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连接组学:从网络稀疏性到大规模数据库

Connectomes: from a sparsity of networks to large-scale databases.

作者信息

Kaiser Marcus

机构信息

NIHR Nottingham Biomedical Research Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.

Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.

出版信息

Front Neuroinform. 2023 Jun 12;17:1170337. doi: 10.3389/fninf.2023.1170337. eCollection 2023.

Abstract

The analysis of whole brain networks started in the 1980s when only a handful of connectomes were available. In these early days, information about the human connectome was absent and one could only dream about having information about connectivity in a single human subject. Thanks to non-invasive methods such as diffusion imaging, we now know about connectivity in many species and, for some species, in many individuals. To illustrate the rapid change in availability of connectome data, the UK Biobank is on track to record structural and functional connectivity in 100,000 human subjects. Moreover, connectome data from a range of species is now available: from and the fruit fly to pigeons, rodents, cats, non-human primates, and humans. This review will give a brief overview of what structural connectivity data is now available, how connectomes are organized, and how their organization shows common features across species. Finally, I will outline some of the current challenges and potential future work in making use of connectome information.

摘要

对全脑网络的分析始于20世纪80年代,当时仅有少数几个连接组可供研究。在早期,人类连接组的信息并不存在,人们只能梦想获取单个人类受试者的连接信息。得益于诸如扩散成像等非侵入性方法,我们现在了解了许多物种的连接情况,对于某些物种,还了解了许多个体的连接情况。为了说明连接组数据可获取性的快速变化,英国生物银行有望记录10万名人类受试者的结构和功能连接情况。此外,现在可以获取一系列物种的连接组数据:从线虫和果蝇到鸽子、啮齿动物、猫、非人类灵长类动物以及人类。本综述将简要概述目前可用的结构连接数据、连接组是如何组织的,以及它们的组织方式如何在不同物种间呈现出共同特征。最后,我将概述在利用连接组信息方面当前面临的一些挑战以及未来可能的工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c81/10291062/9a5ad2785868/fninf-17-1170337-g001.jpg

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