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Mo N, Shao S, Cui Z, Bao C. Roles of eyestalk in salinity acclimatization of mud crab (Scylla paramamosain) by transcriptomic analysis. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY. PART D, GENOMICS & PROTEOMICS 2024; 52:101276. [PMID: 38935995 DOI: 10.1016/j.cbd.2024.101276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 05/29/2024] [Accepted: 06/12/2024] [Indexed: 06/29/2024]
Abstract
Salinity acclimatization refers to the physiological and behavioral adjustments made by crustaceans to adapt to varying salinity environments. The eyestalk, a neuroendocrine organ in crustaceans, plays a crucial role in salinity acclimatization. To elucidate the molecular mechanisms underlying eyestalk involvement in mud crab (Scylla paramamosain) acclimatization, we employed RNA-seq technology to analyze transcriptomic changes in the eyestalk under low (5 ppt) and standard (23 ppt) salinity conditions. This analysis revealed 5431 differentially expressed genes (DEGs), with 2372 upregulated and 3059 downregulated. Notably, these DEGs were enriched in crucial biological pathways like metabolism, osmoregulation, and signal transduction. To validate the RNA-seq data, we further analyzed 15 DEGs of interest using qRT-PCR. Our results suggest a multifaceted role for the eyestalk: maintaining energy homeostasis, regulating hormone synthesis and release, PKA activity, and downstream signaling, and ensuring proper ion and osmotic balance. Furthermore, our findings indicate that the crustacean hyperglycemic hormone (CHH) may function as a key regulator, modulating carbonic anhydrase expression through the activation of the PKA signaling pathway, thereby influencing cellular osmoregulation, and associated metabolic processes. Overall, our study provides valuable insights into unraveling the molecular mechanisms of mud crab acclimatization to low salinity environments.
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Affiliation(s)
- Nan Mo
- School of Marine Sciences, Ningbo University, Ningbo 315020, China
| | - Shucheng Shao
- School of Marine Sciences, Ningbo University, Ningbo 315020, China
| | - Zhaoxia Cui
- School of Marine Sciences, Ningbo University, Ningbo 315020, China
| | - Chenchang Bao
- School of Marine Sciences, Ningbo University, Ningbo 315020, China.
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2
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Yoon H. Age-dependent cardiorespiratory directional coupling in wake-resting state. Physiol Meas 2022; 43. [PMID: 36575156 DOI: 10.1088/1361-6579/acaa1b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 12/08/2022] [Indexed: 12/13/2022]
Abstract
Objective.Cooperation in the cardiorespiratory system helps maintain internal stability. Various types of system interactions have been investigated; however, the characteristics of the interactions have mostly been studied using data collected in well-defined physiological states, such as sleep. Furthermore, most analyses provided general information about the interaction, making it difficult to quantify how the systems influenced one another.Approach.Cardiorespiratory directional coupling was investigated in different age groups (20 young and 19 elderly subjects) in a wake-resting state. The directionality index (DI) was calculated using instantaneous phases from the heartbeat interval and respiratory signal to provide information about the strength and direction of interaction between the systems. Statistical analysis was performed between the groups on the DI and independent measures of directionality (ncr: influence from cardiac system to respiratory system, and ncc: influence from the respiratory system to the cardiac system).Main results.The values of DI were -0.52 and -0.17 in the young and elderly groups, respectively (p< 0.001). Furthermore, the values of ncrand nccwere found to be significantly different between the groups (p< 0.001), respectively.Significance.Changes in both directions between the systems influence different aspects of cardiorespiratory coupling between the groups. This observation could be linked to different levels of autonomic modulation associated with ageing. Our approach could aid in quantitatively tracking and comprehending how systems interact in response to physiological and environmental changes. It could also be used to understand how abnormal interaction characteristics influence physiological system dysfunctions and disorders.
