Brain machine interfaces incorporating neural population dynamics

摘要

A brain-machine interface is provided that incorporates a neural dynamical structure in the control of a prosthetic device to restore motor function and is able to significantly enhance the control performance compared to existing technologies. In one example, a neural dynamical state is inferred from neural observations, which are obtained from a neural implant. In another example, the neural dynamical state can be inferred from both the obtained neural observations and from the kinematics. A controller interfaced with the prosthetic device uses the inferred neural dynamical state as input to the controller to control kinematic variables of the prosthetic device.

主权项

1. A brain-machine interface for restoring motor function, comprising:
(a) a neural implant for obtaining neural observations yk, wherein the neural observations are defined by a spike frequency of one or more neurons; (b) a computer-implemented inference system for inferring a neural dynamical state sk from the obtained neural observations (yk), wherein the inferred neural dynamical state is a state of a dynamical system which is defined by:
sk+1=f(sk)+g(uk)+nk yk=h(sk)+l(uk)+rk  where f(sk) is a function describing how the neural dynamical state evolves over time from sk to sk+1,
where h(sk) is a function mapping the neural dynamical state sk to the neural observations yk,where (uk) is an input to the dynamical system at time k,where g(uk) is a function mapping the input uk to the dynamical state Sk+1,where l(uk) is a function mapping the input uk to the neural observations yk,where nk and rk are noise variables, andwhere k denotes time; (c) a prosthetic device; and (d) a controller interfaced with the prosthetic device, wherein the inferred neural dynamical state (sk) is input to the controller to control kinematic variables (xk) of the prosthetic device.