Network Physiology: Mapping interactions between complex physiological systems

Plamen Ch. Ivanov Network Physiology:Network Physiology: Mapping interactions between Mapping interactions between complex physiological systems complex physiological systems Physics Department, Boston University and Division of Sleep Medicine Brigham and Women’s Hospital & Harvard Medical School Plamen Ch. Ivanov Departamento de Física Aplicada II Málaga University 04 April 2016 Human Organism comprises Human Organism comprises diverse multidiverse multi--component physiological systems component physiological systems Human Organism comprises Human Organism comprises diverse multidiverse multi--component physiological systems component physiological systems Neurologists Cardiologists Medical specialists traditionally focus on single organ systems Cardiologists Pulmonologists Human Organism Human Organism –– Integrated Network Integrated Network Coordinated Interactions of Organ SystemsCoordinated Interactions of Organ Systems Essential to: Maintain Health Generate distinct physiological states Disrupted Communications among Organ SystemsDisrupted Communications among Organ Systems Leads to: 1. Dysfunction of individual systems 2. Collapse of the entire organism Failure of one system may trigger a cascade of failures leading to a breakdown of the entire organism Even structurally intact and functioning individual systems    Not sufficient for Health ! Human Organism Human Organism –– Integrated Network Integrated Network of interconnected and interacting organ systemsof interconnected and interacting organ systems Broad clinical implications: Coma, Multiple Organ Failure Yet, despite the importance to: •understanding basic physiologic functions •clinical relevance we do not know how organ systems dynamically interact as a network to coordinate and optimize their functions    Not sufficient for Health ! ? organ Integrative Physiology Current Research Current Research FocusFocus of Systems Biology and Integrative Physiologyof Systems Biology and Integrative Physiology Vertical Integration sub-cellular tissue Signaling and feedbacks across space/time scales cell Systems Biology Horizontal Integration Macroscopic Epidemiology / Population Health ? Our Research Focus: Horizontal IntegrationOur Research Focus: Horizontal Integration Integration Microscopic Mesoscopic organs tissue cell sub-cellular Vertical Integration Integrative Physiology Systems Biology New Research Direction: New Research Direction: Shifting the focus from single organ systemsShifting the focus from single organ systems to the network of organ interactionsto the network of organ interactions Our Research Program A new field A new fieldA new field A new field Network Physiology needed to probe needed to probe needed to probe needed to probe interactions interactions interactions interactions among diverse among diverse among diverse among diverse physiologic systems. physiologic systems. physiologic systems. physiologic systems. 5 healthy subjects 5 heart failure subjects Local Hurst exponent h(t) New Technology New Diagnostics Multifractal organization in heartbeat fluctuations Level 1: Individual Systems Multicolor ↔ Multifractal Monocolor ↔ Monofractal P.Ch. Ivanov et al. Chaos 11: 641 (2001). time ttime t Local Hurst exponent (6-hour recordings) Motor Activity: Wrist motion fluctuations ? Motivation: Test hypothesis that there are intrinsic stable patterns in human motor activity. LocomotorLocomotor system dynamicssystem dynamics Level 1: Individual Systems Magnitudes of wrist acceleration LocomotorLocomotor system dynamicssystem dynamics Level 1: Individual Systems Motor Activity: Wrist motion fluctuations K. Hu et al. Physica A 337: 307 (2004). P. Ch. Ivanov et al., PNAS 104: 20702 (2007) . K. Hu et al., Neuroscience 149: 508 (2007). • Long-range correlations long-term memory Discovery: Universal scale-invariant organization in human activity fluctuations • Stable distribution over time scales scale invariance in wrist acceleration Smart wristband Protocol α αmag Daily routine 0.92 ±0.05 0.78 ±0.06 Constant routine 0.88 ±0.05 0.82 ±0.05 Forced desynchrony 0.92 0.80 LocomotorLocomotor system dynamics: system dynamics: wrist motion fluctuationswrist motion fluctuations Scaling exponents independent of activity level Level 1: Individual Systems Scaling exponents --- remarkably consistent for: - all subjects - all protocols - all days of the week. Party time! Day of rest! desynchrony ±0.03 ±0.04 Inspiration Heart rate Expiration Heart rate Heart % of mean Heart rate CardioCardio--respiratory Interactionrespiratory Interaction Respiratory Sinus Arrhythmia (RSARespiratory Sinus Arrhythmia (RSA)) Level 2: Pair-wise Coupling Heart Respiration 2345 1 Inspiration Expiration % of mean Heart rate Heart beat number “Synchronization is an adjustment of rhythms of self-sustained oscillators due to their weak