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Affiliation(s)
- Heenam Yoon
- Department of Human-Centered Artificial Intelligence, Sangmyung University, Seoul 03016, Republic of Korea
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3
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Abdalbari H, Durrani M, Pancholi S, Patel N, Nasuto SJ, Nicolaou N. Brain and brain-heart Granger causality during wakefulness and sleep. Front Neurosci 2022; 16:927111. [PMID: 36188466 PMCID: PMC9520578 DOI: 10.3389/fnins.2022.927111] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 08/19/2022] [Indexed: 11/13/2022] Open
Abstract
In this exploratory study we apply Granger Causality (GC) to investigate the brain-brain and brain-heart interactions during wakefulness and sleep. Our analysis includes electroencephalogram (EEG) and electrocardiogram (ECG) data during all-night polysomnographic recordings from volunteers with apnea, available from the Massachusetts General Hospital’s Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory. The data is manually annotated by clinical staff at the MGH in 30 second contiguous intervals (wakefulness and sleep stages 1, 2, 3, and rapid eye movement (REM). We applied GC to 4-s non-overlapping segments of available EEG and ECG across all-night recordings of 50 randomly chosen patients. To identify differences in GC between the different sleep stages, the GC for each sleep stage was subtracted from the GC during wakefulness. Positive (negative) differences indicated that GC was greater (lower) during wakefulness compared to the specific sleep stage. The application of GC to study brain-brain and brain-heart bidirectional connections during wakefulness and sleep confirmed the importance of fronto-posterior connectivity during these two states, but has also revealed differences in ipsilateral and contralateral mechanisms of these connections. It has also confirmed the existence of bidirectional brain-heart connections that are more prominent in the direction from brain to heart. Our exploratory study has shown that GC can be successfully applied to sleep data analysis and captures the varying physiological mechanisms that are related to wakefulness and different sleep stages.
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Affiliation(s)
- Helmi Abdalbari
- Department of Basic and Clinical Sciences, University of Nicosia Medical School, Nicosia, Cyprus
| | - Mohammad Durrani
- Department of Basic and Clinical Sciences, University of Nicosia Medical School, Nicosia, Cyprus
| | - Shivam Pancholi
- Department of Basic and Clinical Sciences, University of Nicosia Medical School, Nicosia, Cyprus
| | - Nikhil Patel
- Department of Basic and Clinical Sciences, University of Nicosia Medical School, Nicosia, Cyprus
| | - Slawomir J. Nasuto
- Department of Biomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom
| | - Nicoletta Nicolaou
- Department of Basic and Clinical Sciences, University of Nicosia Medical School, Nicosia, Cyprus
- Center for Neuroscience and Integrative Brain Research (CENIBRE), University of Nicosia Medical School, Nicosia, Cyprus
- *Correspondence: Nicoletta Nicolaou,
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4
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Zschocke J, Bartsch RP, Glos M, Penzel T, Mikolajczyk R, Kantelhardt JW. Long- and short-term fluctuations compared for several organ systems across sleep stages. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:937130. [PMID: 36926083 PMCID: PMC10013069 DOI: 10.3389/fnetp.2022.937130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022]
Abstract
Some details of cardiovascular and cardio-respiratory regulation and their changes during different sleep stages remain still unknown. In this paper we compared the fluctuations of heart rate, pulse rate, respiration frequency, and pulse transit times as well as EEG alpha-band power on time scales from 6 to 200 s during different sleep stages in order to better understand regulatory pathways. The five considered time series were derived from ECG, photoplethysmogram, nasal air flow, and central electrode EEG measurements from full-night polysomnography recordings of 246 subjects with suspected sleep disorders. We applied detrended fluctuation analysis, distinguishing between short-term (6-16 s) and long-term (50-200 s) correlations, i.e., scaling behavior characterized by the fluctuation exponents α 1 and α 2 related with parasympathetic and sympathetic control, respectively. While heart rate (and pulse rate) are characterized by sex and age-dependent short-term correlations, their long-term correlations exhibit the well-known sleep stage dependence: weak long-term correlations during non-REM sleep and pronounced long-term correlations during REM sleep and wakefulness. In contrast, pulse transit times, which are believed to be mainly affected by blood pressure and arterial stiffness, do not show differences between short-term and long-term exponents. This is in constrast to previous results for blood pressure time series, where α 1 was much larger than α 2, and therefore questions a very close relation between pulse transit times and blood pressure values. Nevertheless, very similar sleep-stage dependent differences are observed for the long-term fluctuation exponent α 2 in all considered signals including EEG alpha-band power. In conclusion, we found that the observed fluctuation exponents are very robust and hardly modified by body mass index, alcohol consumption, smoking, or sleep disorders. The long-term fluctuations of all observed systems seem to be modulated by patterns following sleep stages generated in the brain and thus regulated in a similar manner, while short-term regulations differ between the organ systems. Deviations from the reported dependence in any of the signals should be indicative of problems in the function of the particular organ system or its control mechanisms.
