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Title *

Test-Retest Reliability in Functional Magnetic Resonance Imaging: Impact of Analytical Decisions on Individual and Group Estimates in the Monetary Incentive Delay Taskuse asterix (*) to get italics

Authors *

Michael I. Demidenko, Jeanette A. Mumford, Russell A. PoldrackPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2023

Picture

Abstract *

<p>Empirical studies reporting low test-retest reliability of individual neural estimates in functional magnetic resonance imaging (fMRI) data have resurrected interest among cognitive neuroscientists in methods that may improve reliability in fMRI. Over the last decade, several individual studies have reported that modeling decisions, such as smoothing, motion correction and contrast selection, may improve estimates of test-retest reliability of neural estimates. However, it remains an empirical question whether certain analytic decisions consistently improve individual and group level reliability estimates in an fMRI task across multiple large, independent samples. This study uses three independent samples (approximate Ns: 65, 150 & 2,000) that collected the same task (Monetary Incentive Delay task) across two runs and two sessions to evaluate the effects of analytic decisions on the individual (continuous) and group (binary/continuous) reliability estimates of neural activity in task fMRI. The analytic decisions in this study vary across four categories: smoothing kernel (five options), motion correction (six options), task parameterizing (three options) and task contrasts (four options), totaling 360 different modeling permutations. Continuous and binary reliability estimates of neural activity are calculated within and between sessions and associations between modeling decisions and reliability estimates (e.g., intraclass correlation (ICC), Jaccard similarity) are reported using specification curve analyses and hierarchical linear modeling. In addition to examining whether specific modeling decisions result in higher reliability, this study also evaluates an underexplored issue: How modeling decisions impact within- and between-subject variance and at which sample size the ICC stabilizes in fMRI data.</p>

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Keywords (optional)

Test-retest Reliability, Intraclass Correlation, Jaccard Similarity, Functional Magnetic Resonance Imaging, Monetary Incentive Delay task, Individual Differences

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Life Sciences, Social sciences

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Submission date

2023-04-17 22:27:54

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Dorothy Bishop

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