连接:从稀疏的网络到大规模的数据库
Marcus Kaiser1,2,3
1NIHR Nottingham Biomedical Research Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
Frontiers in neuroinformatics
|June 28, 2023
概括
大脑网络分析已经取得了显著的进步,现在可以在许多物种中获得广泛的连接组数据. 本综述探讨了当前的数据,组织原则和连接组研究的未来方向.
科学领域:
- 神经科学是一个神经科学.
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 整个大脑网络分析始于20世纪80年代,数据有限.
- 早期人类连接的信息很少.
- 非侵入性成像技术的进步极大地提高了数据的可用性.
研究的目的:
- 提供可用的结构连接数据的概述.
- 讨论连接组的组织原理.
- 突出跨物种的共同组织特征,并概述未来的挑战.
主要方法:
- 对现有文献和大规模神经成像数据集的审查.
- 分析包括人类在内的各种物种的连接组数据.
- 探索结构和功能连接度量.
主要成果:
- 连接组数据可用性显著增加,英国生物银行倡议就是一个很好的例子.
- 现在Connectome数据涵盖了从无脊椎动物到人类的各种物种.
- 跨物种大脑网络中共同的组织原则的新兴理解.
结论:
- 该领域已经从梦想着单个主体的人类连接组发展到拥有庞大的多物种数据集.
- 连接组组织揭示了多种类型中保存的特征.
- 未来的工作应该专注于利用这些丰富的数据来解决复杂的神经科学问题.
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