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Network physiology
From Wikipedia, the free encyclopedia
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The human organism is an integrated network, where multi-component physiological systems, each with its own regulatory mechanism, continuously interact to synchronize their dynamics and coordinate their functions. Physiological interactions occur at multiple levels of integration and spatio-temporal scales to generate distinct physiological states, behaviors, and conditions at the organism level. Disrupting communications among physiological systems can lead to dysfunction of individual systems or collapse of the entire organism, as observed under clinical conditions such as neurodegenerative disorders, cardiac arrest, sepsis, coma, and multiple organ failure.Yet, despite its importance to basic physiological functions and clinical practice, the nature of dynamic interactions between systems and sub-systems, and their collective role as an adaptive network in health and disease, remains largely unknown. A new multidisciplinary field, Network Physiology (originated and founded by Professor Plamen Ch. Ivanov, Keck Laboratory for Network Physiology, Boston University) [1][2][3][4][5][6][7], has emerged to provide the analytic and computational methodologies and the theoretical framework needed to identify and quantify network interactions among diverse physiological systems [8][9][10], to explore the mechanisms through which global states and behaviors emerge at the organism level [11][12][13], and to derive network-based biomarkers of diagnosis and prognosis.[14][15][16][17][18][19]
Whole-body vertical and horizontal integration of systems and organs — essential for the emergence of states and functions at the organism level [7]
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Networks in Organ Systems
Networks in Heart
Networks in Lungs
Networks in Kidney
Networks in Brain
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The multidisciplinary field of Network Physiology focuses on whole-body research to understand the mechanisms through which diverse physiological systems and sub-systems interact across spatio-temporal scales — from the metabolic [20], genomic and cellular scale [21][22][23][24], to organs and the organism level [25][26][27] — to synchronize their dynamics and coordinate their functions; to uncover laws of cross-communication among systems; and establish basic principles underlying the integration of systems and organs as an adaptive dynamic network to generate distinct physiological states and functions. In addition to defining health and disease through biochemical, structural, dynamical, and regulatory changes in individual physiological systems, the conceptual framework of Network Physiology explores the signaling pathways, coordination, network interactions, and functional integration among systems and sub-systems as a hallmark of states and conditions. Research in Network Physiology involves basic science, physiology, and medicine, emphasizing systems interaction and whole-body integration as the basis for emerging physiological states, conditions, and behaviors at the organism level in both health and disease.[3][28][29][18]
Network Physiology integrates empirical and theoretical knowledge, concepts and approaches across disciplines from applied mathematics, data science, statisitical physics, and biomedical engineering to biology, genomics and proteomics, neuroscience, physiology, and clinical medicine [30][31][32][33].
Empirical Findings
Reorganization in network of organ systems interactions with transitions across states [1]
Immune-endocrine cellular network in diabetic islet [21]
Networks of alveolar-capillary blood flow [38]
Astrocyte-neuronal modulation networks across scales [39]
Networks of visceral epithelial cells in different organs (top) and network graphlets in epithelial tissues (bottom) [40]
Fibroblastic reticular cells network organization determines lymph node functionality [43]
Molecular and cellular networks of neuro-vascular interaction [44]
Networks in the lungs alveolar ventilation [45]
Functional networks of cardiac autonomic regulation from phase coherence [46]
Evolution of disease network with age and spreading of diseases through comorbidity networks[49]
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Network Physiology stimulates and fosters the development of three major directions of scientific, biomedical engineering and data science activity [7]:
- Building integrated platforms of biomedical devices, networks of sensors, and wearables for simultaneous synchronized recording of data across physiological systems in clinical and ambulatory environments; whole-body integration of biochemical, genetic, and imaging modalities with organ systems signals and clinical parameters.
- Collection, curation and dynamic visualization of large-scale multi-modal databases of continuously recorded parameters and output signals from multiple systems and body areas under various physiological states and clinical conditions; establishing a gold standard for synchronous multi-system data-collection.
- Developing novel computational, data science, and analytic methodologies widely applicable to diverse systems with transient dynamics operating at different time scales, and able to infer coupling forms; information transfer; variability and causality of interactions; adaptive networks of dynamical systems, and higher order interactions to investigate responses to regulatory and external changes across levels in the organism under health and disease.
In addition to developing the methodological instrumentarium (including platforms of integrated devices and sensor networks; large multi-modal, multi-system databases; analytic and computational approaches), Network Physiology builds a generalized theoretical framework necessary to investigate the principles and mechanisms through which various states and functions at the organism level emerge from network integration among sub-systems and systems.