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Affiliation(s)
- Johannes Zschocke
- Institute of Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Martin-Luther-University Halle-Wittenberg, Halle, Germany.,Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Ronny P Bartsch
- Department of Physics, Bar-Ilan University, Ramat Gan, Israel
| | - Martin Glos
- Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Thomas Penzel
- Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Rafael Mikolajczyk
- Institute of Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Jan W Kantelhardt
- Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
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5
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Günther M, Kantelhardt JW, Bartsch RP. The Reconstruction of Causal Networks in Physiology. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:893743. [PMID: 36926108 PMCID: PMC10013035 DOI: 10.3389/fnetp.2022.893743] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/06/2022] [Indexed: 11/13/2022]
Abstract
We systematically compare strengths and weaknesses of two methods that can be used to quantify causal links between time series: Granger-causality and Bivariate Phase Rectified Signal Averaging (BPRSA). While a statistical test method for Granger-causality has already been established, we show that BPRSA causality can also be probed with existing statistical tests. Our results indicate that more data or stronger interactions are required for the BPRSA method than for the Granger-causality method to detect an existing link. Furthermore, the Granger-causality method can distinguish direct causal links from indirect links as well as links that arise from a common source, while BPRSA cannot. However, in contrast to Granger-causality, BPRSA is suited for the analysis of non-stationary data. We demonstrate the practicability of the Granger-causality method by applying it to polysomnography data from sleep laboratories. An algorithm is presented, which addresses the stationarity condition of Granger-causality by splitting non-stationary data into shorter segments until they pass a stationarity test. We reconstruct causal networks of heart rate, breathing rate, and EEG amplitude from young healthy subjects, elderly healthy subjects, and subjects with obstructive sleep apnea, a condition that leads to disruption of normal respiration during sleep. These networks exhibit differences not only between different sleep stages, but also between young and elderly healthy subjects on the one hand and subjects with sleep apnea on the other hand. Among these differences are 1) weaker interactions in all groups between heart rate, breathing rate and EEG amplitude during deep sleep, compared to light and REM sleep, 2) a stronger causal link from heart rate to breathing rate but disturbances in respiratory sinus arrhythmia (breathing to heart rate coupling) in subjects with sleep apnea, 3) a stronger causal link from EEG amplitude to breathing rate during REM sleep in subjects with sleep apnea. The Granger-causality method, although initially developed for econometric purposes, can provide a quantitative, testable measure for causality in physiological networks.
