title: A spectral graphical model approach for learning brain connectivity network of children's narrative comprehension.
abstract: Narrative comprehension is a fundamental cognitive skill that involves the coordination of different functional brain regions. We develop a spectral graphical model with model averaging to study the connectivity networks underlying these brain regions using fMRI data collected from a story comprehension task. Based on the spectral density matrices in the frequency domain, this model captures the temporal dependency of the entire fMRI time series between brain regions. A Bayesian model averaging procedure is then applied to select the best directional links that constitute the brain network. Using this model, brain networks of three distinct age groups are constructed to assess the dynamic change of network connectivity with respect to age.
authors.affiliation: Department of Management Science and Information Systems, Rutgers University, Piscataway, New Jersey 08854, USA. xiadonglin@gmail.com
authors.forename: Xiaodong
authors.initials: X
authors.lastname: Lin
authors.forename: Xiangxiang
authors.initials: X
authors.lastname: Meng
authors.forename: Prasanna
authors.initials: P
authors.lastname: Karunanayaka
authors.forename: Scott K
authors.initials: SK
authors.lastname: Holland
mesh_terms: D000161:Acoustic Stimulation / Q000379:methods*; D000293:Adolescent; D001499:Bayes Theorem; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D002648:Child; D002675:Child, Preschool; D032882:Comprehension / Q000502:physiology*; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D033262:Narration; D009415:Nerve Net / Q000502:physiology; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology