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脑干网状结构是一个小世界网络,而非无标度网络。

The brainstem reticular formation is a small-world, not scale-free, network.

作者信息

Humphries M D, Gurney K, Prescott T J

机构信息

Adaptive Behaviour Research Group, Department of Psychology, University of Sheffield, Sheffield S10 2TP, UK.

出版信息

Proc Biol Sci. 2006 Feb 22;273(1585):503-11. doi: 10.1098/rspb.2005.3354.

Abstract

Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called 'small-world' and 'scale-free' networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain--the medial reticular formation (RF) of the brainstem--and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement.

摘要

最近,已经证明几个复杂系统可能具有简单的图论特征,即所谓的“小世界”和“无标度”网络。这些网络也已应用于灵长类动物皮质区域之间的总体神经连接以及秀丽隐杆线虫的神经系统。在此,我们将这项工作扩展到脊椎动物大脑的一个特定神经回路——脑干的内侧网状结构(RF),并且这样做我们做出了三个关键贡献。第一,这项工作构成了三十多年来对这个重要脑结构的首个模型(以及定量综述)。第二,我们在神经网络层面开展了对脊椎动物脑连接性的首次图论分析。第三,我们提出了简单的指标来定量评估所研究的网络在何种程度上是小世界网络或无标度网络。我们得出结论,在内侧RF被配置为在适合定量测量的假设下创建小世界(意味着连贯的快速处理能力)而非无标度类型的网络。

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