White Matter Connectivity and Network Analysis

白质连接和网络分析

• 批准号: 8746532
• 负责人: peter j munson
• 金额: $ 17.16万
• 依托单位: CENTER FOR INFORMATION TECHNOLOGY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8746532
• 关键词: Address; Affect; Astrocytes; Axon; Binding; Biological; Brain; Caliber; Cell Culture Techniques; Cells; Characteristics; Childhood; Clinical; Collaborations; Complex; Computer Architectures; Data; Development; Diffusion; Functional Magnetic Resonance Imaging; Genes; Genomics; Goals; Graph; Human; Image; Laboratories; Language; Learning; Manuscripts; Measurement; Measures; Methodology; Methods; Molecular; Myelin; National Institute of Child Health and Human Development; National Institute of Mental Health; National Institute of Neurological Disorders and Stroke; Nature; Network-based; Neuroglia; Neurons; Neurosciences; Nodal; Normal Cell; Pathway Analysis; Patients; Physics; Property; Publishing; Research Personnel; Role; Science; Signal Transduction; Simulate; Skin; Structure; System; Tail; Techniques; Theoretical Studies; Thick; Tissues; Weight; Width; Work; base; follow-up; improved; nervous system development; novel; programs; relating to nervous system; simulation; social; theories; white matter

In a project with investigators of NIMH, we compare cortical network architectures to human brain networks obtained using diffusion spectrum imaging (DSI) and fMRI, as well as a number of other (non-neural) weighted complex networks, like scientific collaboration networks, airline networks, etc. Our study reveals novel and robust weight organization particularly pronounced in the networks with biological origin (neural, gene), but also in different social and language (word) networks. Additionally, using simulations, we show that such network architecture can be obtained using local learning rules that adjust the weights in the network based on the past interactions between the nodes. A manuscript describing this work has been published in Nature Physics in April of 2012. Continuation of this work is under way and focuses on the learning rules. In a continuing project with investigators in the Program on Pediatric Imaging and Tissue Sciences (PPITS), NICHD we conduct a theoretical study of the observed skewed and heavy-tailed axon diamater distribution. We show that the observed distributions conforms to a heavy-tailed distribution with parametric form that optimizes the informative upper bound (IUB) as well as the information capacity. A manuscript describing this work is published in PLOS ONE in January of 2013. In a follow-up project, the distribution developed based on the optimal IUB characteristics has been implemented and applied to simulated and experimental data, yielding improved measurements of the axon diameter distributions. In a project with investigators from the Program on Pediatric Imaging and Tissue Sciences (PPITS), NICHD and the Nervous System Development and Plasticity Section, NINDS, we use the cable theory as a theoretical framework to predict how the changes in myelin thickness, as well as the increase in the nodal width, affects the propagation of the signals along a myelinated axon. Both of these are regulated by the surrounding glial cells and dependent on the level of activity present in an axon. The theoretical predictions are implemented in Mathematica and are compared with the experimentally observed values, with the ultimate goal of addressing the role of myelinating glia in learning and plasticity. Manuscript describing the experimental findings on the role of astrocytes in modifying the myelinated axon properties is about to be submitted to Neuron, while the theoretical aspect of myelin plasticity are described in a mansucript submitted to Neuroscience in July, 2013. In a new project with investigators from the Laboratory of Clinical and Developmental Genomics, NICHD we study neuronal cultures created by reprogramming skin cells from autistic patients as well as normals. It is a part of a larger study addressing the molecular and cellular changes that occur in the autistic brain during the development. In the current study the goal is to identify the changes in the network structure, or in the activity profile of different cells that distinguishes the normal cell cultures from those of autistic patients.

在与NIMH研究人员的一个项目中，我们将皮质网络结构与使用扩散光谱成像(DSI)和功能磁共振成像(FMRI)获得的人脑网络以及其他一些(非神经)加权的复杂网络进行了比较，如科学协作网络、航空公司网络等。我们的研究揭示了新颖而健壮的权重组织，特别是在生物起源(神经、基因)的网络中，但在不同的社会和语言(单词)网络中也是如此。此外，通过仿真，我们证明了这种网络结构可以使用局部学习规则来获得，所述局部学习规则基于节点之间过去的交互来调整网络中的权重。描述这项工作的手稿已于2012年4月发表在《自然物理》杂志上。这项工作正在继续进行，重点是学习规则。 在与NICHD儿科影像和组织科学计划(PPITS)的研究人员一起进行的一个持续项目中，我们对观察到的轴突直径偏斜和重尾分布进行了理论研究。我们表明，观测到的分布符合参数形式的重尾分布，它优化了信息上限(Iub)和信息容量。描述这项工作的手稿于2013年1月发表在《公共科学图书馆·综合》上。在后续项目中，基于最优IUB特征开发的分布已被实施并应用于模拟和实验数据，产生了改进的轴突直径分布测量结果。 在与NICHD儿科影像和组织科学项目(PPITS)和NINDS神经系统发育和可塑性部门的研究人员共同参与的一个项目中，我们使用电缆理论作为理论框架，预测髓鞘厚度的变化以及结节宽度的增加如何影响信号沿有髓轴突的传播。这两者都受到周围神经胶质细胞的调节，并依赖于轴突中存在的活动水平。理论预测在MATHEMICAL A中实现，并与实验观察值进行比较，最终目的是解决髓鞘胶质细胞在学习和可塑性中的作用。描述星形胶质细胞在改变有髓轴突特性中的作用的实验发现的手稿即将提交给神经元，而髓鞘可塑性的理论方面在2013年7月提交给神经科学的手稿中进行了描述。 在与NICHD临床和发育基因组实验室的研究人员合作的一个新项目中，我们研究了自闭症患者和正常人通过重新编程皮肤细胞创建的神经元培养。这是一项更大的研究的一部分，该研究旨在解决自闭症大脑在发育过程中发生的分子和细胞变化。在目前的研究中，目标是识别网络结构的变化，或不同细胞活动谱的变化，以区分正常细胞培养和自闭症患者的细胞培养。