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PLoS One. 2015 Nov 10;10(11):e0142143. doi: 10.1371/journal.pone.0142143. eCollection 2015.

Network Physiology: How Organ Systems Dynamically Interact.

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Department of Physics, Bar-Ilan University, Ramat Gan, 52900, Israel.
Department of Physics, Boston University, Boston, MA 02215, United States of America.
Department of Neurology, Beth Israel Deaconess Medical Center and Havard Medical School, Boston, MA 02115, United States of America.
Harvard Medical School and Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, United States of America.
Harvard Medical School and Division of Sleep Medicine, Brigham and Women's Hospital, Boston, MA 02115, United States of America.
Institute of Solid State Physics, Bulgarian Academy of Sciences, Sofia 1784, Bulgaria.


We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

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