1 Marcus Autism Center , Children's Healthcare of Atlanta, Atlanta, Georgia .
2 Division of Autism and Related Disabilities, Department of Pediatrics, Emory University School of Medicine , Atlanta, Georgia .
Brain Connect. 2018 Nov;8(9):537-548. doi: 10.1089/brain.2018.0592.
Although a large body of research has identified discrete neuroanatomical regions involved in social cognition and behavior (the "social brain"), the existing findings are based largely on studies of specific brain structures defined within the context of particular tasks or for specific types of social behavior. The objective of the current work was to view these regions as nodes of a larger collective network and to quantitatively characterize both the topology of that network and the relative criticality of its many nodes. Large-scale data mining was performed to generate seed regions of the social brain. High-quality diffusion MRI data of typical adults were used to map anatomical networks of the social brain. Network topology and nodal centrality were analyzed using graph theory. The structural social brain network demonstrates a high degree of global functional integration with strong local segregation. Bilateral dorsomedial prefrontal cortices and amygdala play the most central roles in the network. Strong probabilistic evidence supports modular divisions of the social brain into subnetworks bearing good resemblance to functionally classified clusters. The present network-driven approach quantifies the structural topology of the social brain as a whole. This work can serve as a critical benchmark against which to compare (1) developmental change in social brain topology over time (from infancy through adolescence and beyond) and (2) atypical network topologies that may be a sign or symptom of disorder (as in conditions such as autism, Williams syndrome, schizophrenia, and others).
尽管大量研究已经确定了涉及社会认知和行为的离散神经解剖区域(“社会大脑”),但现有研究结果主要基于特定任务或特定类型的社会行为背景下对特定大脑结构的研究。当前工作的目的是将这些区域视为更大的集体网络的节点,并定量描述该网络的拓扑结构及其许多节点的相对关键性。通过大规模数据挖掘生成社会大脑的种子区域。使用高质量的典型成年人弥散磁共振成像数据来绘制社会大脑的解剖网络。使用图论分析网络拓扑和节点中心度。结构社会大脑网络表现出高度的全局功能整合,具有强烈的局部隔离。双侧背内侧前额皮质和杏仁核在网络中起着最重要的作用。强有力的概率证据支持将社会大脑分为子网的模块划分,这些子网与功能分类簇非常相似。目前的网络驱动方法量化了整个社会大脑的结构拓扑。这项工作可以作为一个关键基准,(1)比较社会大脑拓扑结构随时间(从婴儿期到青春期及以后)的发展变化,(2)比较可能是障碍的标志或症状的异常网络拓扑(如自闭症、威廉姆斯综合征、精神分裂症等)。