BCI decoding framework.

Top figure depicts the general setting where neural activity is taken together with prior information to decode an estimate of the underlying intention. When in closed loop, sensory (visual) feedback is provided which can allow the user to modify intention and also permit changes to the encoding model. Bottom figure depicts the steady state Kalman filter (SSKF), a simple exemplar of the general setting in which A, F, & G are matrices which multiply the vectors x_t, y_t, or

x^

t−1

. Contributions from Fy_t and

G

x^

t−1

combine additively.