FIGURE 6.

Decoding accuracies for different architectures during thumb and middle finger flexion task. Independent test sets results are shown for four different decoding architectures tested offline with SEEG and ECoG recordings in participant P3: the first row results are for a multi-class non-linear SVM using a gaussian kernel without feature selection, the second row are results for an architecture that performs repeatability-based feature selection (MCC > 0.6) and SVM, the third row shows results for a LSTM recurrent neural network without feature selection, and the last row shows results for an architecture using feature selection as described and a LSTM recurrent neural network.