【作者】 贾会宾； 李艳玮； 禹东川；

【Author】 Huibin Jia;Yanwei Li;Dongchuan Yu;Key Laboratory of Child Development and Learning Science of Ministry of Education (Southeast University);School of Biological Sciences & Medical Engineering, Southeast University;

【机构】 儿童发展与学习科学教育部重点实验室(东南大学)； 东南大学生物科学与医学工程学院；

【摘要】 孤独症谱系障碍是一种广泛性发育障碍,主要表现为社会交往和沟通障碍、重复刻板行为和兴趣狭隘等特征。研究者提出了多种理论来解释孤独症的神经生物学机制。越来越多的证据支持如下理论,即孤独症谱系障碍与患者大脑中异常的神经连接密切相关。本研究使用fNIRS技术采集了孤独症儿童和年龄与性别匹配的正常发育儿童观看卡通片时的氧合血红蛋白浓度变化值。为了对这些孤独症儿童fNIRS信号异常的功能连接进行分析,本研究分析了氧合血红蛋白浓度的空间复杂性。大脑信号的空间复杂性指的是各个脑区信号的异质性,并与这些脑区总体的功能连接水平成反比。传统的空间复杂性指标(即Omega复杂性)具有一定局限性,例如它们对选取的脑区的数量很敏感。本研究提出一种结合主成分分析和标准熵计算空间复杂性的新方法。此方法包括一系列的空间复杂性分析指标,例如全脑空间复杂性、区域空间复杂性、局部复杂性差值以及这些指标的变异性。全脑空间复杂性和区域空间复杂性分别衡量的是全脑所有通道和某个脑区内所有通道的空间复杂性(或总体的功能连接水平)。某个脑区的局部复杂性差值指的是某脑区的活动对全脑总体连接水平的贡献。本研究发现:(1)孤独症组的右侧前额的区域空间复杂性和局部复杂性差值与正常发育儿童相比显著更高;(2)孤独症组的右侧颞叶的局部复杂性差值的变异值显著高于正常发育儿童。这些结果证明了这个新方法的价值与意义,并且证明了右侧前额叶和右侧颞叶的异常功能连接是孤独症的重要特征。更多还原

【Abstract】 Autism Spectrum Disorder(ASD) describes a range of polygenetic developmental disorders that are characterized by impairments in social communicative development, along with repetitive stereotyped behaviors and/or restricted interests. A series of theories have been proposed to explain the underpinning neurobiological mechanisms of ASD. Increasing evidence support the theory that the ASD is closely associated to the aberrant neural connectivity in autistic persons’ brains. In the current study, the concentration changes of oxy-hemoglobin(oxy-Hb) of children with ASD and age-and gender-matched typically developing(TD) children were recorded using functional near-infrared spectroscopy(fNIRS), when they were watching cartoon. In order to analysis the aberrant functional connectivity of f NIRS signals in these children with ASD, the spatial complexity of oxy-Hb was studied. The spatial complexity analysis of brain signals can be defined as the heterogeneity of neural signals in different brain regions and varies inversely with the global functional connectivity level across distinct regions. Traditional spatial complexity measures(i.e., measures based on omega complexity) have certain limitation, i.e., they are sensitive to the number of brain regions selected. In the current study, a novel approach, combining principal component analysis and normalized entropy, was proposed to estimate the spatial complexity of brain signals, which included several spatial complexity metrics: global spatial complexity(GSC), regional spatial complexity(RSC), local complexity differential(LCD) and their variabilities. The GSC and RSC could be used to quantify spatial complexity or the global functional connectivity level across all channels and across all channels within a given region, respectively. The LCD of a given brain region could estimate the contribution of activities of specific region to the global functional connectivity of all regions. This study found that(1) the RSC and LCD of right prefrontal cortex(i.e., RP-RSC and RP-LCD) were significantly higher in ASD group, compared to those in TD group;(2) the variability of local complexity differential of right temporal lobe(RT-v LCD) was significantly higher in ASD group. These results not only proved the value and significance of the novel approach, but also proved that aberrant neural connectivity of right prefrontal cortex and right temporal lobe was important feature in ASD.更多还原