Léo Choinière, Rose Guay-Hottin, Rémi Picard, Guillaume Lajoie, Marco Bonizzato and Numa Dancause
Article (2024)
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Open Access to the full text of this document Published Version Terms of Use: Creative Commons Attribution Download (4MB) |
Abstract
Effective neural stimulation requires adequate parametrization. Gaussian-process (GP)-based Bayesian optimization (BO) offers a framework to discover optimal stimulation parameters in real time. Here, we first provide a general protocol to deploy this framework in neurostimulation interventions and follow by exemplifying its use in detail. Specifically, we describe the steps to implant rats with multi-channel electrode arrays in the hindlimb motor cortex. We then detail how to utilize the GP-BO algorithm to maximize evoked target movements, measured as electromyographic responses.
For complete details on the use and execution of this protocol, please refer to Bonizzato and colleagues (2023).
Subjects: |
1900 Biomedical engineering > 1900 Biomedical engineering 1900 Biomedical engineering > 1901 Biomedical technology 2500 Electrical and electronic engineering > 2500 Electrical and electronic engineering 2700 Information technology > 2715 Optimization |
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Department: |
Department of Electrical Engineering Institut de génie biomédical |
Funders: | NSERC / CRSNG, New Frontiers in Research Fund, Institut de Valorisation des Données (IVADO), Unifying Neuroscience and Artificial Intelligence - Québec (UNIQUE), Fonds de recherche du Québec – Nature et technologies (FRQNT), Fonds de Recherche Québec Santé (FRQS), Canada Research Chair in Neural Computation and Interfacing (tier 2), Canada CIFAR AI Research Chair |
Grant number: | RGPIN-2022-04210, RGPIN-2023-04370, NFRFE-2022-00394, PRF-2019-0039445779, 336095, 318568, 0961371377 |
PolyPublie URL: | https://publications.polymtl.ca/57817/ |
Journal Title: | STAR Protocols (vol. 5, no. 1) |
Publisher: | Elsevier |
DOI: | 10.1016/j.xpro.2024.102885 |
Official URL: | https://doi.org/10.1016/j.xpro.2024.102885 |
Date Deposited: | 28 Mar 2024 15:20 |
Last Modified: | 30 Sep 2024 14:59 |
Cite in APA 7: | Choinière, L., Guay-Hottin, R., Picard, R., Lajoie, G., Bonizzato, M., & Dancause, N. (2024). Gaussian-process-based Bayesian optimization for neurostimulation interventions in rats. STAR Protocols, 5(1), 102885 (28 pages). https://doi.org/10.1016/j.xpro.2024.102885 |
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