期刊
DEVELOPMENTAL COGNITIVE NEUROSCIENCE
卷 50, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.dcn.2021.100974
关键词
Anxiety disorders; Brain development; Childhood; Adolescence; Neuroimaging; Big data
资金
- National Institutes of Health (NIH) Director's Early Independence Award [DP5OD021370]
- Brain & Behavior Research Foundation (National Alliance for Research on Schizophrenia and Depression
- NARSAD)
- Jacobs Foundation Early Career Research Fellowship
- NIH Medical Scientist Training Program [T32]
- National Science Foundation Graduate Research Fellowship Program Award
- Massachusetts Institute of Technology (MIT) Henry E. Singleton Fellowship
Anxiety disorders are common among youth, with neurodevelopmental trajectories playing a key role in understanding pediatric anxiety. Challenges in neuroimaging research have limited progress in this area, but 'big data' holds promise for mapping these trajectories and informing risk identification and treatment targets. Age-related differences in neural structure and function, particularly in threat and safety learning, contribute to our understanding of pediatric anxiety and can be further elucidated through large-scale studies.
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.
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