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Affiliation(s)
| | - Jan W Kantelhardt
- Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Ronny P Bartsch
- Department of Physics, Bar-Ilan University, Ramat Gan, Israel
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6
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Borovkova EI, Prokhorov MD, Kiselev AR, Hramkov AN, Mironov SA, Agaltsov MV, Ponomarenko VI, Karavaev AS, Drapkina OM, Penzel T. Directional couplings between the respiration and parasympathetic control of the heart rate during sleep and wakefulness in healthy subjects at different ages. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:942700. [PMID: 36926072 PMCID: PMC10013057 DOI: 10.3389/fnetp.2022.942700] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/15/2022] [Indexed: 11/13/2022]
Abstract
Cardiorespiratory interactions are important, both for understanding the fundamental processes of functioning of the human body and for development of methods for diagnostics of various pathologies. The properties of cardiorespiratory interaction are determined by the processes of autonomic control of blood circulation, which are modulated by the higher nervous activity. We study the directional couplings between the respiration and the process of parasympathetic control of the heart rate in the awake state and different stages of sleep in 96 healthy subjects from different age groups. The detection of directional couplings is carried out using the method of phase dynamics modeling applied to experimental RR-intervals and the signal of respiration. We reveal the presence of bidirectional couplings between the studied processes in all age groups. Our results show that the coupling from respiration to the process of parasympathetic control of the heart rate is stronger than the coupling in the opposite direction. The difference in the strength of bidirectional couplings between the considered processes is most pronounced in deep sleep.
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Affiliation(s)
- Ekaterina I Borovkova
- National Medical Research Center for Therapy and Preventive Medicine, Moscow, Russia
| | - Mikhail D Prokhorov
- Smart Sleep Laboratory, Saratov State University, Saratov, Russia.,Laboratory of Nonlinear Dynamics Modeling, Saratov Branch of Kotelnikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, Saratov, Russia
| | - Anton R Kiselev
- National Medical Research Center for Therapy and Preventive Medicine, Moscow, Russia.,Institute of Cardiological Research, Saratov State Medical University, Saratov, Russia
| | | | - Sergey A Mironov
- National Medical Research Center for Therapy and Preventive Medicine, Moscow, Russia
| | - Mikhail V Agaltsov
- National Medical Research Center for Therapy and Preventive Medicine, Moscow, Russia
| | - Vladimir I Ponomarenko
- Smart Sleep Laboratory, Saratov State University, Saratov, Russia.,Laboratory of Nonlinear Dynamics Modeling, Saratov Branch of Kotelnikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, Saratov, Russia
| | - Anatoly S Karavaev
- Smart Sleep Laboratory, Saratov State University, Saratov, Russia.,Laboratory of Nonlinear Dynamics Modeling, Saratov Branch of Kotelnikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, Saratov, Russia.,Institute of Cardiological Research, Saratov State Medical University, Saratov, Russia
| | - Oksana M Drapkina
- National Medical Research Center for Therapy and Preventive Medicine, Moscow, Russia
| | - Thomas Penzel
- Smart Sleep Laboratory, Saratov State University, Saratov, Russia.,Interdisciplinary Sleep Medicine Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
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7
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Ivanov PC. The New Field of Network Physiology: Building the Human Physiolome. FRONTIERS IN NETWORK PHYSIOLOGY 2021; 1:711778. [PMID: 36925582 PMCID: PMC10013018 DOI: 10.3389/fnetp.2021.711778] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 05/21/2021] [Indexed: 12/22/2022]
Affiliation(s)
- Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States.,Harvard Medical School and Division of Sleep Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Bulgarian Academy of Sciences, Institute of Solid State Physics, Sofia, Bulgaria
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8
