Journal article
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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(Preview, Version of record, pdf, 7.3MB, Terms of use)
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(Preview, Supplementary materials, pdf, 12.3MB, Terms of use)
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- Publisher copy:
- 10.1016/j.nbd.2024.106565
Authors
+ Medical Research Council
More from this funder
- Funder identifier:
- https://ror.org/03x94j517
- Grant:
- MR/P012272/1
- MR/V00655X/1
+ Royal Academy of Engineering
More from this funder
- Funder identifier:
- https://ror.org/0526snb40
- Grant:
- RF2223-22-270
- 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:
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0969-9961
- Pmid:
-
38880431
- Language:
-
English
- Keywords:
- Pubs id:
-
2009596
- Local pid:
-
pubs:2009596
- Deposit date:
-
2024-07-08
- ARK identifier:
Terms of use
- Copyright holder:
- Sermon et al
- Copyright date:
- 2024
- Rights statement:
- © 2024 The Author(s). This article is distributed under the terms of the Creative Commons Attributions (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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