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Evoked resonant neural activity long-term dynamics can be reproduced by a computational model with vesicle depletion

Abstract:
Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinson's disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA (over hundreds of seconds) with a single neuronal population, and, crucially, with vesicle depletion as one of the key mechanisms behind the ERNA frequency decay in our model. We further validate the proposed model against experimental data from Parkinson's disease patients, where it captures the variations in ERNA frequency and amplitude in response to variable stimulation frequency, amplitude, and to stimulation pulse bursting. We provide a series of predictions from the model that could be the subject of future studies for further validation.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.nbd.2024.106565

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Research group:
MRC Brain Networks Dynamics Unit
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Research group:
MRC Brain Networks Dynamics Unit
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Research group:
MRC Brain Networks Dynamics Unit
Role:
Author
ORCID:
0000-0001-8038-3029
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Research group:
MRC Brain Networks Dynamics Unit
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Research group:
MRC Brain Networks Dynamics Unit
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0001-6147-905X


More from this funder
Funder identifier:
https://ror.org/03x94j517
Grant:
MR/P012272/1
MR/V00655X/1
More from this funder
Funder identifier:
https://ror.org/0526snb40
Grant:
RF2223-22-270
More from this funder
Funder identifier:
https://ror.org/04e3zg361


Publisher:
Elsevier
Journal:
Neurobiology of Disease More from this journal
Volume:
199
Article number:
106565
Place of publication:
United States
Publication date:
2024-06-14
Acceptance date:
2024-06-11
DOI:
EISSN:
1095-953X
ISSN:
0969-9961
Pmid:
38880431


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