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Emergence of complex dynamics in a simple model of signaling networks
Author(s) -
Luı́s A. Nunes Amaral,
Albert Dı́az-Guilera,
André A. Moreira,
Ary L. Goldberger,
Lewis A. Lipsitz
Publication year - 2004
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0404843101
Subject(s) - scaling , complex network , complex system , set (abstract data type) , complex dynamics , noise (video) , simple (philosophy) , statistical physics , computer science , biological system , dynamical systems theory , topology (electrical circuits) , living systems , dynamics (music) , physics , biology , mathematics , artificial intelligence , acoustics , philosophy , epistemology , world wide web , mathematical analysis , geometry , quantum mechanics , combinatorics , image (mathematics) , programming language
Various physical, social, and biological systems generate complex fluctuations with correlations across multiple time scales. In physiologic systems, these long-range correlations are altered with disease and aging. Such correlated fluctuations in living systems have been attributed to the interaction of multiple control systems; however, the mechanisms underlying this behavior remain unknown. Here, we show that a number of distinct classes of dynamical behaviors, including correlated fluctuations characterized by 1/f scaling of their power spectra, can emerge in networks of simple signaling units. We found that, under general conditions, complex dynamics can be generated by systems fulfilling the following two requirements, (i) a "small-world" topology and (ii) the presence of noise. Our findings support two notable conclusions. First, complex physiologic-like signals can be modeled with a minimal set of components; and second, systems fulfilling conditions i and ii are robust to some degree of degradation (i.e., they will still be able to generate 1/f dynamics).

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