title: Parcellating an individual subject's cortical and subcortical brain structures using snowball sampling of resting-state correlations.
abstract: We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability-reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units.
authors.affiliation: Department of Neurology, gwig@utdallas.edu.
authors.forename: Gagan S
authors.initials: GS
authors.lastname: Wig
authors.affiliation: Department of Neurology.
authors.forename: Timothy O
authors.initials: TO
authors.lastname: Laumann
authors.affiliation: Department of Neurology.
authors.forename: Alexander L
authors.initials: AL
authors.lastname: Cohen
authors.affiliation: Department of Neurology.
authors.forename: Jonathan D
authors.initials: JD
authors.lastname: Power
authors.affiliation: Department of Psychology, Washington University, St. Louis, MO, USA.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Nelson
authors.affiliation: Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO, USA and.
authors.forename: Matthew F
authors.initials: MF
authors.lastname: Glasser
authors.affiliation: Department of Neurology, Department of Radiology.
authors.forename: Francis M
authors.initials: FM
authors.lastname: Miezin
authors.affiliation: Department of Neurology, Department of Radiology.
authors.forename: Abraham Z
authors.initials: AZ
authors.lastname: Snyder
authors.affiliation: Department of Neurology, Department of Radiology, Department of Pediatrics.
authors.forename: Bradley L
authors.initials: BL
authors.lastname: Schlaggar
authors.affiliation: Department of Neurology, Department of Radiology, Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO, USA and Department of Psychology, Washington University, St. Louis, MO, USA.
authors.forename: Steven E
authors.initials: SE
authors.lastname: Petersen
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009434:Neural Pathways / Q000502:physiology; D009483:Neuropsychological Tests; D015203:Reproducibility of Results; D012146:Rest; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D055815:Young Adult
keywords: boundary mapping; brain area parcellation; brain networks; individual differences; resting-state functional correlations; snowball sampling