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Network Physiology aims to quantify the structure and dynamics of physiological networks, and to link dynamic maps of systems interactions with physiological states and clinical conditions. A major objective is to build the Human Physiolome — a comprehensive data-driven dynamic atlas of physiologic interactions and networks of systems and organs across all levels and scales, a new BigData consisting of a library of multi-system signal recordings and the corresponding blueprint reference network maps (≈ millions of maps) that represent hundreds of physiological states across thousands of developmental, environmental, and pathological conditions.[4][6][50] The Human Physiolome Project was initiated in 2013 by Prof Plamen Ch. Ivanov (Keck Laboratory for Network Physiology, Boston University).[4][51][7]
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Definition of field
In science, a field is defined as a coherent domain of research that is centered on a group of closely-related fundamental questions to investigate a class of natural phenomena; it requires a distinctive methodological approach, develops specific analytic formalism, and theoretical framework, and has broad relevance to many systems and states. A scientific field becomes established when research progresses from descriptive observation to quantitative theory, developing its own methods and models, and establishing principles that can be applied across multiple contexts and systems. Network Physiology meets these criteria.
Fundamental questions
The field of Network Physiology addresses a set of core fundamental questions: What is the nature of signaling and communication between physiological systems and sub-systems? How do physiological and organ systems dynamically coordinate and synchronize their functions? What physiological mechanisms underlie higher-order network interactions by regulating not only the dynamics and functions of individual systems (network nodes) but also the time-varying interactions between systems (network links)? How do global states and conditions at the organism level emerge out of interactions and network integration among systems? What are the fundamental principles of hierarchical integration, information transfer, and network control within and across levels and scales in the organism (network of networks) that govern the "whole-body internet"?[1][3][7]
Distinctive approach
Network Physiology requires a distinctive quantitative and integrative approach that departs from phenomenological observations of associations between systems, and seeks a physical quantification of pair-wise physiological coupling (structure in temporal variability, linear/nonlinear characteristics, etc.) as well as of the synchronization and cooperation behaviors in adaptive networks of dynamical systems. The approach shifts focus from single-organ systems to the whole-body network, examining the relationship of physiological states, behaviors, and functions vs. networks of systems interactions. Network Physiology develops data-driven approaches utilizing BigData derived from continuous, high-frequency, synchronized, multi-systems recordings, enabling researchers to capture coordination across time scales and physiological domains.
Specific analytic formalism and theoretical framework
The field of Network Physiology requires new computational methods, analytic formalism and theoretical framework to identify and quantify physiological coupling from noisy, nonlinear, and transient signals of diverse systems (metabolic, neuronal, cardio-circulatory, respiratory, renal, endocrine/hormone, musculo-skeletal, locomotor, brain, etc.), each with distinct structure and dynamics (deterministic, stochastic, mixed) operating on a broad range of time scales (from millisecond to days). The formalism aims to describe the mechanisms of emergent global behaviors in networks of diverse dynamical systems; establish principles of control in multi-component physiological networks; and ultimately define a set of equations that represent physiological states and functions at the organism level, and establish the critical zone beyond which physiological couplings and networks break down, leading to clinical conditions and diseases. Network Physiology fosters the development of new analytical formalism by integrating concepts and advances in information theory [53][54][55], Granger causality,[56][57] nonlinear dynamics and synchronization theory,[58][59][60][61][62] coherence analysis [63][64], time delay stability [1][35][65], reconstruction of causal networks [66][67], non-equilibrium processes and criticality [68][69], statistical learning, networks of dynamical systems and adaptive networks[70][71][72][73][74], higher order interactions [75][76], reservoir computing [77][78] and AI [79][80][81][82][83][84].
Broad relevance and implications
The implications are broad: Network Physiology informs basic understanding of human physiology and living systems in general; offers new avenues to explore physiological regulation of systems interactions and networks; redefines global states and functions at the organism level through physiological networks; develops novel strategies to predict and treat adverse clinical events and diseases; foster the development of new analytic methodologies and theoretical formalism tailored to dynamic networks of diverse complex systems with nonlinear time-varying interactions; the field also facilitates the development of multi-modal sensor networks, integrated biomedical devices and monitoring platforms; and contributes to building the Human Physiolome—a large-scale dynamic atlas of network maps representing interactions among physiological systems across systems levels in the organism [4][51][50][7]; extends principles of the hierarchical organization and network integration of physiological systems to electronic systems with "smart" behavior, including swarms of bots, cyborgs, robotics and a new generation AI architecture (liquid neural network) that incorporates adaptive links and modules based on empirical findings in Network Physiology.