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Romero-Ortuño R, Martínez-Velilla N, Sutton R, Ungar A, Fedorowski A, Galvin R, Theou O, Davies A, Reilly RB, Claassen J, Kelly ÁM, Ivanov PC. Network Physiology in Aging and Frailty: The Grand Challenge of Physiological Reserve in Older Adults. FRONTIERS IN NETWORK PHYSIOLOGY 2021; 1:712430. [PMID: 36925570 PMCID: PMC10012993 DOI: 10.3389/fnetp.2021.712430] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 06/25/2021] [Indexed: 12/29/2022]
Affiliation(s)
- Román Romero-Ortuño
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.,Mercer's Institute for Successful Ageing, St James's Hospital, Dublin, Ireland.,Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Nicolás Martínez-Velilla
- Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Public University of Navarra (UPNA), Navarra Health Research Institute (IdisNa), Pamplona, Spain
| | - Richard Sutton
- Faculty of Medicine, Imperial College London, Heart Science, National Heart and Lung Institute, London, United Kingdom
| | - Andrea Ungar
- Geriatric Department, University of Florence and Azienda Ospedaliero Universitaria Careggi, Florence, Italy
| | - Artur Fedorowski
- Department of Clinical Sciences, Lund University and Department of Cardiology, Skåne University Hospital, Malmo, Sweden
| | - Rose Galvin
- Ageing Research Centre, School of Allied Health, Health Research Institute, University of Limerick, Limerick, Ireland
| | - Olga Theou
- Physiotherapy and Geriatric Medicine, Dalhousie University, Halifax, NS, Canada
| | - Andrew Davies
- School of Medicine, Trinity College Dublin, University College Dublin and Our Lady's Hospice and Care Services, Dublin, Ireland
| | - Richard B Reilly
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland.,Trinity Centre for Biomedical Engineering, Trinity College Dublin, Dublin, Ireland
| | - Jurgen Claassen
- Department of Geriatric Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - Áine M Kelly
- Discipline of Physiology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Boston University, Boston, MA, United States
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9
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Wessel N, Berg K, Kraemer JF, Gapelyuk A, Rietsch K, Hauser T, Kurths J, Wenzel D, Klein N, Kolb C, Belke R, Schirdewan A, Kääb S. Cardiac Autonomic Dysfunction and Incidence of de novo Atrial Fibrillation: Heart Rate Variability vs. Heart Rate Complexity. Front Physiol 2020; 11:596844. [PMID: 33363477 PMCID: PMC7752808 DOI: 10.3389/fphys.2020.596844] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/13/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND The REACT DX registry evaluates standard therapies to episodes of long-lasting atrial tachyarrhythmias and assesses the quality of sensing and stability of the lead and the implantable cardioverter-defibrillator (ICD) (BIOTRONIK Lumax VR-T DX and successors) over at least a 1-year follow-up period. OBJECTIVE To study the association between the risk of de novo device-detected atrial fibrillation (AF), the autonomic perturbations before the onset of paroxysmal AF and a 7-days heart rate variability (7dHRV) 1 month after ICD implantation. METHODS The registry consists of 234 patients implanted with an ICD, including 10 with de novo long-lasting atrial tachyarrhythmias with no prior history of AF. The patients were matched via the propensity-score methodology as well as for properties directly influencing the ECGs recorded using GE CardioMem CM 3000. Heart rate variability (HRV) analysis was performed using standard parameters from time- and frequency-domains, and from non-linear dynamics. RESULTS No linear HRV was associated with an increased risk of AF (p = n.s.). The only significant approach was derived from symbolic dynamics with the parameter "forbidden words" which distinguished both groups on all 7 days of measurements (p < 0.05), thereby quantifying the heart rate complexity (HRC) as drastically lower in the de novo AF group. CONCLUSION Cardiac autonomic dysfunction denoted by low HRC may be associated with higher AF incidence. For patients with mild to moderate heart failure, standard HRV parameters are not appropriate to quantify cardiac autonomic perturbations before the onset of AF. Further studies are needed to determine the individual risk for AF that would enable interventions to restore autonomic balance in the general population.
