ED Fig. 3. Cross-subject decoding.

The GAN-augmentation, mutation-augmentation, stretch-augmentation, real-concatenation and real-only methods are shown in red, purple, orange, blue and green curves with an error bar in 5-fold cross-validation. The horizontal axis is the number of minutes of neural data from Monkey M used. The vertical axis is the correlation coefficient between the decoded kinematics and real kinematics on an independent test set from the Monkey M (mean + / − S.D., n = 5 folds). When the neural data from another subject is limited, synthesized spike trains that capture the neural attributes improve the cross-subject decoding performance on acceleration. Even with ample neural data for both subjects, the neural attributes learned from one subject can transfer some useful knowledge that improves the best achievable decoding performance on the acceleration of another subject.