Method of Calibrating and Operating a Direct Neural Interface System

A method of calibrating a direct neural interface system comprising the steps of:

• a. acquiring electrophysiological signals representative of a neuronal activity of a subject's brain over a plurality of observation time windows and representing them in the form of a N+1-way tensor (X), N being greater or equal to one, called an observation tensor;
• b. acquiring data indicative of a voluntary action performed by said subject during each of said observation time windows, and organizing them in a vector or tensor (y), called an output vector or tensor;
• and
• c. determining a regression function of said output vector or tensor on said observation tensor;
• wherein said step c. includes performing multilinear decomposition of said observation tensor on a “score” vector (t), having a dimension equal to the number of said observation time windows, and N “weight” vectors (w1, w2, w3), wherein said “weights” vectors are chosen such as to maximize the covariance between said “score” vector and said output vector or tensor subject to a sparsity-promoting constraint or penalty.