文章基本信息

标题：Dependence of connectivity on geometric distance in brain networks
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作者：Alessio Perinelli ; Davide Tabarelli ; Carlo Miniussi 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2019
卷号：9
期号：1
页码：1-9
DOI：10.1038/s41598-019-50106-2
出版社：Springer Nature
摘要：In any network, the dependence of connectivity on physical distance between nodes is a direct consequence of trade-off mechanisms between costs of establishing and sustaining links, processing rates, propagation speed of signals between nodes. Despite its universality, there are still few studies addressing this issue. Here we apply a recently-developed method to infer links between nodes, and possibly subnetwork structures, to determine connectivity strength as a function of physical distance between nodes. The model system we investigate is brain activity reconstructed on the cortex out of magnetoencephalography recordings sampled on a set of healthy subjects in resting state. We found that the dependence of the time scale of observability of a link on its geometric length follows a power-law characterized by an exponent whose extent is inversely proportional to connectivity. Our method provides a new tool to highlight and investigate networks in neuroscience.