title: Directed progression brain networks in Alzheimer's disease: properties and classification.
abstract: This article introduces a new approach in brain connectomics aimed at characterizing the temporal spread in the brain of pathologies like Alzheimer's disease (AD). The main instrument is the development of "directed progression networks" (DPNets), wherein one constructs directed edges between nodes based on (weakly) inferred directions of the temporal spreading of the pathology. This stands in contrast to many previously studied brain networks where edges represent correlations, physical connections, or functional progressions. In addition, this is one of a few studies showing the value of using directed networks in the study of AD. This article focuses on the construction of DPNets for AD using longitudinal cortical thickness measurements from magnetic resonance imaging data. The network properties are then characterized, providing new insights into AD progression, as well as novel markers for differentiating normal cognition (NC) and AD at the group level. It also demonstrates the important role of nodal variations for network classification (i.e., the significance of standard deviations, not just mean values of nodal properties). Finally, the DPNets are utilized to classify subjects based on their global network measures using a variety of data-mining methodologies. In contrast to most brain networks, these DPNets do not show high clustering and small-world properties.
authors.affiliation: 1 International Computer Science Institute , Berkeley, California.
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Friedman
authors.forename: Karl
authors.initials: K
authors.lastname: Young
authors.forename: Danial
authors.initials: D
authors.lastname: Asif
authors.forename: Inderjit
authors.initials: I
authors.lastname: Jutla
authors.forename: Michael
authors.initials: M
authors.lastname: Liang
authors.forename: Scott
authors.initials: S
authors.lastname: Wilson
authors.forename: Adam S
authors.initials: AS
authors.lastname: Landsberg
authors.forename: Norbert
authors.initials: N
authors.lastname: Schuff
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000473:pathology*; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods; D002540:Cerebral Cortex / Q000473:pathology; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D009415:Nerve Net / Q000473:pathology*; D009434:Neural Pathways / Q000473:pathology
keywords: Alzheimer's disease; amyloid plaques; brain connectomics; cortical thickness; directed networks