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

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.