title: Change-point detection of cognitive states across multiple trials in functional neuroimaging.
abstract: Many functional neuroimaging-based studies involve repetitions of a task that may require several phases, or states, of mental activity. An appealing idea is to use relevant brain regions to identify the states. We developed a novel change-point methodology that adapts to the repeated trial structure of such experiments by assuming the number of states stays fixed across similar trials while allowing the timing of change-points to change across trials. Model fitting is based on reversible-jump MCMC. Simulation studies verified its ability to identify change-points successfully. We applied this technique to data collected via functional magnetic resonance imaging (fMRI) while each of 20 subjects solved unfamiliar arithmetic problems. Our methodology supplies both a summary of state dimensionality and uncertainty assessments about number of states and the timing of state transitions. Copyright © 2016 John Wiley & Sons, Ltd.
authors: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, U.S.A.|Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, U.S.A.
authors: F Spencer
authors: FS
authors: Koerner
authors: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, U.S.A.|Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, U.S.A.|Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, U.S.A.
authors: John R
authors: JR
authors: Anderson
authors: Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, U.S.A.
authors: Jon M
authors: JM
authors: Fincham
authors: Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, U.S.A.|Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, U.S.A.|Department of Machine Learning, Carnegie Mellon University, Pittsburgh, PA, U.S.A.
authors: Robert E
authors: RE
authors: Kass
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology; D002986:Clinical Trials as Topic; D003071:Cognition / Q000502:physiology; D003627:Data Interpretation, Statistical; D059907:Functional Neuroimaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D025341:Principal Component Analysis; D035501:Uncertainty
keywords: Bayesian inference; change-point detection; functional magnetic resonance imaging; reversible-jump MCMC; segmentation