Leveraging big data to map neurodevelopmental trajectories in pediatric anxiety

Anxiety disorders are the most prevalent psychiatric condition among youth, with symptoms commonly emerging prior to or during adolescence. Delineating neurodevelopmental trajectories associated with anxiety disorders is important for understanding the pathophysiology of pediatric anxiety and for early risk identification. While a growing literature has yielded valuable insights into the nature of brain structure and function in pediatric anxiety, progress has been limited by inconsistent findings and challenges common to neuroimaging research. In this review, we first discuss these challenges and the promise of 'big data' to map neurodevelopmental trajectories in pediatric anxiety. Next, we review evidence of age-related differences in neural structure and function among anxious youth, with a focus on anxiety-relevant processes such as threat and safety learning. We then highlight large-scale cross-sectional and longitudinal studies that assess anxiety and are well positioned to inform our understanding of neurodevelopment in pediatric anxiety. Finally, we detail relevant challenges of 'big data' and propose future directions through which large publicly available datasets can advance knowledge of deviations from normative brain development in anxiety. Leveraging 'big data' will be essential for continued progress in understanding the neurobiology of pediatric anxiety, with implications for identifying markers of risk and novel treatment targets.