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Leo Choiniere

PhD - Université de Montréal
Supervisor
Guillaume Lajoie
Research Topics
Computational Neuroscience
Optimization

Publications

Gaussian-process-based Bayesian optimization for neurostimulation interventions in rats
Leo Choiniere
Rose Guay-Hottin
Rémi Picard
Guillaume Lajoie
Marco Bonizzato
Numa Dancause
2024-02-29
STAR Protocols (published)
doi.org
Autonomous optimization of neuroprosthetic stimulation parameters that drive the motor cortex and spinal cord outputs in rats and monkeys
Marco Bonizzato
Rose Guay Hottin
Sandrine L. Côté
Elena Massai
Leo Choiniere
Uzay Macar
Samuel Laferrière
Parikshat Sirpal
Stephan Quessy
Guillaume Lajoie
Marina Martinez
Numa Dancause
Neural stimulation can alleviate paralysis and sensory deficits. Novel high-density neural interfaces can enable refined and multipronged ne… (see more)urostimulation interventions. To achieve this, it is essential to develop algorithmic frameworks capable of handling optimization in large parameter spaces. Here, we leveraged an algorithmic class, Gaussian-process (GP)-based Bayesian optimization (BO), to solve this problem. We show that GP-BO efficiently explores the neurostimulation space, outperforming other search strategies after testing only a fraction of the possible combinations. Through a series of real-time multi-dimensional neurostimulation experiments, we demonstrate optimization across diverse biological targets (brain, spinal cord), animal models (rats, non-human primates), in healthy subjects, and in neuroprosthetic intervention after injury, for both immediate and continual learning over multiple sessions. GP-BO can embed and improve “prior” expert/clinical knowledge to dramatically enhance its performance. These results advocate for broader establishment of learning agents as structural elements of neuroprosthetic design, enabling personalization and maximization of therapeutic effectiveness.
2023-03-31
Cell Reports Medicine (published)
doi.org