Yue Xipeng, Zhang Ge, Li Xiaochen, Shen Yu, Wei Wei, Bai Yan, Luo Yu, Wei Huanhuan, Li Ziqiang, Zhang Xianchang, Wang Meiyun
Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, 7 Weiwu Road, 450000, Zhengzhou, China.
Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China.
Clin Neuroradiol. 2022 Dec;32(4):1087-1096. doi: 10.1007/s00062-022-01173-y. Epub 2022 May 11.
This study sought to explore changes of brain dynamic functional network connectivity (dFNC) in adults with autism spectrum disorder (ASD) and investigate their relationship with clinical manifestations.
Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 78 adult ASD patients from autism brain imaging data exchange datasets, and 65 age-matched healthy controls subjects from the local community. Independent component analysis was conducted to evaluate dFNC patterns on the basis of 13 independent components (ICs) within 11 resting-state networks (RSN), namely, auditory network (AUDN), basal ganglia network (BGN), language network (LN), sensorimotor network (SMN), precuneus network (PUCN), salience network (SN), visuospatial network (VSN), dorsal default mode network (dDMN), high visual network (hVIS), primary visual network (pVIS), ventral default mode network (vDMN). Fraction time, mean dwell time, number of transitions, and RSN connectivity were calculated for group comparisons. Correlation analyses were performed between abnormal metrics and autism diagnostic observation schedule (ADOS) scores.
Compared with controls, ASD patients had higher fraction time and mean dwell time in state 2 (P = 0.017, P = 0.014). Reduced dFNC was found in the SMN with PUCN, SMN with hVIS, and increased dFNC was observed in the dDMN with SN in state 2 in the ASD group. Fraction time and mean dwell time was positively correlated with stereotyped behavior scores of ADOS.
The findings demonstrated the importance of evaluating transient alterations in specific neural networks of adult ASD patients. The abnormal metrics and connectivity may be related to symptoms such as stereotyped behavior.
本研究旨在探索自闭症谱系障碍(ASD)成人患者脑动态功能网络连接性(dFNC)的变化,并研究其与临床表现的关系。
从自闭症脑成像数据交换数据集获取78例成年ASD患者的静息态功能磁共振成像(rs-fMRI)数据,并从当地社区招募65例年龄匹配的健康对照者。基于11个静息态网络(RSN)中的13个独立成分(IC)进行独立成分分析,以评估dFNC模式,这11个静息态网络分别为听觉网络(AUDN)、基底神经节网络(BGN)、语言网络(LN)、感觉运动网络(SMN)、楔前叶网络(PUCN)、突显网络(SN)、视觉空间网络(VSN)、背侧默认模式网络(dDMN)、高级视觉网络(hVIS)、初级视觉网络(pVIS)、腹侧默认模式网络(vDMN)。计算分数时间、平均停留时间、转换次数和RSN连接性以进行组间比较。对异常指标与自闭症诊断观察量表(ADOS)评分进行相关性分析。
与对照组相比,ASD患者在状态2下的分数时间和平均停留时间更高(P = 0.017,P = 0.014)。在ASD组中,状态2下SMN与PUCN、SMN与hVIS之间的dFNC降低,dDMN与SN之间的dFNC增加。分数时间和平均停留时间与ADOS的刻板行为评分呈正相关。
研究结果表明评估成年ASD患者特定神经网络的短暂变化具有重要意义。异常指标和连接性可能与刻板行为等症状有关。