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自闭症谱系障碍脑连接组布线异常研究
其他题名Miswired Connectomes in Autism Spectrum Disorders
侯晓晖
学位类型博士
导师左西年
2015-05
学位授予单位中国科学院研究生院
学位授予地点北京
学位专业心理学
关键词自闭症 连接组 发展 脑网络 元分析 自闭功能连接
摘要自闭症谱系障碍研究试图从包括遗传、脑结构和功能以及行为在内的多维视角来理解其潜在病理机制。研究人员目前普遍认为其病理机制在脑层面上体现为脑结构与功能发育异常。借助于功能核磁共振成像技术,越来越多的研究者将自闭症谱系障碍视为一种系统水平的大脑功能紊乱(表现为激活异常和功能连接紊乱)。但是,自闭症谱系障碍的脑成像研究仍面临众多挑战,以下问题尤其突显:(1)大样本和结果可重复性,(2)系统水平上的脑功能整合,(3)毕生发展的视角。为突破以上困境,我们基于大样本任务设计磁共振成像研究的元分析和大样本多模态影像学数据,尝试从系统神经科学视角,通过将自闭症谱系障碍病人功能激活异常的脑区和异常的功能连接,从多维、多尺度的视角以及内在脑功能网络水平为自闭症谱系障碍的神经生理机制ᨀ供脑科学经验数据,研究内容和结果主要包括:
(1)基于 101 篇研究自闭症谱系障碍的任务脑成像研究,我们进行了一系列元分析(涉及 1742 名病人和 1749 名健康被试),并将所得结果在大尺度内在脑功能网络的分布进行深入研究,发现:自闭症谱系障碍病人的高级联合皮层网络(默认网络、背侧注意网络、腹侧注意网络和额顶控制网络)、初级皮层网络(体感运动网络和视觉网络)均表现出功能激活异常;成人研究揭示病人的认知控制网络激活降低比例增加,而视觉网络的激活升高比例增加;儿童/青少年研究则发现病人边缘网络激活降低比例增加,而背侧注意网络的激活升高比例增加;在儿童到成人的变化过程中,大脑默认网络异常(降低和升高)激活占总体异常激活比例明显下降,进一步的默认网络子系统分析发现这些随龄下降涵盖了其背内侧前额叶子系统异常到其中线枢纽子系统和内侧颞叶子系统异常。以上发现,ᨀ示了一个“自闭症谱系障碍脑连接组发展布线异常”的假设。
(2)基于上述元分析所得 46 个异常激活峰值坐标确定感兴趣区中心,以此作为节点,以各自皮层功能连接图谱的空间分布相似性刻画他们代表的大尺度网络的功能连接,并将其作为边,构建“自闭症谱系障碍异常激活脑功能网络” 。基于公开的国际“自闭症脑影像数据交换”项目ᨀ供的大样本、多中心的静息态功能影像学数据,研究上述脑功能网络在自闭症谱系障碍中的功能连接组学异常及其随年龄的变化进行研究。我们发现:自闭症谱系障碍病人体感运动网络与背侧注意网络之间的功能连接降低。这些结果为上述“布线异常连接组假设”ᨀ供部分实证数据。
(3)基于 627 名健康被试(6-85 岁)的毕生多模态脑成像数据,采用与研究(2)相同的节点和边,构建上述脑功能网络,并估计了其脑功能连接组学指标的毕生发展模式。同时,针对研究(2)中表现异常的功能连接组学指标,绘制其毕生发展轨线,并基于国际“自闭症脑成像数据交换”项目样本来分析病人在相应指标毕生发展轨线上的分布情况。通过研究该自闭症谱系障碍异常激活脑功能网络的毕生发展模式,我们发现:这个“自闭症谱系障碍异常脑激活的内在功能网络”的连接表现出显著的毕生随龄变化模式,既有线性增长也有非线性的倒 U 型变化,且绝大部分是网络之间的连接,主要分布于运动体感网络、边缘网络、视觉网络、默认网络和注意网络;只有体感运动网络内部功能连接呈倒U 型发展轨线。最后,我们通过绘制研究(2)发现的自闭症谱系障碍所表现异常的功能连接组学指标的毕生发展轨线,计算病人和健康被试的分布比例来展示毕生发展轨线对自闭症谱系障碍早期检测的参考作用。
本论文通过把元分析结果与大尺度皮层内在功能网络结合,ᨀ出自闭症谱系障碍的脑发展过程的连接组布线异常模型,将早期ᨀ出的神经病理生理学模型拓展为一个系统神经科学水平的连接组模型;大样本、多中心、多模态脑影像学数据实证研究初步揭示该模型可用来开展自闭症谱系障碍基础研究、临床测试及基于脑生物标记的靶点;其毕生发展轨线研究首次将自闭症谱系障碍脑激活异常脑区所构成的内在功能网络在生命全程的变化情况绘制出来,初步应用为未来自闭症谱系障碍研究ᨀ供了毕生发展的参考。
其他摘要Research on Autism Spectrum Disorders (ASD) attempts to understand the neurophysiological mechanism of the disorders from a multidimensional perspective, including genetic, brain anatomy, function, connectivity and behaviors. At present, the pathological mechanism of ASD is generally considered as abnormal development in brain structure and functional. ASD has been increasingly recognized as a brain disorder with aberrant  activity measured by functional magnetic resonance imaging (fMRI). Previous findings on both functional activation and connectivity suggested large-scale neuronal dysfunctions at a system level in ASD. However, Brain imaging studies of ASD is still facing  many challenges, the following problems are particularly highlighted: (1) the large sample and result repeatability, (2) brain function integration at the level of the system, (3) the perspective of lifelong development. To resolve these dilemma, based on meta analyses of a large sample of task design functional magnetic resonance imaging study,  and a large sample lifespan multimodality image data, from the perspective of systems neuroscience, we attempt to provide an explanation for the physiological mechanism of ASD by associated dysfunction of brain regions with the abnormal functional connectivity and clinical behavior score, which will be a key step in understanding the brain-behavior interaction underlying ASD.
