title: Decomposing spatiotemporal brain patterns into topographic latent sources.
abstract: This paper extends earlier work on spatial modeling of fMRI data to the temporal domain, providing a framework for analyzing high temporal resolution brain imaging modalities such as electroencapholography (EEG). The central idea is to decompose brain imaging data into a covariate-dependent superposition of functions defined over continuous time and space (what we refer to as topographic latent sources). The continuous formulation allows us to parametrically model spatiotemporally localized activations. To make group-level inferences, we elaborate the model hierarchically by sharing sources across subjects. We describe a variational algorithm for parameter estimation that scales efficiently to large data sets. Applied to three EEG data sets, we find that the model produces good predictive performance and reproduces a number of classic findings. Our results suggest that topographic latent sources serve as an effective hypothesis space for interpreting spatiotemporal brain imaging data.
authors.affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: sjgershm@mit.edu.
authors.forename: Samuel J
authors.initials: SJ
authors.lastname: Gershman
authors.affiliation: Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08540, USA. Electronic address: blei@cs.princeton.edu.
authors.forename: David M
authors.initials: DM
authors.lastname: Blei
authors.affiliation: Department of Psychology and Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA. Electronic address: knorman@princeton.edu.
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Norman
authors.affiliation: Department of Psychology, The Ohio State University, Columbus, OH 43210, USA. Electronic address: sederberg.1@osu.edu.
authors.forename: Per B
authors.initials: PB
authors.lastname: Sederberg
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004569:Electroencephalography; D018913:Event-Related Potentials, P300; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D013997:Time Factors; D055815:Young Adult
keywords: Bayesian; Decoding; Multivariate; Variational; fMRI