A Connectome Computation System for discovery science of brain
A Connectome Computation System for discovery science of brain
复制标题
用于发现大脑科学的连接组计算系统
DOI：
10.1007/s11434-014-0698-3
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发表时间：
2015-01-01
期刊：
影响因子：
18.9
通讯作者：
Zuo, Xi-Nian
中科院分区：
文献类型：
--
作者：
Xu, Ting;Yang, Zhi;Zuo, Xi-Nian
就像基因组学一样，大脑连接组学已经迅速成为世界上大多数国家大脑项目的核心组成部分。除了这些项目雄心勃勃的目标之外，一个根本性的挑战是需要一个高效，强大，可靠和易于使用的管道来挖掘如此庞大的神经科学数据集。在这里，我们介绍了一个计算流水线，即连接组计算系统（CCS），发现科学的人类大脑连接在宏观尺度上与多模态磁共振成像技术。CCS设计了一个三级层次结构，包括数据清洗和预处理，个别连接体映射和连接体挖掘，知识发现。在此层次结构中嵌入了几个功能模块，以实现质量控制程序，可靠性分析和连接体可视化。我们展示了CCS的实用性，基于一个公开的数据集，NKI-Rockland样本，描绘了著名的大规模神经网络在自然寿命（6-85岁）的规范轨迹。CCS已通过GitHub（https：//github.com/zuoxinian/CCS）和我们实验室的网站（http：//lfcd.psych.ac.cn/ccs.html）免费向公众提供，以促进人类大脑连接组学领域的发现科学的进展。
Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline—namely the Connectome Computation System (CCS)—for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping and connectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI–Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span (6–85 years of age). The CCS has been made freely available to the public via GitHub (https://github.com/zuoxinian/CCS) and our laboratory’s Web site (http://lfcd.psych.ac.cn/ccs.html) to facilitate progress in discovery science in the field of human brain connectomics.