GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy.
GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin, Turin, Italy.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2023 Nov;8(11):1075-1083. doi: 10.1016/j.bpsc.2022.01.007. Epub 2022 Feb 5.
Although neuroimaging research has identified atypical neuroanatomical substrates in individuals with autism spectrum disorder (ASD), it is at present unclear whether and to what extent disorder-selective gray matter alterations occur in this spectrum of conditions. In fact, a growing body of evidence shows a substantial overlap between the pathomorphological changes across different brain diseases, which may complicate identification of reliable neural markers and differentiation of the anatomical substrates of distinct psychopathologies.
Using a novel data-driven and Bayesian methodology with published voxel-based morphometry data (849 peer-reviewed experiments and 22,304 clinical subjects), this study performs the first reverse inference investigation to explore the selective structural brain alteration profile of ASD.
We found that specific brain areas exhibit a >90% probability of gray matter alteration selectivity for ASD: the bilateral precuneus (Brodmann area 7), right inferior occipital gyrus (Brodmann area 18), left cerebellar lobule IX and Crus II, right cerebellar lobule VIIIA, and right Crus I. Of note, many brain voxels that are selective for ASD include areas that are posterior components of the default mode network.
The identification of these spatial gray matter alteration patterns offers new insights into understanding the complex neurobiological underpinnings of ASD and opens attractive prospects for future neuroimaging-based interventions.
尽管神经影像学研究已经确定了自闭症谱系障碍(ASD)个体中异常的神经解剖学基础,但目前尚不清楚在这种情况下是否存在以及在何种程度上存在选择性的灰质改变。事实上,越来越多的证据表明,不同脑部疾病的病理形态变化之间存在实质性的重叠,这可能会使可靠的神经标志物的识别以及不同精神病理学的解剖学基础的区分变得复杂。
本研究使用一种新颖的数据驱动和贝叶斯方法,结合已发表的体素形态计量学数据(849 项同行评审实验和 22304 名临床受试者),首次进行了反向推理研究,以探索 ASD 的选择性结构脑改变特征。
我们发现特定的大脑区域表现出 >90%的灰质改变选择性概率,适用于 ASD:双侧楔前叶(Brodmann 区 7)、右侧下枕叶(Brodmann 区 18)、左侧小脑小叶 IX 和 Crus II、右侧小脑小叶 VIIIA 和右侧 Crus I。值得注意的是,许多对 ASD 具有选择性的大脑体素包括默认模式网络的后向成分区域。
这些空间灰质改变模式的确定为理解 ASD 的复杂神经生物学基础提供了新的见解,并为未来基于神经影像学的干预提供了有吸引力的前景。