4.8 Article

Emergence of complex dynamics in a simple model of signaling networks

Publisher

NATL ACAD SCIENCES
DOI: 10.1073/pnas.0404843101

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Funding

  1. NCRR NIH HHS [P41 RR 13622, P41 RR013622] Funding Source: Medline
  2. NIA NIH HHS [AG 04390, AG 08812, P01 AG004390, P60 AG008812] Funding Source: Medline
  3. NIGMS NIH HHS [K25 GM069546-02] Funding Source: Medline

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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 (it) 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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