Uncovering functional connectivity patterns predictive of cognition in youth using interpretable predictive modeling.

ABSTRACT: Brain-wide association studies using functional MRI have advanced our understanding of how behavioral traits relate to individual variability in brain function. These studies typically identify functional connectivity (FC) patterns linked to behavioral traits using either whole-brain or region-wise predictive models. However, whole-brain models often struggle with generalizability and interpretability due to the high dimensionality of FC data, while region-wise models isolate predictions, limiting their ability to capture the integrated contributions of brain-wide FC patterns. In this study, we introduce an interpretable predictive model that learns fine-grained FC patterns predictive of behavioral traits, jointly at the regional and participant levels, to characterize the overall associat

SUBMITTER: Li H 

PROVIDER: S-EPMC12557476 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature