This unsupervised functional MRI adaptation tool (called UFA-Net) is designed to model spatio-temporal fMRI patterns of labeled source and unlabeled target samples via an attention-guided graph convolution module, and also leverage a maximum mean discrepancy constrained module for unsupervised cross-site feature alignment between two domains. This facilitates unsupervised functional MRI adaptation/harmonization for multi-site research.