Journal
PSYCHOLOGICAL SCIENCE
Volume 31, Issue 7, Pages 792-806Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0956797620916786
Keywords
neuroimaging; individual differences; statistical analysis; cognitive neuroscience
Categories
Funding
- National Institute on Aging (NIA) [R01AG049789, R01AG032282]
- UK Medical Research Council [P005918]
- New Zealand Health Research Council
- New Zealand Ministry of Business, Innovation and Employment (MBIE)
- National Science Foundation Graduate Research Fellowship [DGE-1644868]
- NIH Blueprint for Neuroscience Research
- McDonnell Center for Systems Neuroscience at Washington University
- MRC [MR/P005918/1] Funding Source: UKRI
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Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task functional MRI (fMRI) is a major focus of biomarker development; however, the reliability of task fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N = 1,008) revealed poor overall reliability-mean intraclass correlation coefficient (ICC) = .397. Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected by the Human Connectome Project (N = 45) and the Dunedin Study (N = 20) were poor (ICCs = .067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or for individual-differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.
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