Multi-subject data augmentation for target subject semantic decoding with deep multi-view adversarial learning

•We provide a new insight into the problem of brain semantic decoding. That is, we introduce a multi-subject fMRI data augmentation method to improve the performance of the target subject.•A latent space is introduced to solve the problem of feature mismatch and multiple GAN architectures are introduced to solve the problem of distribution mismatch between distinct subjects.•The experimental results show that our method is better than the baseline methods, especially when the size of the training data is small.