pNet

pNet

pNet is a Python package of an algorithm for computing personalized, sparse, non-negative large-scale functional networks from functional magnetic resonance imaging (fMRI) data, facilitating effective characterization of individual variation in functional topography. The personalized functional networks are comparable across subjects while maintaining subject specific variation, reflected by their improved functional coherence compared with their group-level counterparts. The computation of personalized functional networks is accompanied by quality control, with visualization and quantification of their spatial correspondence and functional coherence in reference to their group-level counterparts.

The algorithm has been successfully applied to studies of individual variation in functional topography of association networks in youth, sex differences in the functional topography of association networks in youth, dissociable multi-scale patterns of development in personalized brain networks, functional network topography of psychopathology in youth, personalized functional brain network topography in youth cognition, and multiscale functional connectivity patterns of the aging brain.