NEST: Network Enrichment Significance Testing of Brain-Phenotype Associations

Oregon Convention Center 

Maps of canonical functional brain networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from Gene Set Enrichment Analysis (GSEA, Subramanian et al. 2005), a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks. We apply NEST to study associations involving structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

enrichment

permutation testing

neuroimaging

brain networks

spatial data 

Biometrics Section