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Affiliation(s)
- Niels Wessel
- Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Karsten Berg
- Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jan F. Kraemer
- Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andrej Gapelyuk
- Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | | | - Jürgen Kurths
- Department of Physics, Humboldt-Universität zu Berlin, Berlin, Germany
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
- Centre for Analysis of Complex Systems, Sechenov First Moscow State Medical University, Moscow, Russia
| | - Dave Wenzel
- Clinic for Cardiology and Angiology, University Hospital Magdeburg, Magdeburg, Germany
| | | | - Christof Kolb
- Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Abteilung für Elektrophysiologie, Faculty of Medicine, Technische Universität München, Munich, Germany
| | | | | | - Stefan Kääb
- Medical Center of Ludwig-Maximilians-University of Munich, Munich, Germany
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10
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Zschocke J, Kluge M, Pelikan L, Graf A, Glos M, Müller A, Mikolajczyk R, Bartsch RP, Penzel T, Kantelhardt JW. Detection and analysis of pulse waves during sleep via wrist-worn actigraphy. PLoS One 2019; 14:e0226843. [PMID: 31891612 PMCID: PMC6938353 DOI: 10.1371/journal.pone.0226843] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 12/04/2019] [Indexed: 11/19/2022] Open
Abstract
The high temporal and intensity resolution of modern accelerometers gives the opportunity of detecting even tiny body movements via motion-based sensors. In this paper, we demonstrate and evaluate an approach to identify pulse waves and heartbeats from acceleration data of the human wrist during sleep. Specifically, we have recorded simultaneously full-night polysomnography and 3d wrist actigraphy data of 363 subjects during one night in a clinical sleep laboratory. The acceleration data was segmented and cleaned, excluding body movements and separating episodes with different sleep positions. Then, we applied a bandpass filter and a Hilbert transform to uncover the pulse wave signal, which worked well for an average duration of 1.7 h per subject. We found that 81 percent of the detected pulse wave intervals could be correctly associated with the R peak intervals from independently recorded ECGs and obtained a median Pearson cross-correlation of 0.94. While the low-frequency components of both signals were practically identical, the high-frequency component of the pulse wave interval time series was increased, indicating a respiratory modulation of pulse transit times, probably as an additional contribution to respiratory sinus arrhythmia. Our approach could be used to obtain long-term nocturnal heartbeat interval time series and pulse wave signals from wrist-worn accelerometers without the need of recording ECG or photoplethysmography. This is particularly useful for an ambulatory monitoring of high-risk cardiac patients as well as for assessing cardiac dynamics in large cohort studies solely with accelerometer devices that are already used for activity tracking and sleep pattern analysis.
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Affiliation(s)
- Johannes Zschocke
- Institute of Medical Epidemiology, Biostatistics and Informatics, Faculty of Medicine, Martin-Luther-University Halle-Wittenberg, Halle, Germany
- Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Maria Kluge
- Interdisziplinäres Schlafmedizinisches Zentrum, Charite - Universitätsmedizin Berlin, Berlin, Germany
| | - Luise Pelikan
- Interdisziplinäres Schlafmedizinisches Zentrum, Charite - Universitätsmedizin Berlin, Berlin, Germany
| | - Antonia Graf
- Interdisziplinäres Schlafmedizinisches Zentrum, Charite - Universitätsmedizin Berlin, Berlin, Germany
| | - Martin Glos
- Interdisziplinäres Schlafmedizinisches Zentrum, Charite - Universitätsmedizin Berlin, Berlin, Germany
| | - Alexander Müller
- Klinik und Poliklinik für Innere Medizin I, Technische Universität München, Munich, Germany
| | - Rafael Mikolajczyk
- Institute of Medical Epidemiology, Biostatistics and Informatics, Faculty of Medicine, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | | | - Thomas Penzel
- Interdisziplinäres Schlafmedizinisches Zentrum, Charite - Universitätsmedizin Berlin, Berlin, Germany
| | - Jan W. Kantelhardt
- Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
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11