Beyond classical graph theory and complex networks
Network Physiology focuses on inferring coupling and dynamical interactions among physiological and organ systems based on continuous streams of synchronous recordings of key physiologic parameters and output signals from multiple systems to infer temporal dynamics in coupling, causality and control of interactions. In contrast to traditional complex network theory, where edges/links are constant and represent static graphs of association, novel approaches in Network Physiology have to take into consideration:
- the complex dynamics of individual systems (network nodes);
- dynamic aspects of network links representing systems communications in real time;
- evolution of systems interactions with time;
- emergence of collective global network behaviors in response to changes in physiologic states and conditions.
In graph theory and classical complex networks, nodes and links are static and represent statistical associations rather than dynamical coupling. Dynamical aspects in classical network theory arise from removing/adding links or nodes and from diffusion processes of flow on a fixed topology, where emphasis is given on the consequences of network topology and structure for networks function to transmit information. In contrast, in Network Physiology, links represent functional forms of dynamic time-varying coupling and coordination between diverse dynamical systems and sub-systems, and have transient characteristics.[58][85][86][63][87][88][89] In classical graphs and complex networks with a fixed number of nodes and links distribution with a given topology, there is only one state and function associated with the specific network structure.[90] In contrast, changes in the temporal dynamics of physiological systems (network nodes) can propagate via 'elastic' nonlinear time-varying links to affect the dynamics of other nodes, and thus, alter the behavior of the entire network, leading to a rich space of states and functions that can emerge from the same network topology.[47][48]
A fundamental question in Network Physiology is how to quantify, predict and control emergent global behaviors in temporal multiplex networks of diverse dynamic systems interacting simultaneously through various functional forms of coupling.[91][92][47][93][94][95]. In such adaptive networks of dynamical systems, markedly different global behaviors can emerge from the same network topology due to temporal changes in the dynamics of a node or in the functional form of a link [3][28][96][59]. This directly relates to the question of how a variety of physiologic states and functions emerge out of the collective dynamics of integrated physiological and organ systems [28][29][25][97][34][98][99], where pairs of systems may interact through multiple links representing different forms of coupling [58][91][92] It poses new challenges to further develop generalized methodology adequate to quantify complex dynamics of networks where nodes are not identical but represent diverse dynamical systems with diverse forms of coupling which continuously change in time to adapt to internal regulation and external perturbations. Thus, investigations in Network Physiology are not simply an application of established concepts and approaches in graphs and complex networks theory to existing fields of biomedical research.[100]. Because of the new type of problems, the specificity of related challenges, and the necessity of a novel methodology, theoretical framework and interdisciplinary efforts, Network Physiology has developed into a new multidisciplinary field of research [7][98][101][31][32][33]
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Synchronization and global synchronization phenomena play essential role in the field of Network Physiology. Amplitude, frequency, and phase synchronization, as forms of coupling and interaction, underlie biological/physiological network mechanisms through which global states, functions and behaviors emerge at the system and organism level.[102][103] Synchronization has been reported across physiological systems and levels of integration, including cardio-respiratory coupling [104][58]; maternal-fetal cardiac phase-synchronization [105][106]; brain blood flow velocity vs. peripheral blood pressure in stroke [94]; synchronization in neuron synaptic function [107]; organ networks [1][25]; EEG-synchronization and EEG-desynchronization in NREM and REM sleep;[108][109] brain waves synchronization and anti-synchronization during rest, exercise, cognitive tasks, sleep and wake [110][96][47][48]; cortio-muscular synchronization;[111][35]; synchronization in pancreatic cells and metabolism[10][112][113] inter-muscular muscle fibers synchronization in exercise and fatigue [41][42]; neuromodulation and Parkinson's, dystonia and epilepsy[114][115][116][117]; circadian synchrony of sleep, nutrition and physical activity [118].
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Recent advances in Information theory concepts, methods and approaches have broad implications in the field of Network Physiology, providing a quantitative framework to understand how physiological systems exchange, process, and integrate information. Through advancing novel measures based on mutual information, transfer entropy, co-information, and Granger causality, etc, tailored to physiological systems with nonlinear and transient output dynamics, information theory enables the detection of coupling strength, directionality, synergy/redundancy and higher-order interactions among physiological systems and sub-systems, thus, revealing how communication and regulation occur within the organism. Applications of information-theoretic approaches span a range from analyzing information transfer in brain-heart and brain-body networks during various states [119][120], to cardio-respiratory [121][122][123][124] and cortico-muscular interactions [125], to brain EEG and fMRI functional networks [126], and physiological systems interactions in extreme environments [95] .
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Frontiers in Network Physiology was launched in 2021 with founding editor-in-chief Professor Plamen Ch. Ivanov (Keck Laboratory for Network Physiology, Boston University) to support and foster the development of the multidisciplinary field of Network Physiology. It is the first and only peer-reviewed scientific journal focusing on how physiological systems and sub-systems interact to synchronize functions and integrate as networks to generate physiological states and conditions in health and disease.
