Automatic sleep staging using fMRI functional connectivity data

► First application of a machine learning algorithm for sleep staging based on fMRI. ► Classification based on BOLD functional connectivity allows accuracies over 80%. ► Classifer tested on two independent datasets without accuracy loss. ► A sliding window approach allows to reconstruct hypnograms from short fMRI epochs. ► Automated classification after training.