Autonomous optimization of neuroprosthetic stimulation parameters that drive the motor cortex and spinal cord outputs in rats and monkeys
| Résumé | Neural stimulation can alleviate paralysis and sensory deficits. Novel high-density neural interfaces can enable refined and multipronged neurostimulation 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. |
| Auteurs | Marco Bonizzato, Rose Guay Hottin, Sandrine L. Côté, Elena Massai, Léo Choinière, Uzay Macar, Samuel Laferrière, Parikshat Sirpal, Stephan Quessy, Guillaume Lajoie, Marina Martinez, Numa Dancause |
| Titre de revue/journal, volume et numéro | Cell Reports Medicine, volume 4, numéro 4. |
| Langue de la publication et/ou de traduction | Anglais (langue d’origine) |
| Année de parution | 2023 |
| Pays | Québec, Canada. |
| Institutions affiliées | CIRCA, UdeM |
| Lien vers la publication | https://doi.org/10.1016/j.xcrm.2023.101008 |
| Type d’accès à la publication | Gratuit |
| Mots clés | Artificial intelligence, Bayesian optimization, Black-box optimization, brain-computer interface, machine learning, neural interfaces, neuromodulation, neurotechnology, neurostimulation, precision medicine |
| Autres informations |