As a multidisciplinary, open-access forum, Frontiers in Network Physiology [127] communicates impactful discoveries to both academics and clinicians, and provides a platform for cutting-edge empirical and theoretical research spanning every level of physiological organization, from metabolic, sub-cellular, and cellular processes to integrated organ systems and the whole organism, while also addressing challenges, current frontiers, and future developments in the field. Frontiers in Network Physiology is committed to advancing the field by providing unrestricted open access to articles and communicating scientific knowledge to researchers and the public [128].
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- New Journal of Physics, Special Issue [129] — Focus on Network Physiology and Network Medicine The first focus issue in the literature devoted to Network Physiology and Network Medicine, 2014-2016 (collection of 26 articles)
- International Summer Institute on Network Physiology (ISINP) [130] — Founded in 2016, ISINP is a global scientific institution fostering the development of Network Physiology, education and collaboration among basic scientists, bio-engineers, physiologists and clinicians, with support from the Alessandro Volta Foundation and the Lake Como School for Advanced Studies.
- Philosophical transactions of the Royal Society A, Theme Issue [131] — Uncovering brain–heart information through advanced signal and image processing, 2016 (collection of 16 articles)
- Physiological Measurement, Special Issue [132] — The new field of Network Physiology: redefining health and disease through networks of physiological interactions, 2017-2019, (collection of 25 articles)
- Frontiers in Physiology, Special Issue [133] — The New Frontier of Network Physiology: From Temporal Dynamics to the Synchronization and Principles of Integration in Networks of Physiological Systems, 2019-2020 (collection of 65 articles)
- The Physiological Society UK Webinar 2025 [30] — Webinar Series 'Network Physiology: Mapping Physiological Networks in Health and Disease' (26 March, 27 March, 02 April, 03 April 2025) hosted by The Physiological Society, UK.
- Google Scholar Group on Network Physiology [134]
- Google Scholar Articles on Network Physiology [135]
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- Functional forms of physiologic coupling, their time variation, and effects of pairwise interactions on the dynamics and control of individual systems
- Network studies on structural and dynamical aspects of physiological subsystems and systems that transcend space and time scales
- Information flow and network topology in relation to cellular and neuronal assemblies and autonomic control of organ systems
- Networks comprising diverse physiological systems and associations between physiologic network structure and function
- Basic principles of hierarchical network organization of individual systems and the entire body
- Evolution of pairwise coupling and network topology with transitions across physiological states
- Role of time-dependent network interactions for emergent transitions in network topology and function
- Networks of physiological networks that transcend interactions of subsystems to interactions among organs
- Self-organization of physiological networks, synergistic principles, and applications
- Control, causality, and higher-order interactions in physiological networks
- Structural and functional connectivity
- Emergence of global behaviors and states from multi-scale networks interactions.
- Mind-Body networks of structural, functional, and metabolic processes in central-autonomic regulation in health and disease; mind-body interventions and effects on physiological networks; impacts on psychological networks and quality of life
- Networks of the central, autonomic, and peripheral nervous systems
- Physiological networks in the emergence of cognition and interception
- Networks of pain signaling from ion channels to brain and organs
- Manipulation, control, and global dynamics of networks in response to clinical treatment
- Physiological networks in exercise, training, fatigue, rehabilitation, and sports medicine
- Network mechanisms underlying clinical conditions such as sleep disorders, coma and traumatic brain injury, and neurodegenerative disorders
- Processes and networks in the endocrine system, their role in hormone release and control, growth, and reproduction
- Effects of aging and frailty on the physiological network and relationship with age-related functional decline
- Temperature regulatory networks
- Networks in the sleep and circadian system
- Network Physiology of Cancer
- Networks in Organoids and Networks of Organiods
- Cascades of failure across systems as encountered in critical care
- Co-controllability of drug-disease-gene networks
- Wound healing-related networks
- Network characteristics and metrics in diagnosis, prognosis and assessments of treatments
- Artificial Intelligence algorithms for Network Physiology
- Developing integrated platforms of biomedical devices and sensor networks for multi-system and multi-modality data recording
- Whole-body multi-modality imaging from cellular to organism level
- The development and curation of large databases; building atlas of dynamic maps of physiological interactions within and across levels, the Human Physiolome
- Development of physiologically inspired AI algorithms, electronic and robotic systems based on the laws and principles of physiologic network interactions
- Network Physiology education in basic sciences and in medicine
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External links
Frontiers in Network Physiology, Frontiers Media
International Summer Institute on Network Physiology
Keck Laboratory for Network Physiology, Boston University
National Center for Complementary and Integrative Health
Google Scholar Articles on Network Physiology
References
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