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Critical Dynamics and Coupling in Bursts of Cortical Rhythms Indicate Non-Homeostatic Mechanism for Sleep-Stage Transitions and Dual Role of VLPO Neurons in Both Sleep and Wake. J Neurosci 2019; 40:171-190. [PMID: 31694962 DOI: 10.1523/jneurosci.1278-19.2019] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Revised: 09/07/2019] [Accepted: 10/07/2019] [Indexed: 11/21/2022] Open
Abstract
Origin and functions of intermittent transitions among sleep stages, including brief awakenings and arousals, constitute a challenge to the current homeostatic framework for sleep regulation, focusing on factors modulating sleep over large time scales. Here we propose that the complex micro-architecture characterizing sleep on scales of seconds and minutes results from intrinsic non-equilibrium critical dynamics. We investigate θ- and δ-wave dynamics in control rats and in rats where the sleep-promoting ventrolateral preoptic nucleus (VLPO) is lesioned (male Sprague-Dawley rats). We demonstrate that bursts in θ and δ cortical rhythms exhibit complex temporal organization, with long-range correlations and robust duality of power-law (θ-bursts, active phase) and exponential-like (δ-bursts, quiescent phase) duration distributions, features typical of non-equilibrium systems self-organizing at criticality. We show that such non-equilibrium behavior relates to anti-correlated coupling between θ- and δ-bursts, persists across a range of time scales, and is independent of the dominant physiologic state; indications of a basic principle in sleep regulation. Further, we find that VLPO lesions lead to a modulation of cortical dynamics resulting in altered dynamical parameters of θ- and δ-bursts and significant reduction in θ-δ coupling. Our empirical findings and model simulations demonstrate that θ-δ coupling is essential for the emerging non-equilibrium critical dynamics observed across the sleep-wake cycle, and indicate that VLPO neurons may have dual role for both sleep and arousal/brief wake activation. The uncovered critical behavior in sleep- and wake-related cortical rhythms indicates a mechanism essential for the micro-architecture of spontaneous sleep-stage and arousal transitions within a novel, non-homeostatic paradigm of sleep regulation.SIGNIFICANCE STATEMENT We show that the complex micro-architecture of sleep-stage/arousal transitions arises from intrinsic non-equilibrium critical dynamics, connecting the temporal organization of dominant cortical rhythms with empirical observations across scales. We link such behavior to sleep-promoting neuronal population, and demonstrate that VLPO lesion (model of insomnia) alters dynamical features of θ and δ rhythms, and leads to significant reduction in θ-δ coupling. This indicates that VLPO neurons may have dual role for both sleep and arousal/brief wake control. The reported empirical findings and modeling simulations constitute first evidences of a neurophysiological fingerprint of self-organization and criticality in sleep- and wake-related cortical rhythms; a mechanism essential for spontaneous sleep-stage and arousal transitions that lays the bases for a novel, non-homeostatic paradigm of sleep regulation.
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12
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Wang JWJL, Lombardi F, Zhang X, Anaclet C, Ivanov PC. Non-equilibrium critical dynamics of bursts in θ and δ rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Comput Biol 2019; 15:e1007268. [PMID: 31725712 PMCID: PMC6855414 DOI: 10.1371/journal.pcbi.1007268] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 07/11/2019] [Indexed: 01/08/2023] Open
Abstract
Origin and functions of intermittent transitions among sleep stages, including short awakenings and arousals, constitute a challenge to the current homeostatic framework for sleep regulation, focusing on factors modulating sleep over large time scales. Here we propose that the complex micro-architecture characterizing the sleep-wake cycle results from an underlying non-equilibrium critical dynamics, bridging collective behaviors across spatio-temporal scales. We investigate θ and δ wave dynamics in control rats and in rats with lesions of sleep-promoting neurons in the parafacial zone. We demonstrate that intermittent bursts in θ and δ rhythms exhibit a complex temporal organization, with long-range power-law correlations and a robust duality of power law (θ-bursts, active phase) and exponential-like (δ-bursts, quiescent phase) duration distributions, typical features of non-equilibrium systems self-organizing at criticality. Crucially, such temporal organization relates to anti-correlated coupling between θ- and δ-bursts, and is independent of the dominant physiologic state and lesions, a solid indication of a basic principle in sleep dynamics.
