EISSN:
1531-8257
ISSN:
0885-3185


Language:
English
Keywords:
Pubs id:
2300118
Local pid:
pubs:2300118
Source identifiers:
3339254
Deposit date:
2025-10-03
ARK identifier:
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