Dual-Branch Spatio-Temporal Transformer for fMRI Brain-Disorder Diagnosis
A transformer architecture that classifies neurodevelopmental disorders from resting-state fMRI by jointly modelling spatial and temporal structure. Effective connectivity from Granger causality drives an eigenvector-centrality reordering of brain regions, giving the transformer a stable spatial ordering; a variable-window temporal module with cross-window attention captures multiscale dynamics of the BOLD time series; and parallel spatial and temporal branches are fused for classification. The concept covers how injecting network-derived spatial order and multiscale temporal windows into attention improves both accuracy and interpretability over connectivity-only models.
STARFormer: A Novel Spatio-Temporal Aggregation Reorganization Transformer of FMRI for Brain
STARFormer is a dual-branch spatio-temporal transformer for classifying brain disorders (autism spectrum disorder and ADHD) from resting-state fMRI. From each subject's BOLD time series it builds an …