Closed-loop multisensory brain-computer interfaces for enhanced decision accuracy
Our joint US/UK effort investigates the neural mechanisms underlying multisensory processing and decision making. We develop models and adaptive algorithms that use multisensory information in closed-loop brain-computer interfaces.
The project brings together computational work in Bayesian inference, stochastic control, adaptive signal processing, and machine learning with experimental neurophysiology.
Principal investigator: Maryam Shanechi, University of Southern California. Funding agencies: US Army Research Office and UK Ministry of Defence.