Document Type

Article

Publication Date

10-1-2021

Publication Title

NeuroImage

Department

Department of Psychological and Brain Sciences

Abstract

Recent years have seen a surge of research on variability in functional brain connectivity within and between individuals, with encouraging progress toward understanding the consequences of this variability for cognition and behavior. At the same time, well-founded concerns over rigor and reproducibility in psychology and neuroscience have led many to question whether functional connectivity is sufficiently reliable, and call for methods to improve its reliability. The thesis of this opinion piece is that when studying variability in functional connectivity—both across individuals and within individuals over time—we should use behavior prediction as our benchmark rather than optimize reliability for its own sake. We discuss theoretical and empirical evidence to compel this perspective, both when the goal is to study stable, trait-level differences between people, as well as when the goal is to study state-related changes within individuals. We hope that this piece will be useful to the neuroimaging community as we continue efforts to characterize inter- and intra-subject variability in brain function and build predictive models with an eye toward eventual real-world applications.

DOI

10.1016/j.neuroimage.2021.118254

Original Citation

Emily S. Finn, Monica D. Rosenberg. Beyond fingerprinting: Choosing predictive connectomes over reliable connectomes, NeuroImage, Volume 239, 2021, 118254, https://doi.org/10.1016/j.neuroimage.2021.118254.

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