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）和弥散张量成像（DTI）文献表明，自闭症谱系障碍（ASD）的认知、社会交际和感觉运动障碍与大脑网络连接受损有关。然而，迄今为止很少有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）提供的动态处理测量相结合。我们建议使用fcMRI、DTI和MEG对ASD的连通性进行全面调查，选择一个任务范式来识别视觉、词汇语义、执行和运动（VLSEM）电路，用于示例性网络节点集。来自60名ASD青少年和60名正常发育（TD）参与者的数据将被获取，以实现四个具体目标：(1)使用fMRI识别词汇-语义决策过程中VLSEM回路的节点，并检查该回路内以及节点与其余大脑之间的功能连接。(2)利用MEG对VLSEM电路进行时域和时频分析，包括在多个频带内锁相共振，研究VLSEM电路的动态、时空特性。(3)使用概率DTI束状图检查VLSEM电路内连接的解剖学完整性，并测试fcMRI， MEG和DTI测量之间的联系。(4)探讨ASD组功能、解剖连通性和动态加工与诊断和神经心理学指标的关系。该研究将为改进和全面了解ASD的脑网络异常提供多模态成像证据。这些证据对于识别自闭症谱系障碍的生物标记物尤其重要，包括那些可能区分自闭症生物学亚型的生物标记物。对寻找生物标记物的贡献将有益于公共卫生，因为这些生物标记物将对遗传和疾病的鉴定至关重要

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.