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的研究人员的项目中，我们将皮质网络架构与使用扩散光谱成像（DSI）和fMRI获得的人脑网络进行比较，以及许多其他（非中性）加权复杂网络，例如科学协作网络，航空公司，航空公司，航空公司网络等。我们的研究揭示了具有生物来源（神经，基因）的网络中特别明显的新颖和健壮的体重组织，但在不同的社交和语言（Word）网络中也是如此。此外，使用仿真，我们表明可以使用本地学习规则来获得此类网络体系结构，这些本地学习规则可以根据节点之间的过去交互调整网络中的权重。描述这项工作的手稿已于2012年4月发表在《自然物理学》中。这项工作正在进行中，并着重于学习规则。 在与小儿成像和组织科学计划（PPITS）计划的持续项目中，NICHD我们对观察到的偏斜和重尾轴突直径分布进行了理论研究。我们表明，观察到的分布符合与参数形式的重尾分布，可优化信息丰富的上限（IUB）以及信息能力。 描述这项工作的手稿在2013年1月发表在PLOS One中。在一个后续项目中，基于最佳IUB特征开发的分布已实施并应用于模拟和实验数据，从而改善了轴突直径分布的测量值。 在与小儿成像和组织科学计划（PPITS）计划的研究人员的项目中随着淋巴结宽度的增加，会影响沿髓式轴突的信号的传播。这两者均由周围的神经胶质细胞调节，并取决于轴突中存在的活性水平。理论预测是在数学上实现的，并将其与实验观察到的值进行了比较，其最终目的是解决髓质神经胶质在学习和可塑性中的作用。关于星形胶质细胞在修饰髓鞘轴突特性中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则在2013年7月提交给神经科学的MANSUCRIPT中描述。 在与临床和发育基因组实验室的研究人员的一个新项目中，NICHD我们研究了通过对自闭症患者和正常患者进行重编程的皮肤细胞创建的神经元培养物。它是较大研究的一部分，该研究涉及发育过程中自闭症大脑中发生的分子和细胞变化。在当前的研究中，目标是确定网络结构的变化，或在不同细胞的活性谱中，将正常细胞培养物与自闭症患者的培养区分开。