RT Journal Article SR Electronic T1 A Guide for Quantifying and Optimizing Measurement Reliability for the Study of Individual Differences JF bioRxiv FD Cold Spring Harbor Laboratory SP 2022.01.27.478100 DO 10.1101/2022.01.27.478100 A1 Xu, Ting A1 Cho, Jae Wook A1 Kiar, Gregory A1 Bridgeford, Eric W. A1 Vogelstein, Joshua T. A1 Milham, Michael P. YR 2022 UL http://biorxiv.org/content/early/2022/01/28/2022.01.27.478100.abstract AB Characterizing individual variations is central to interpreting individual differences in neuroscience and clinical studies. While the field has examined multifaceted individual differences in brain functional organization, it is only in recent years that neuroimaging researchers have begun to place a priority on its quantification and optimization. Here, we highlight a potential analytic pitfall that can lead to contaminated estimates of inter-individual differences. We define a two-dimensional individual variation field map to decipher sources of individual variation and their relation to fingerprinting and measures of reliability. We illustrate theoretical gradient flow that represents the most effective direction for optimization when measuring individual differences. We propose to use this general framework for dissecting within- and between-individual variation and provide a supporting online tool for the purposes of guiding optimization efforts in biomarker discovery.Competing Interest StatementThe authors have declared no competing interest.