A method for using blocked and event-related fMRI data to study "resting state" functional connectivity

Damien A. Fair, Bradley L. Schlaggar, Alexander L. Cohen, Francis M. Miezin, Nico U.F. Dosenbach, Kristin K. Wenger, Michael D. Fox, Abraham Z. Snyder, Marcus E. Raichle, Steven E. Petersen

Research output: Contribution to journalArticle

374 Scopus citations

Abstract

Resting state functional connectivity MRI (fcMRI) has become a particularly useful tool for studying regional relationships in typical and atypical populations. Because many investigators have already obtained large data sets of task-related fMRI, the ability to use this existing task data for resting state fcMRI is of considerable interest. Two classes of data sets could potentially be modified to emulate resting state data. These data sets include: (1) "interleaved" resting blocks from blocked or mixed blocked/event-related sets, and (2) residual timecourses from event-related sets that lack rest blocks. Using correlation analysis, we compared the functional connectivity of resting epochs taken from a mixed blocked/event-related design fMRI data set and the residuals derived from event-related data with standard continuous resting state data to determine which class of data can best emulate resting state data. We show that, despite some differences, the functional connectivity for the interleaved resting periods taken from blocked designs is both qualitatively and quantitatively very similar to that of "continuous" resting state data. In contrast, despite being qualitatively similar to "continuous" resting state data, residuals derived from event-related design data had several distinct quantitative differences. These results suggest that the interleaved resting state data such as those taken from blocked or mixed blocked/event-related fMRI designs are well-suited for resting state functional connectivity analyses. Although using event-related data residuals for resting state functional connectivity may still be useful, results should be interpreted with care.

Original languageEnglish (US)
Pages (from-to)396-405
Number of pages10
JournalNeuroImage
Volume35
Issue number1
DOIs
StatePublished - Mar 2007
Externally publishedYes

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