interaction.” Pikovsky, Rosenblum, Kurths. Synchronization: a universal concept in nonlinear sciences (Cambridge University Press 2001) Coupled Metronomes CardioCardio--respiratory Interactionrespiratory Interaction Phase SynchronizationPhase Synchronization Level 2: Pair-wise Coupling Start: different frequencies, different phases   No synchronization End: same frequencies, same phase difference (“phase locked”)   Synchronization CardioCardio--respiratory Interactionrespiratory Interaction Phase SynchronizationPhase Synchronization Level 2: Pair-wise Coupling •London: Millennium (“Wobbly”) bridge opening day June 10, 2000 Millenium bridge reopened in February 2002: - after 5 Million £ spent on bridge modifications - research based on work by S. Strogatz et al. Nature 438, 43 (2005) CardioCardio--respiratory Interactionrespiratory Interaction Phase SynchronizationPhase Synchronization Level 2: Pair-wise Coupling Heart Respiration Phases collapse Phase synchronization CardioCardio--respiratory Interactionrespiratory Interaction Phase Synchronization despite continuous fluctuationsPhase Synchronization despite continuous fluctuations Level 2: Pair-wise Coupling Segments of Synchronization Pronounced stratification of synchronization is stable for all age groups CardioCardio--respiratory Interactionrespiratory Interaction Phase SynchronizationPhase Synchronization Level 2: Pair-wise Coupling Discovery: Phase transitions in cardio-respiratory coupling RP Bartsch, AY Schumann, JW Kantelhardt, T Penzel, PCh Ivanov “Phase transitions in physiologic coupling”, PNAS vol. 109, p. 10181 (2012) 400% increase in synchronization from REM to deep sleep Quantifying interactions between diverse systems: concept of Time Delay Stability normalized spectral power of EEG-δband normalized spectral power of EEG-σband Conclusion Network connectivity and link strength of the brain–brain sub-network for different sleep stages Network of networks across sleep stages Transitions in the network of physiological interactions Network of physiological interactions Physiologic recordings Quantifying interactions between diverse systems: concept of Time Delay Stability DataDriven Concept Cross-correlation function vs. time lag in 30 sec windows Time delay vs. real time Time periods of constant time delay indicate stable interaction represented by network links HR – Eye interaction α– Chin interaction α Transitions in the networkTransitions in the network of physiological interactionsof physiological interactions DataDriven Discovery α – Chin link HR – Eye link Dynamical Evolution Fast reorganization of network connectivity with transitions across physiologic states Network connectivity across sleep stages Wake, REM sleep, Light sleep (LS), Deep sleep (DS) Transitions in the network of physiological interactions Network of physiological interactions Physiologic recordings Network Topology & Physiologic Function Network Topology & Physiologic Function connectivity across sleep stagesconnectivity across sleep stages DataDriven Discovery Deep SleepLight SleepREM SleepWake Network link strengthNetwork connectivity Network topology changes with physiologic states Network connectivity Network link strength Individual Group averaged Network of networks across sleep stages Robust sleep-stage stratification pattern Different subnetworks Different physiologic functions Network connectivity and link strength of the brain–brain sub-network for different sleep stages Topology of brain-brain sub-network no change Strength of network links significant change Network connectivity and link strength of the brain–brain sub-network for different sleep stages Network of networks across sleep stages Transitions in the network of physiological interactions Network of physiological interactions Physiologic recordings Transitions in connectivity and link strength of Transitions in connectivity and link strength of individual network nodes across sleep stagesindividual network nodes across sleep stages Heart Chin Robust sleep-stage stratification pattern in: a) Individual node connectivity b) Average link strength of individual nodes Chin Network Physiology Networks of brain activity across sleep stages Phase transition in link strength and network topology Colors: Frequency bands in the EEG signals Location of the nodes: Brain EEG Channels Maps of physiologic interactionsMaps of physiologic interactions signals Width of the links: Coupling strength between the systems Radar Chart in the Hexagon: Brain Control on the target organ Visualization: different physiologic statesVisualization: different physiologic states Maps for different organ systemsMaps for different organ systems Chin Eye Chin Heart Respiration Support: Our Group: http://physics.bu.edu/labnetworkphysiology Support: WM Keck Foundation NIH 1R01-HL098437 US–Israel Binational Science Foundation Grant Office of Naval Research (ONR Grant 000141010078)