Department of Psychological and Brain Sciences (Kliemann, Van De Water, Egger), Department of Psychiatry (Kliemann), and Iowa Neuroscience Institute (Kliemann, Van De Water), University of Iowa, Iowa City; Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena (Kliemann, Adolphs); School of Informatics, University of Edinburgh, Edinburgh (Galdi); McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Mass. (Jarecka, Ghosh); Division of Biology and Biological Engineering and Chen Neuroscience Institute, California Institute of Technology, Pasadena (Adolphs); Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston (Ghosh).
Am J Psychiatry. 2024 Dec 1;181(12):1076-1085. doi: 10.1176/appi.ajp.20230249. Epub 2024 Aug 29.
Three leading neurobiological hypotheses about autism spectrum disorder (ASD) propose underconnectivity between brain regions, atypical function of the amygdala, and generally higher variability between individuals with ASD than between neurotypical individuals. Past work has often failed to generalize, because of small sample sizes, unquantified data quality, and analytic flexibility. This study addressed these limitations while testing the above three hypotheses, applied to amygdala functional connectivity.
In a comprehensive preregistered study, the three hypotheses were tested in a subset (N=488 after exclusions; N=212 with ASD) of the Autism Brain Imaging Data Exchange data sets. The authors analyzed resting-state functional connectivity (FC) from functional MRI data from two anatomically defined amygdala subdivisions, in three hypotheses with respect to magnitude, pattern similarity, and variability, across different anatomical scales ranging from whole brain to specific regions and networks.
A Bayesian approach to hypothesis evaluation produced inconsistent evidence in ASD for atypical amygdala FC magnitude, strong evidence that the multivariate pattern of FC was typical, and no consistent evidence of increased interindividual variability in FC. The results strongly depended on analytic choices, including preprocessing pipeline for the neuroimaging data, anatomical specificity, and subject exclusions.
A preregistered set of analyses found no reliable evidence for atypical functional connectivity of the amygdala in autism, contrary to leading hypotheses. Future studies should test an expanded set of hypotheses across multiple processing pipelines, collect deeper data per individual, and include a greater diversity of participants to ensure robust generalizability of findings on amygdala FC in ASD.
关于自闭症谱系障碍（ASD）的三个主要神经生物学假说提出，大脑区域之间的连接不足、杏仁核功能异常以及 ASD 患者个体之间的变异性通常高于神经典型个体。过去的研究由于样本量小、数据质量未量化以及分析灵活性等原因，往往无法推广。本研究在测试上述三个假说的同时解决了这些限制，这些假说应用于杏仁核功能连接。
在一项全面的预先注册研究中，对自闭症脑成像数据交换数据集的一个子集（排除后 N=488；N=212 患有 ASD）进行了上述三个假说的测试。作者分析了来自两个解剖学定义的杏仁核亚区的静息状态功能磁共振成像数据的功能连接（FC），根据幅度、模式相似性和变异性，在三个假说中，在不同的解剖尺度上，从整个大脑到特定区域和网络，对 FC 进行了分析。
假说评估的贝叶斯方法在 ASD 中产生了不一致的证据，表明杏仁核 FC 幅度的异常，强有力的证据表明 FC 的多元模式是典型的，并且没有 FC 个体间变异性增加的一致证据。结果强烈依赖于分析选择，包括神经影像学数据的预处理管道、解剖学特异性和个体排除。
一组预先注册的分析发现，在自闭症中，杏仁核的功能连接没有异常的可靠证据，这与主要假说相反。未来的研究应该在多个处理管道中测试一组扩展的假说，为每个个体收集更深的数据，并包括更大的参与者多样性，以确保在 ASD 中杏仁核 FC 的发现具有稳健的可推广性。
