Abstract
Depression, non-suicidal self-injury (NSSI) and suicidal thoughts and behaviors (STB) commonly emerge in
youth and each represent important risk factors for death by suicide. Early detection and intervention has the
promise of altering trajectories, improving adult outcomes and preventing suicide. Brain networks implicated in
depression (frontal-limbic threat, cortico-striatal approach/reward and default mode) undergo significant
change during childhood and adolescence; the manner of how these changes unfold may be critical to
understanding the onset and course of depression, NSSI, and STB. The Adolescent Brain Cognitive
Development (ABCD) is a population-based study that is following over 11,000 children annually over 10
years, with clinical and neuroimaging data from the first three years already publicly available. Since ABCD
data collection spans a critical developmental window notable for significant rises in depression, NSSI and
STB, analyzing this data presents an ideal opportunity to characterize the links between neural network
changes and unfolding risk for suicide in youth. Resting-state fMRI (rs-fMRI) can be used to characterize brain
network structure and organization. While our laboratory and others have extensively applied standard
functional connectivity methods to characterize strength within depression networks using cross-sectional
designs, longitudinal designs are needed to understand now aberrant development in network strength may
contribute to onset depression, NSSI and STB. Recently, novel approaches have emerged to estimate
network flexibility from rsfMRI data. These include drawing from information theory to measure entropy of
brain signals and from dynamic connectivity analyses to measure state-switching, or shifts between brain
network configurations during rest. Our preliminary data point to inverse relationships between brain flexibility
(entropy and state-switching frequency) and depression, NSSI and STB in adolescents, suggesting a potential
neural mechanism for getting “stuck” in negative ways of thinking and feeling. We propose that individual
differences in the trajectory of neural network strength and flexibility changes across childhood and
adolescence may help explain the emergence of depression and suicide risk in adolescents. In our conceptual
model, inherited and environmental factors shape network developmental trajectories, which in turn underlie
the emergence of depression, NSSI and STB. This proposal seeks to delineate the neurodevelopmental
trajectories of strength and flexibility in fronto-limbic threat, cortico-striatal approach/reward and default mode
networks associated with the risk, onset and early course of depression, NSSI and STB in children and
adolescents in the ABCD study using novel analytic strategies. New insights from this study will provide the
foundation for designing personalized interventions to facilitate early detection of depression and suicide risk,
and to guide interventions capable of restoring healthy brain development and averting serious negative
outcomes including suicide.