(1) We conducted a series of comprehensive meta-analyses of 101 fMRI studies on ASD (1742 patients versus 1749 healthy controls) and linked the observations to a functional parcellation of connectomes derived from 1000 healthy participants. We found that both associative (default, dorsal attention, ventral attention and frontoparietal control network) and primary networks (somatomotor and visual network) are altered in ASD. Hypo-  and hyper-activations were more detectable in adulthood samples for cognitive control network and visual network, respectively whereas the abnormal activations were mainly presented for limbic network and dorsal attention network in neurodevelopmental samples. Particularly, default network demonstrated remarkable reduction of proportion of abnormal activations from childhood to adulthood. Based on the findings, we propose a miswired connectome profile during neurodevelopment of ASD patients.
(2) 46 surface-based region of interests derived from  the dysfunctional maximum 3D coordinates derived form ALE meta-analyses wear  selected as nodes, and the whole brain surface functional connectivity similarity of these noes as edges, and constructed a brain functional network. Taking Autism Brian Imaging Data Exchange (ABIDE) datasets as the  subjects, we explored functional connectomics abnormity  of  above-mentioned brain functional network  among ASD patients and associated the abnormity with clinical symptoms. We detected reduction of functional connectivity between  somatomotor and dorsal attention networks among ASD patients, and detected a positive correlation between this reduction and ADI-R social communication score.
(3) Based on 627 multimodal  imaging data of health subjects, we explored the lifespan developmental pattern of study (2) mentioned brain functional network. Meanwhile we mapped lifespan developmental trajectory of functional connectomics index of ASD patients, and  explored the distribution of ASD patients from ABIDE distributions on  the trajectory. We detected functional connectivity among intra- and inter-  resting state functional network changes markedly with age. As for intra-networks, we found the functional connectivity within somatomoter network show inverted U  curve  in lifespan development. On the other hand we found functional connectivity among different resting state networks mainly show linear increase with age,  few  of them show inverted U  curve  in lifespan development. By mapping  lifespan developmental trajectory of functional connectomics index of ASD patients, our results showed the indexes  could  distinguish  ASD patients  from  health participants to some extent.
These findings extend early neural pathophysiological models of ASD to a whole brain system-level model by proposing a miswired connectome profile during the neurodevelopment, which will serve as a target for basic research, clinical tests and brain-based biomarkers of ASD in future.
学科领域认知神经科学
语种中文
文献类型学位论文
条目标识符http://ir.psych.ac.cn/handle/311026/19592
专题认知与发展心理学研究室
作者单位中国科学院心理研究所
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侯晓晖. 自闭症谱系障碍脑连接组布线异常研究[D]. 北京. 中国科学院研究生院,2015.
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