Data-driven parcellation and graph theory analyses to study adolescent mood and anxiety symptoms.

ABSTRACT: Adolescence is a period of rapid brain development when psychiatric symptoms often first emerge. Studying adolescents may therefore facilitate the identification of neural alterations early in the course of psychiatric conditions. Here, we sought to utilize new, high-quality brain parcellations and data-driven graph theory approaches to characterize associations between resting-state networks and the severity of depression, anxiety, and anhedonia symptoms-salient features across psychiatric conditions. As reward circuitry matures considerably during adolescence, we examined both Whole Brain and three task-derived reward networks. Subjects were 87 psychotropic-medication-free adolescents (age = 12-20) with diverse psychiatric conditions (n = 68) and healthy controls (n = 19). All completed

SUBMITTER: Ely BA 

PROVIDER: S-EPMC8093238 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature