Integrity and Dynamic Processing Efficiency of Networks in ASD

描述(由申请人提供)：越来越多的功能连接MRI(FcMRI)和扩散张量成像(DTI)文献表明，自闭症谱系障碍(ASD)的认知、社交和感觉运动障碍与大脑网络连接受损有关。然而，到目前为止，很少有ASD研究将功能和解剖连接的测量结合起来。更重要的是，没有研究将这些与脑磁图(MEG)提供的动态处理措施相结合。我们建议使用fcMRI、DTI和MEG来全面研究ASD中的连通性，选择一种任务范式来识别一组示例性网络节点的视觉、词汇语义、执行和运动(VLSEM)电路。来自60名患有自闭症的青少年和60名匹配的典型发展中(TD)参与者的数据将被获取以追求四个具体目标：(1)在词汇-语义判断过程中使用fMRI识别VLSEM电路的节点，并检查该电路内以及节点与剩余大脑之间的功能连接。(2)研究了超大规模扫描电子显微镜电路的动态、时空特性，利用脑磁图对电路进行了时-频分析，包括多个频段的锁相共振。(3)使用概率DTI纤维束造影术检查VLSEM回路内连接的解剖完整性，并测试fcMRI、MEG和DTI测量之间的联系。(4)探讨ASD组的功能和解剖连通性以及动态加工与诊断和神经心理学指标的关系。这项研究将为改进和全面了解ASD的脑网络异常提供多模式成像证据。这些证据对于确定自闭症的生物标记物特别重要，包括那些可以区分该疾病的生物学亚型的标记物。对寻找生物标记物的贡献将对公众健康有益，因为这种生物标记物将对识别遗传和 ASD的其他原因需要有针对性的治疗。

DESCRIPTION (provided by applicant): A growing functional connectivity MRI (fcMRI) and diffusion tensor imaging (DTI) literature suggests that cognitive, sociocommunicative, and sensorimotor impairments in autism spectrum disorders (ASD) are associated with impaired brain network connectivity. However few ASD studies to date have combined measures of functional and anatomical connectivity. Even more importantly, there are no studies combining these with measures of dynamic processing, as provided by magnetoencephalography (MEG). We propose to use fcMRI, DTI, and MEG for a comprehensive investigation of connectivity in ASD, selecting a task paradigm to identify a visual, lexico-semantic, executive, and motor (VLSEM) circuit for an exemplary set of network nodes. Data from sixty adolescents with ASD and 60 matched typically developing (TD) participants will be acquired to pursue four specific aims: (1) To identify nodes of a VLSEM circuit using fMRI during lexical-semantic decision and to examine the functional connectivity within this circuit and between nodes and the remaining brain. (2) To examine the dynamic, spatiotemporal characteristics of the VLSEM circuit, using MEG in time-domain and time-frequency analyses including phase-locked co-oscillation in several frequency bands. (3) To examine the anatomical integrity of connections within the VLSEM circuit using probabilistic DTI tractography, and to test for links between fcMRI, MEG, and DTI measures. (4) To examine the relation of functional and anatomical connectivity as well as dynamic processing with diagnostic and neuropsychological measures in the ASD group. The study will contribute multimodal imaging evidence for an improved and comprehensive understanding of brain network abnormalities in ASD. Such evidence will be particularly important for the identification of biomarkers of ASD, including those which may distinguish biological subtypes of the disorder. The contribution to the search for biomarkers will have public health benefit because such biomarkers will be crucial for the identification of genetic and other causes of ASD needed for targeted treatment.