Network physiology reveals relations between network topology and physiological function

By Amir Bashan, R. Bartsch, Jan W. Kantelhardt, Shlomo Havlin, Plamen Ch. Ivanov. Nature Communications, 2012

660 citations recorded by the source corpus.

The human organism is an integrated network where complex physiological systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here we develop a framework to probe interactions among diverse systems, and we identify a physiological network. We find that each physiological state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiological states, the network undergoes topological transitions associated with fast reorganization of physiological interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology. Humans are a network of complex physiological systems, but quantifying these diverse systems is a challenge. This study presents a method to show that each physiological state is characterized by a specific network structure, demonstrating a connection between network topology and function.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/895ffe4e5f4ee91e7069738f3a80696155bab5b6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Network Physiology: How Organ Systems Dynamically Interact (2015, methodology): “introduced a novel concept, Time Delay Stability (TDS), and we recently developed a new TDS method [1, 2, 10] to study the time delay with which bursts of activation in the output dynamics of a given system are consistently followed by corresponding bursts in the signal output of other systems (Fig ”