Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits

被引:307
作者
Bassett, Danielle S. [1 ,2 ,3 ,6 ]
Greenfield, Daniel L. [4 ]
Meyer-Lindenberg, Andreas [5 ]
Weinberger, Daniel R. [6 ]
Moore, Simon W. [4 ]
Bullmore, Edward T. [3 ]
机构
[1] Univ Calif Santa Barbara, Dept Phys, Santa Barbara, CA 93106 USA
[2] Univ Calif Santa Barbara, Inst Collaborat Biotechnol, Santa Barbara, CA 93106 USA
[3] Univ Cambridge, Dept Psychiat, Behav & Clin Neurosci Inst, Cambridge, England
[4] Univ Cambridge, Comp Lab, Cambridge CB2 3QG, England
[5] Cent Inst Mental Hlth, D-6800 Mannheim, Germany
[6] NIMH, Genes Cognit & Psychosis Program, Clin Brain Disorders Branch, Bethesda, MD 20892 USA
基金
美国国家卫生研究院; 英国工程与自然科学研究理事会;
关键词
WHITE-MATTER; CEREBRAL-CORTEX; HIERARCHICAL ORGANIZATION; CORTICAL THICKNESS; FRACTAL ANALYSIS; GRAY-MATTER; CONNECTIVITY; INSIGHTS; MAMMALS; DYSCONNECTIVITY;
D O I
10.1371/journal.pcbi.1000748
中图分类号
Q5 [生物化学];
学科分类号
070307 [化学生物学];
摘要
Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.
引用
收藏
页数:14
相关论文
共 76 条
[1]
[Anonymous], 1983, The modularity of mind
[2]
[Anonymous], 2009, Frontiers in Neuroinformatics, DOI [10.3389/neuro.11.037.2009.eCollection2009, 10.3389/neuro.11.037.2009]
[3]
[Anonymous], 1991, CORTICONICS
[4]
An energy budget for signaling in the grey matter of the brain [J].
Attwell, D ;
Laughlin, SB .
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, 2001, 21 (10) :1133-1145
[5]
Bakoglu H., 1990, CIRCUITS INTERCONNEC
[6]
Scale-Free Networks: A Decade and Beyond [J].
Barabasi, Albert-Laszlo .
SCIENCE, 2009, 325 (5939) :412-413
[7]
Hierarchical organization of human cortical networks in health and schizophrenia [J].
Bassett, Danielle S. ;
Bullmore, Edward T. ;
Verchinski, Beth A. ;
Mattay, Venkata S. ;
Weinberger, Daniel R. ;
Meyer-Lindenberg, Andreas .
JOURNAL OF NEUROSCIENCE, 2008, 28 (37) :9239-9248
[8]
BEIU V, 2008, P IEEE ISCA IN PRESS
[9]
Mapping limbic network organization in temporal lobe epilepsy using morphometric correlations: Insights on the relation between mesiotemporal connectivity and cortical atrophy [J].
Bernhardt, Boris C. ;
Worsley, Keith J. ;
Besson, Pierre ;
Concha, Luis ;
Lerch, Jason P. ;
Evans, Alan C. ;
Bernasconi, Neda .
NEUROIMAGE, 2008, 42 (02) :515-524
[10]
Thalamo-cortical network pathology in idiopathic generalized epilepsy: Insights from MRI-based morphometric correlation analysis [J].
Bernhardt, Boris C. ;
Rozen, Daniel A. ;
Worsley, Keith J. ;
Evans, Alan C. ;
Bernasconi, Neda ;
Bernasconi, Andrea .
NEUROIMAGE, 2009, 46 (02) :373-381