Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels.

ABSTRACT:

Background

Data-driven approaches can capture behavioral and biological variation currently unaccounted for by contemporary diagnostic categories, thereby enhancing the ability of neurobiological studies to characterize brain-behavior relationships.

Methods

A community-ascertained sample of individuals (N = 347, 18-59 years of age) completed a battery of behavioral measures, psychiatric assessment, and resting-state functional magnetic resonance imaging in a cross-sectional design. Bootstrap-based exploratory factor analysis was applied to 49 phenotypic subscales from 10 measures. Hybrid hierarchical clustering was applied to resultant factor scores to identify nested groups. Adjacent groups were compared via independent samples t tests and chi-square tests of factor scores,

SUBMITTER: Van Dam NT 

PROVIDER: S-EPMC5402759 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature