Properties of a temporal difference reinforcement learning brain machine interface driven by a simulated motor cortex.
Our overall goal is to develop a reinforcement learning (RL) based decoder for brain machine interfaces. As an important step in this process, we determine the basic stability and convergence properties of a Temporal Difference (TD) RL architecture being driven by a simulated motor cortex.
Department of Physiology and Pharmacology, SUNY Downstate Medical Center, Brooklyn, 450 Clarkson Avenue, Brooklyn, NY 11203, USA. aditya30887@gmail.com
Aditya
A
Tarigoppula
Nick
N
Rotella
Joseph T
JT
Francis
D062207:Brain-Computer Interfaces; D007858:Learning; D009044:Motor Cortex / Q000166:cytology / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D059629:Signal-To-Noise Ratio