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CRCNS: Community-supported open-source software for computational neuroanatomy

CRCNS：社区支持的计算神经解剖学开源软件

基本信息

批准号：
9912156
负责人：
Eleftherios Garyfallidis
金额：
$ 17.34万
依托单位：
TRUSTEES OF INDIANA UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9912156
关键词：
Address Algorithmic Analysis Algorithms Area Back Beds Behavior Benchmarking Brain Brain Diseases Clinical Clinical Research Cloud Computing Cognition Collection Communities Complex Computational Technique Computer software Computing Methodologies Data Data Science Data Set Development Diffusion Diffusion Magnetic Resonance Imaging Documentation Education Face Generations Human Image Infrastructure International Knowledge Libraries Mathematics Measures Medicine Methods Modeling Neuroanatomy Neurons Neurosciences Perception Physics Preparation Process Property Psychology Pythons Research Research Personnel Role Scientist Software Tools Statistical Data Interpretation Techniques Technology Testing Translating Travel Work base biophysical techniques clinical application clinical decision-making clinically relevant cohesion community building computational neuroscience computer science computing resources image processing large datasets meetings method development neuroimaging novel open source relating to nervous system research and development skills software development tool tractography white matter

项目摘要

Different parts of the brain share and transmit Information through long-range connections that connect nerve cells in each part of the brain with nerve cells in other brain areas. These connections form bundles of nerve cells, and these bundles comprise a complex and expansive network within the human brain. Understanding these brain networks and their relation to the way that the brain Implements perception and cognition, and understanding how these networks break down In various brain disorders are major challenges In contemporary neuroscience. Diffusion Magnetic Resonance Imaging (dMRI) is the only currently available method to measure these connections In the living human brain non-invasively. The DIPY (Diffusion imaging in Python) project Is an International community-based effort to implement open-source software for analysis and Interpretation of dMRI data. The research and development work proposed here aims to expand the development work in DIPY, and to help share this work more widely with the community of researchers that use dMRI In their research. The project proposes to Implement and share new algorithms for analysis of dMRI data, and to share several important new datasets that will serve as benchmarks for ongoing methods development; it will support the development of software tools for cloud-computing with these data and it will facilitate the participation of a global community of scientists in the development of the software. Furthermore, it will support its wide dissemination to relevant research and enable computation on large datasets.

大脑的不同部分通过长距离连接共享和传递信息，将大脑各部分的神经细胞与其他大脑区域的神经细胞连接起来。这些连接形成神经细胞束，这些束构成了复杂而广泛的神经网络。人类大脑中的网络。了解这些大脑网络及其与大脑执行感知和认知，并了解这些网络如何在不同的大脑中分解，是当代神经科学的主要挑战。扩散磁共振成像（dMRI）是目前唯一可用的方法来测量这些连接在活着的人非侵入性的大脑DIPY（Diffusion Imaging in Python）是一个国际性的项目。以社区为基础的努力用于分析和解释dMRI数据的开源软件。的研发这里提出的工作旨在扩展DIPY的开发工作，并帮助更多地共享这项工作在研究中使用dMRI的研究人员中广泛使用。项目拟实施和分享用于分析dMRI数据的新算法，并分享几个重要的新算法数据集将作为正在进行的方法制定的基准;它将支持利用这些数据开发云计算软件工具，全球科学家社区参与软件开发。此外，它还将支持向有关研究机构广泛传播该报告，大型数据集上的计算。