Autonomous learning agents for intelligent neurostimulation
Informal Systems Seminar (ISS) Centre for Intelligent Machines (CIM) and Groupe d'Etudes et de Recherche en Analyse des Decisions (GERAD)
Speaker: Marco Bonizzato
**听狈辞迟别听迟丑补迟听迟丑颈蝉听颈蝉听补听丑测产谤颈诲听别惫别苍迟.
**听狈辞迟别听迟丑补迟听迟丑颈蝉听蝉别尘颈苍补谤听颈蝉听补迟听鲍苍颈惫别谤蝉颈迟测听辞蹿听惭辞苍迟谤别补濒.
惭别别迟颈苍驳听滨顿:听845听1388听1004听听听听听听听
笔补蝉蝉肠辞诲别:听痴滨厂厂
Abstract: The nervous system communicates via electrical signals. Electrical neurostimulation is obtained by positioning electrodes in contact with brain, spinal cord or nerves and delivering stimuli that will modulate neuronal activity. This powerful technique allows causal investigation of neural circuits, enabling neuroscientific discovery. It also constitutes the biophysical foundation of a class of medical interventions. Neurostimulation always requires precise adjustment of several stimulation parameters, such as the spatial location of the stimulus, the timing, as well as the frequency of stimulus delivery. Even in the most cutting-edge applications, stimulation tuning has been almost exclusively handled manually. The lack of algorithmic frameworks to control and optimize neurostimulation has hindered scientific discovery. Our program is to transform neurostimulation by introducing an advanced autonomous control layer. We use Gaussian Process-based Bayesian Optimization (GPBO) as an algorithmic framework to tailor and personalize neurostimulation to each individual implant. We show that this framework could be scaled, via algorithmic novelties, to unprecedented neurostimulation steering capacities: 1) from solely stationary to new non-stationary optimization options, 2) from single target to multi-target optimization, 3) from simple outputs to sequences of stimuli. This work will equip neuroscientists and designers of medical technology with a toolbox of optimization methods to scale the next generation of medical technologies well beyond the limits of the present constrained control.
Bio: Marco Bonizzato is an Automation and Life Sciences Engineer working in implantable brain-computer interfaces and neuromodulation technology. He has a double expertise in (a) neural prostheses and (b) machine intelligence and optimization. He is an Assistant Professor of Electrical Engineering at Polytechnique Montr茅al, Adjunct Professor of Neurosciences at Universit茅 de Montr茅al and Associate Academic Member at Mila - Qu茅bec AI institute. He is directing the sciNeurotech Lab. The research goal is developing the entire translational arc of new neurostimulation therapies, aiming at restoring sensorimotor function after neurotrauma, from discovery in rodent to application in human medical technology, tailored and personalized to each user by artificial learning agents.