Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains

被引：22

作者：

Stoop, Ralph ^{[3
]}

Saase, Victor ^{[1
,2
]}

Wagner, Clemens ^{[1
,2
]}

Stoop, Britta ^{[4
]}

Stoop, Ruedi ^{[1
,2
]}

机构：

[1] Univ Zurich, Inst Neuroinformat, CH-8057 Zurich, Switzerland

[2] Swiss Fed Inst Technol, CH-8057 Zurich, Switzerland

[3] Univ Basel, Inst Phys, CH-4056 Basel, Switzerland

[4] Univ Bern, Inst Forens Med, CH-3012 Bern, Switzerland

来源：

PHYSICAL REVIEW LETTERS | 2013年 / 110卷 / 10期

基金：

瑞士国家科学基金会;

关键词：

COMPLEX NETWORKS; CHAOS;

D O I：

10.1103/PhysRevLett.110.108105

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic-intercolumnar-scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks. DOI: 10.1103/PhysRevLett.110.108105

引用

页数：5

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