Psychiatric disorders show high rates of comorbidity and nonspecificity of presenting clinical symptoms, while demonstrating substantial heterogeneity within diagnostic categories. Notably, many of these psychiatric disorders first manifest in youth. We review progress and next steps in efforts to parse heterogeneity in psychiatric symptoms in youths by identifying abnormalities within neural circuits. To address this fundamental challenge in psychiatry, a number of methods have been proposed. We provide an overview of these methods, broadly organized into dimensional versus categorical approaches and single-view versus multiview approaches. Dimensional approaches including factor analysis and canonical correlation analysis aim to capture dimensional associations between psychopathology and brain measures across a continuous spectrum from health to disease. In contrast, categorical approaches, such as clustering and community detection, aim to identify subtypes of individuals within a class of symptoms or brain features. We highlight several studies that apply these methods to samples of youths and discuss issues to consider when using these approaches. Finally, we end by highlighting avenues for future research.

中文翻译：

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定义与青少年精神病理学相关的常见和可分离神经生物学缺陷的方法

精神疾病表现出较高的共病率和临床症状的非特异性，同时在诊断类别中表现出很大的异质性。值得注意的是，许多精神疾病首先出现在青少年时期。我们回顾了通过识别神经回路异常来解析青少年精神症状异质性的进展和后续步骤。为了解决精神病学中的这一基本挑战，人们提出了多种方法。我们提供了这些方法的概述，大致分为维度方法与分类方法以及单视图与多视图方法。包括因子分析和典型相关分析在内的维度方法旨在捕获从健康到疾病的连续范围内的精神病理学和大脑测量之间的维度关联。相比之下，分类方法（例如聚类和社区检测）旨在识别一类症状或大脑特征中个体的亚型。我们重点介绍了几项将这些方法应用于青少年样本的研究，并讨论了使用这些方法时需要考虑的问题。最后，我们最后强调了未来研究的途径。