CRII: SCH: A Computational Toolbox for Analysis of Big Brain Data

大脑是我们最复杂、最不为人所知的器官。由于最近大型公共神经成像数据库的激增，研究人员可以访问前所未有的数据量，但在许多方面，数据量已经超出了我们的分析能力。随着紧迫的健康问题吸引了科学家、临床医生和工程师的兴趣，我们迫切需要能够整合不同领域的方法和专业知识的计算工具。该项目旨在通过开发、使用和共享新的开源计算工具来建模和分析大脑皮质厚度（健康大脑发育的一个指标），从而推进对大脑大数据的分析。通过对包含500多个个体扫描的两个大型数据集的分析，将生成健康发育过程中皮质厚度变化的基线。数值模拟还将揭示产生大脑的机械力的影响。S独特的形状。开发的计算工具将供其他研究人员使用，以进一步利用现有的开放获取MRI扫描数据库。除此之外，该项目有可能在分析神经系统疾病（如自闭症谱系障碍、阿尔茨海默病和帕金森病）的临床应用中产生新的见解。除了这个跨学科项目，该团队还将开发一个面向公众的学生博客，介绍生物力学领域的有趣研究。脑回转，或者说是大脑形成其特有的皱纹和褶皱的过程，是生物过程和机械力量共同作用的结果。这些因素紧密耦合并相互影响，影响着大脑的形态和功能。该项目将通过开发描述异质、各向异性、生长和重塑组织的新材料模型，提高用于模拟旋转的有限元模拟的生物保真度，模拟脑脊液压力、神经元凋亡和突触修剪。这些计算模拟将使我们更深入地了解机械力在皮质厚度演变中的作用，皮质厚度在个体内部和个体之间都存在区域差异。通过引入一种新的感兴趣的度量，允许表征任意小区域的厚度变化，该项目将开发新的计算工具，用于分析受试者内部和受试者之间的皮质厚度变化，并表征健康发育中的这些模式。这项研究的成功完成将为许多公共神经成像数据库中的大脑数据的神经成像分析带来新的计算工具，从现有资源中产生额外的价值。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The brain is our most complex and least understood organ. Due to the recent proliferation of large public neuroimaging data repositories, researchers have access to an unprecedented amount of data, but in many ways the amount of data has surpassed our abilities to analyze it. With pressing health questions attracting the interest of scientists, clinicians, and engineers, we have an urgent need for computational tools that integrate the methods and expertise of different fields. This project seeks to advance the analysis of big brain data by developing, using, and sharing novel open-source computational tools for the modeling and analysis of cortical thickness, an indicator of healthy brain development. Through the analysis of two large data sets containing over 500 individual scans, a baseline for cortical thickness variation throughout healthy development will be generated. Numerical simulations will also shed light on the effect of the mechanical forces that give rise to the brain?s unique shape. The computational tools developed will be made available for use by other researchers to further leverage existing open access databases of MRI scans. Beyond that, this project has the potential to produce new insights with clinical applications in the analysis of neurological disorders such as Autism Spectrum Disorder, Alzheimer's Disease, and Parkinson's Disease. Alongside this trans-disciplinary project, the team will also develop a student-written blog, intended for the general public, on interesting investigations in the field of biomechanics.Gyrification, or the process by which the brain develops its characteristic wrinkles and folds, is the result of both biological processes and mechanical forces. These elements, tightly coupled and affecting each other, affect both the form and function of the brain. This project will increase the biological fidelity of the finite element simulations used to model gyrification by representing cerebrospinal fluid pressure, neuronal apoptosis, and synaptic pruning through the development of new material models that describe heterogeneous, anisotropic, growing and remodeling tissue. These computational simulations will generate a deeper understanding of the role of mechanical forces in the evolution of cortical thickness, which varies regionally both within and between individuals. By introducing a new metric of interest that allows for the characterization of thickness variations on arbitrarily small regions, this project will develop new computational tools for the analysis of within-subject and between-subject variations of cortical thickness and the characterization of these patterns in healthy development. The successful completion of this research will result in novel computational tools for neurological imaging analysis of big brain data in the many public neuroimaging databases, generating additional value out of existing resources.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.