Individual heterogeneity in the functional network topography of medial prefrontal cortex

Abstract

Abstract Human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are implicated in multiple cognitive functions, including subjective valuation processes and processes linked to the default network (DN). Our ability to interpret these seemingly co-localized effects is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was preferentially implicated in DN effects relative to valuation. We then used resting-state fMRI data and a data-driven network analysis algorithm, spectral partitioning, to partition mPFC and PCC into “DN” and “non-DN” subdivisions in individual participants (n = 100 from the Human Connectome Project). The spectral partitioning algorithm efficiently identified individual-level cortical subdivisions that were reliable across test/retest sessions and varied markedly across individuals, especially in mPFC. Our results point toward a new generation of strategies for assessing whether distinct cognitive functions engage common or distinct mPFC subregions.