Intrinsic Brain Architecture of Young Children with Autism While Awake and Asleep

摘要 功能神经成像正在日益增强我们对自闭症谱系障碍(ASD)的理解 断线综合症，但由于它的要求，大多数研究都集中在成年人或年龄较大的儿童。 在自然睡眠期间进行功能神经成像可以对幼儿和婴儿进行研究。 鉴于ASD的发病较早，这样的研究对于识别生物标志物可能是至关重要的。然而， 关于睡眠中的发现可以推广到清醒状态的假设还没有得到证实 经过系统测试。这一探索性的建议是通过研究来填补这一重要空白的第一步 患有自闭症的儿童有两种状态--清醒和自然睡眠--使用静息状态功能 磁共振成像(R-fMRI)。通过量化整个网络的内部功能连接性(IFC) 大脑，R-fMRI提供了关于大脑功能电路的丰富信息。虽然两者之间的差异 到目前为止，已经描述了健康成年人的睡眠和清醒的R-fMRI，IFC测量了年轻睡眠的情况 患有自闭症的儿童还没有被系统地描述出来，也没有被对比过 保持清醒。因此，我们的首要目标是提供一个初步的系统特征 ASD儿童全脑IFC在不同状态(清醒和睡眠)的稳定性(可靠性)。我们建议 收集至少20名年龄在66岁至66岁之间的ASD儿童在清醒和自然睡眠时的R-fMRI 90个月--从儿童清醒时可以成功扫描的最小年龄开始。我们会 使用结构和功能分割单位测量全脑IFC 文学。我们还将计算其他全脑体素的内在大脑功能结构的测量 以前被报告为ASD异常，并捕获了未以其他方式表征的特定属性 通过传统的相关分析。其中包括体素镜像同伦连接、地区性 齐性、低频波动的分数幅度、度中心性和独立性 成分分析。我们的假设生成的目的是(1)检验两国之间的显著差异 ASD儿童的觉醒和睡眠，以及(2)系统地表征稳定性(可靠性) 不同状态(睡眠、清醒)的R-fMRI测量的个体间差异 相关系数。我们还将讨论有关不同分割的影响的其他问题。 系统关于稳定性的测量，大脑行为稳定性与ASD测量的关系，并推导出 期内重测信度的初步估计。最后，为了最大限度地发挥这一努力的影响，我们将 在收集数据时，每六个月向科学界提供完全匿名的数据。 我们期待这种预期的数据共享将进一步提高拟议工作的科学价值。这 将加快将收集的数据用作未来研究工作的基础的步伐 越来越小的儿童，以描绘ASD的潜在病理生理学。

Abstract Functional neuroimaging is increasingly enhancing our understanding of autism spectrum disorders (ASD) as disconnection syndromes, but because of its demands, most studies have focused on adults or older children. Conducting functional neuroimaging during natural sleep permits the study of young children and infants. Given the early onset of ASD, such studies may be crucial to the identification of biomarkers. However, the assumption that findings obtained during sleep can be generalized to wakefulness has not yet been systematically tested. This exploratory proposal represents a first step to fill this important gap by studying young children with ASD in two conditions - wakefulness and natural sleep - using resting-state functional magnetic resonance imaging (R-fMRI). By quantifying intrinsic functional connectivity (iFC) throughout the brain, R-fMRI provides a wealth of information about functional brain circuitry. While differences between asleep and awake R-fMRI in healthy adults have been described, to date, iFC measures in sleeping young children with ASD have not been systematically characterized, nor have they been contrasted with wakefulness. Accordingly, our overarching goal is to provide an initial systematic characterization of the stability (reliability) across states (awake and sleep) of whole-brain iFC in children with ASD. We propose to collect R-fMRI while awake and during natural sleep in at least 20 children with ASD between the ages of 66 to 90 months - starting at the youngest ages at which children can be successfully scanned while awake. We will survey whole brain iFC employing structural and functional parcellation units commonly examined in the literature. We will also compute other whole-brain voxel-wise measures of intrinsic brain functional architecture previously reported to be abnormal in ASD and which capture specific properties not otherwise characterized by traditional correlation analyses. These include Voxel Mirrored Homotopic Connectivity, Regional Homogeneity, Fractional Amplitude of Low Frequency Fluctuations, Degree Centrality and Independent Component Analyses. Our hypothesis generating aims are (1) to test for significant differences between wakefulness and sleep across children with ASD, and (2) to systematically characterize the stability (reliability) of between-individual differences in R-fMRI measures across states (asleep, awake) as indexed by intraclass correlation coefficients. We will also address additional questions regarding the effects of different parcellation systems on measures of stability, the stability of brain-behavior relationships with ASD measures, and derive initial estimates of within-session test-retest reliability. Finally, to maximize the impact of this effort, we will make fully anonymized data available to the scientific community every six months as the data are collected. We expect such prospective data sharing to further enhance the scientific value of the proposed efforts. This will accelerate the pace at which the collected data can be used as a foundation for future efforts to study increasingly younger children so as to delineate the underlying pathophysiology of ASD.