title: Networks of anatomical covariance.
abstract: Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique.
authors.affiliation: McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Canada. alan.evans@mcgill.ca
authors.forename: Alan C
authors.initials: AC
authors.lastname: Evans
mesh_terms: D000818:Animals; D001921:Brain / Q000473:pathology* / Q000503:physiopathology*; D001927:Brain Diseases / Q000473:pathology* / Q000503:physiopathology*; D063132:Connectome / Q000379:methods*; D006801:Humans; D008953:Models, Anatomic; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net / Q000473:pathology* / Q000503:physiopathology*
keywords: Connectivity; Cortical thickness; Structural covariance