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.

焦虑症是青少年中最普遍的精神疾病，症状通常在青春期之前或期间出现。描绘与焦虑症相关的神经发育轨迹对于了解儿科焦虑症的病理生理学和早期风险识别非常重要。虽然越来越多的文献对儿科焦虑中大脑结构和功能的性质产生了宝贵的见解，但进展受到不一致的发现和神经影像学研究常见的挑战的限制。在这篇综述中，我们首先讨论了这些挑战以及“大数据”在绘制儿科焦虑症的神经发育轨迹方面的前景。接下来，我们回顾了焦虑青年中与年龄相关的神经结构和功能差异的证据，重点关注与焦虑相关的过程，例如威胁和安全学习。然后，我们重点介绍评估焦虑的大规模横断面和纵向研究，这些研究可以很好地帮助我们了解儿科焦虑中的神经发育。最后，我们详细介绍了“大数据”的相关挑战，并提出了未来的方向，大型公开可用的数据集可以通过这些方向推进对焦虑中偏离规范大脑发育的认识。利用“大数据”对于理解儿科焦虑的神经生物学的持续进展至关重要，这对于识别风险标志物和新的治疗目标具有重要意义。然后，我们重点介绍评估焦虑的大规模横断面和纵向研究，这些研究可以很好地帮助我们了解儿科焦虑中的神经发育。最后，我们详细介绍了“大数据”的相关挑战，并提出了未来的方向，大型公开可用的数据集可以通过这些方向推进对焦虑中偏离规范大脑发育的认识。利用“大数据”对于理解儿科焦虑的神经生物学的持续进展至关重要，这对于识别风险标志物和新的治疗目标具有重要意义。然后，我们重点介绍评估焦虑的大规模横断面和纵向研究，这些研究可以很好地帮助我们了解儿科焦虑中的神经发育。最后，我们详细介绍了“大数据”的相关挑战，并提出了未来的方向，大型公开可用的数据集可以通过这些方向推进对焦虑中偏离规范大脑发育的认识。利用“大数据”对于理解儿科焦虑的神经生物学的持续进展至关重要，这对于识别风险标志物和新的治疗目标具有重要意义。