Dynamic Connectivity Regression: Determining State-Related Changes in Brain Connectivity

Posted: 23 May 2013 Last revised: 13 Jun 2013

See all articles by Ivor Cribben

Ivor Cribben

University of Alberta - Department of Finance and Statistical Analysis

Ragnheidur Haraldsdottir

Columbia University

Lauren Atlas

New York University (NYU)

Tor Wager

University of Colorado at Boulder

Martin Lindquist

Columbia University

Date Written: May 22, 2012

Abstract

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method's ability to observe how the networks between different brain regions changed with subjects' emotional state.

Keywords: Functional connectivity, Graphical lasso, Regression trees, Change point analysis, fMRI

Suggested Citation

Cribben, Ivor and Haraldsdottir, Ragnheidur and Atlas, Lauren and Wager, Tor and Lindquist, Martin, Dynamic Connectivity Regression: Determining State-Related Changes in Brain Connectivity (May 22, 2012). NeuroImage, Volume 61, Issue 4, 2012; University of Alberta School of Business Research Paper No. 20132013-201. Available at SSRN: https://ssrn.com/abstract=2268675

Ivor Cribben (Contact Author)

University of Alberta - Department of Finance and Statistical Analysis ( email )

2-32C Business Building
Edmonton, Alberta T6G 2R6
Canada

Ragnheidur Haraldsdottir

Columbia University

3022 Broadway
New York, NY 10027
United States

Lauren Atlas

New York University (NYU) ( email )

Bobst Library, E-resource Acquisitions
20 Cooper Square 3rd Floor
New York, NY 10003-711
United States

Tor Wager

University of Colorado at Boulder ( email )

Boulder, CO

Martin Lindquist

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

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