<  Back to the Polytechnique Montréal portal

Gaussian-process-based Bayesian optimization for neurostimulation interventions in rats

Léo Choinière, Rose Guay-Hottin, Rémi Picard, Guillaume Lajoie, Marco Bonizzato and Numa Dancause

Article (2024)

Open Acess document in PolyPublie and at official publisher
Open Access to the full text of this document
Published Version
Terms of Use: Creative Commons Attribution
Download (4MB)
Show abstract
Hide 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
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: 04 May 2024 22:24
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


Total downloads

Downloads per month in the last year

Origin of downloads


Repository Staff Only

View Item View Item