title: From brain connectivity models to identifying foci of a neurological disorder.
abstract: We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. We employ the variational EM algorithm to fit the model and to identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia.
authors.affiliation: MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA.
authors.forename: Archana
authors.initials: A
authors.lastname: Venkataraman
authors.forename: Marek
authors.initials: M
authors.lastname: Kubicki
authors.forename: Polina
authors.initials: P
authors.lastname: Golland
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods; D016022:Case-Control Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008959:Models, Neurological; D009415:Nerve Net / Q000503:physiopathology; D009422:Nervous System Diseases / Q000175:diagnosis / Q000503:physiopathology*; D009434:Neural Pathways / Q000503:physiopathology; D016011:Normal Distribution; D011336:Probability; D012559:Schizophrenia / Q000175:diagnosis / Q000473:pathology; D012984:Software