title: Alzheimer's disease: connecting findings from graph theoretical studies of brain networks.
abstract: The interrelationships between pathological processes and emerging clinical phenotypes in Alzheimer's disease (AD) are important yet complicated to study, because the brain is a complex network where local disruptions can have widespread effects. Recently, properties in brain networks obtained with neuroimaging techniques have been studied in AD with tools from graph theory. However, the interpretation of graph alterations remains unclear, because the definition of connectivity depends on the imaging modality used. Here we examined which graph properties have been consistently reported to be disturbed in AD studies, using a heuristically defined "graph space" to investigate which theoretical models can best explain graph alterations in AD. Findings from structural and functional graphs point to a loss of highly connected areas in AD. However, studies showed considerable variability in reported group differences of most graph properties. This suggests that brain graphs might not be isometric, which complicates the interpretation of graph measurements. We highlight confounding factors such as differences in graph construction methods and provide recommendations for future research.
authors.affiliation: Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands. betty.tijms@gmail.com
authors.forename: Betty M
authors.initials: BM
authors.lastname: Tijms
authors.forename: Alle Meije
authors.initials: AM
authors.lastname: Wink
authors.forename: Willem
authors.initials: W
authors.lastname: de Haan
authors.forename: Wiesje M
authors.initials: WM
authors.lastname: van der Flier
authors.forename: Cornelis J
authors.initials: CJ
authors.lastname: Stam
authors.forename: Philip
authors.initials: P
authors.lastname: Scheltens
authors.forename: Frederik
authors.initials: F
authors.lastname: Barkhof
mesh_terms: D000544:Alzheimer Disease / Q000473:pathology*; D001921:Brain / Q000473:pathology* / Q000503:physiopathology; D004569:Electroencephalography; D006801:Humans; D008279:Magnetic Resonance Imaging; D015225:Magnetoencephalography; D008962:Models, Theoretical; D009415:Nerve Net / Q000473:pathology* / Q000503:physiopathology; D059906:Neuroimaging / Q000379:methods*