This research demonstrates a new method for testing brain-behavior associations in large neurodevelopmental cohorts, indicating improved accuracy and power.
Interpreting brain-behavior relationships through the lens of anatomical parcellations or functional networks is commonplace in human brain mapping. However, statistical approaches for testing whether brain-behavior associations are stronger (i.e., enriched) within a region of interest remain underdeveloped. Here, we propose a permutation-based approach for network enrichment testing using ordinal dominance curves (NETDOM). In simulation studies, we demonstrate that NETDOM properly controls the type I error rate-unlike other prominent enrichment methods-while exhibiting increased statistical power when enrichment occurs in a subset of in-network locations. Using data from two large-scale neurodevelopmental cohorts, we illustrate that NETDOM effectively detects enriched associations between structural and functional brain measures and neurocognitive performance.
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Hillman et al. (2026) studied this question.
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