Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, MD, USA.
Department of Psychology, Royal Holloway, University of London, Egham, Surrey, UK.
Sci Rep. 2023 Mar 31;13(1):5303. doi: 10.1038/s41598-023-32249-5.
It is well-established that individuals with autism exhibit atypical functional brain connectivity. However, the role this plays in naturalistic social settings has remained unclear. Atypical patterns may reflect core deficits or may instead compensate for deficits and promote adaptive behavior. Distinguishing these possibilities requires measuring the 'typicality' of spontaneous behavior and determining how connectivity relates to it. Thirty-nine male participants (19 autism, 20 typically-developed) engaged in 115 spontaneous conversations with an experimenter during fMRI scanning. A classifier algorithm was trained to distinguish participants by diagnosis based on 81 semantic, affective and linguistic dimensions derived from their use of language. The algorithm's graded likelihood of a participant's group membership (autism vs. typically-developed) was used as a measure of task performance and compared with functional connectivity levels. The algorithm accurately classified participants and its scores correlated with clinician-observed autism signs (ADOS-2). In support of a compensatory role, greater functional connectivity between right inferior frontal cortex and left-hemisphere social communication regions correlated with more typical language behavior, but only for the autism group. We conclude that right inferior frontal functional connectivity increases in autism during communication reflect a neural compensation strategy that can be quantified and tested even without an a priori behavioral standard.
已有充分证据表明，自闭症患者表现出非典型的功能性大脑连接。然而，其在自然社交环境中的作用仍不清楚。异常模式可能反映了核心缺陷，也可能补偿缺陷并促进适应性行为。要区分这些可能性，需要测量自发行为的“典型性”，并确定连接与它的关系。39 名男性参与者（19 名自闭症，20 名发育正常）在 fMRI 扫描期间与实验者进行了 115 次自发对话。分类器算法经过训练，可以根据语言使用的 81 个语义、情感和语言维度来区分诊断为自闭症的参与者和发育正常的参与者。该算法对参与者群体成员身份（自闭症与发育正常）的分级可能性（自闭症与发育正常）被用作任务表现的衡量标准，并与功能连接水平进行了比较。该算法能够准确地对参与者进行分类，其分数与临床观察到的自闭症迹象（ADOS-2）相关。支持补偿作用的是，右侧下额叶皮层与左侧半球社会交流区域之间更强的功能连接与更典型的语言行为相关，但仅与自闭症组相关。我们的结论是，自闭症患者在交流期间右侧下额叶功能连接增加反映了一种神经补偿策略，即使没有先验的行为标准，也可以对其进行量化和测试。
