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The Human Organism as an Integrated Interaction Network: Recent Conceptual and Methodological Challenges
Klaus Lehnertz1,2,3, Timo Bröhl1,2, Thorsten Rings1,2
1Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany.
Frontiers in Physiology
|January 7, 2021
Summary
Network Physiology studies how physiological systems interact as a network to maintain health. This research addresses key challenges in analyzing these complex interactions for better understanding and theoretical development.
Area of Science:
- Physiology
- Network Science
- Systems Biology
Background:
- Network Physiology views the organism as an integrated network, with organs as vertices and interactions as edges.
- Understanding complex interactions within and among physiological systems is crucial for optimizing function and maintaining health.
- Current analytical tools and theoretical frameworks are insufficient for fully probing these dynamic physiological networks.
Purpose of the Study:
- To advance the understanding of interactions within and among physiological systems.
- To identify and address critical challenges in network physiology research.
- To inspire new theoretical and analytical concepts for studying physiological networks.
Main Methods:
- Utilizing time-series analysis techniques to infer properties of time-varying interactions (strength, direction, functional form).
- Applying methods from network theory to characterize time-dependent networks derived from physiological data.
- Focusing on analyzing time-locked recordings of physiological observables.
Main Results:
- Identified significant challenges that hinder a comprehensive understanding of network physiology.
- Highlighted the need for novel theoretical and analytical approaches.
- Demonstrated the potential of network theory and time-series analysis in this field.
Conclusions:
- Addressing the identified challenges is essential for advancing network physiology.
- New theoretical and analytical frameworks are needed to fully study complex physiological interactions.
- This work provides a foundation for future research in network physiology and systems biology.
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