Functional connectivity heterogeneity and consequences for clinical and cognitive prediction: Stage 2 registered...

Functional connectivity is frequently used to assess dynamic brain functioning and predict individual differences in behavioral outcomes, such as psychopathology. Inferences from functional connectivity analyses typically rely on group-averaged model statistics. However, heterogeneity between individuals may lead to group-level models that poorly reflect each individual. Poor individual-level precision may limit the ability to make individual-level predictions, which is necessary for key goals such as clinical translation. This registered report examined between-person heterogeneity in resting-state functional connectivity strength patterns by assessing similarity between group- and individual-level connectivity models in the Adolescent Brain Cognitive Development study. Using intraclass correlation coefficients, we found that a group-averaged region-of-interest-based connectivity model was a poor reflection of every individual. In contrast, a group-averaged model of between- and within-network connectivity was a good representation of most individuals. We then examined how individual-level distinctness from the group moderated predictive performance of several clinical and neurocognitive scales. Hypotheses that group-to-individual dissimilarity would worsen behavioral prediction were not supported with primary clinical outcomes. The little psychopathology reported in this sample was a notable limitation. In contrast, lower similarity to the group worsened prediction of performance on the pattern comparison test, providing minor support for hypotheses. Overall, results suggest that region-of-interest-based functional connectivity networks are highly heterogeneous and group-based models are inappropriate for individual-level inferences, but that network-based connectivity is largely similar across individuals. Additionally, we provide minor evidence of the impacts of heterogeneity on prediction that future studies should build on.