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Affiliation(s)
- Jilin W. J. L. Wang
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts, United States of America
| | - Fabrizio Lombardi
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts, United States of America
- Institute of Science and Technology Austria, A-3400 Klosterneuburg, Austria
| | - Xiyun Zhang
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts, United States of America
| | - Christelle Anaclet
- Department of Neurobiology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
- Department of Neurology, Division of Sleep Medicine, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Plamen Ch. Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts, United States of America
- Department of Neurology, Division of Sleep Medicine, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
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13
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Yeh CH, Juan CH, Yeh HM, Wang CY, Young HWV, Lin JL, Lin C, Lin LY, Lo MT. The critical role of respiratory sinus arrhythmia on temporal cardiac dynamics. J Appl Physiol (1985) 2019; 127:1733-1741. [PMID: 31647722 DOI: 10.1152/japplphysiol.00262.2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Temporal cardiac properties provide alternative information in analyzing heart rate variability (HRV), which may be disregarded by the standard HRV analyses. Patients with congestive heart failure (CHF) are known to have distinct temporal features from the healthy individuals. However, the underlying mechanism leading to the variation remains unclear. Whether or not these parameters can finely classify the severity for CHF patients is uncertain as well. In this work, an electrocardiogram was monitored in advanced CHF patients using 24-h Holter in four conditions, including baseline, one and three months after atenolol therapy, and healthy individuals. Slope and area under the curve (AUC) of multiscale entropy (MSE) curve over short (scales 1-5) and long (scales 6-20) scales, and detrended fluctuation analysis (DFA) scaling exponents at short (4-11 beats) and intermediate (>11 beats) window sizes were calculated. The results show that short-time scale MSE-derived parameters (slope: -0.08 ± 0.10, -0.03 ± 0.10, 0.02 ± 0.06, 0.08 ± 0.06; AUC: 4.03 ± 2.11, 4.69 ± 1.28, 4.73 ± 0.94, and 6.17 ± 1.23) and short-time scale DFA exponent (0.79 ± 0.16, 0.95 ± 0.22, 1.11 ± 0.19, and 1.35 ± 0.20) can hierarchically classify all four conditions. More importantly, simulated R-R intervals with different fractions and amplitude of respiratory sinus arrhythmia (RSA) components were examined to validate our hypothesis regarding the essentiality of RSA in the improvement of cardiovascular function, and its tight association with unpredictability and fractal property of HRV, which is in line with our hypothesis that RSA contributes significantly to the generation of the unpredictability and fractal behavior of HR dynamics.NEW & NOTEWORTHY Temporal cardiac properties provide useful diagnostic parameters for patients with congestive heart failure (CHF). Our study hierarchically classified CHF patients with β-blocker treatment by using multiscale entropy and detrended fluctuation analysis. Also, we provided the evidence to validate the critical role of respiratory sinus arrhythmia in the fractal properties of heart rate variability.
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Affiliation(s)
- Chien-Hung Yeh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Chung-Hau Juan
- Department of Biomedical Sciences, National Central University, Taoyuan, Taiwan.,Department of Anesthesiology, Cathay General Hospital, Taipei, Taiwan
| | - Huei-Ming Yeh
- Department of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan
| | - Cheng-Yen Wang
- Department of Biomedical Sciences, National Central University, Taoyuan, Taiwan
| | - Hsu-Wen Vincent Young
- Department of Biomedical Sciences, National Central University, Taoyuan, Taiwan.,Department of Applied Mathematics, Chung Yuan Christian University, Taoyuan, Taiwan
| | - Jiunn-Lee Lin
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen Lin
- Department of Biomedical Sciences, National Central University, Taoyuan, Taiwan
| | - Lian-Yu Lin
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Men-Tzung Lo
- Department of Biomedical Sciences, National Central University, Taoyuan, Taiwan
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Bocaccio H, Pallavicini C, Castro MN, Sánchez SM, De Pino G, Laufs H, Villarreal MF, Tagliazucchi E. The avalanche-like behaviour of large-scale haemodynamic activity from wakefulness to deep sleep. J R Soc Interface 2019; 16:20190262. [PMID: 31506046 PMCID: PMC6769314 DOI: 10.1098/rsif.2019.0262] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 08/08/2019] [Indexed: 02/02/2023] Open
Abstract
Increasing evidence suggests that responsiveness is associated with critical or near-critical cortical dynamics, which exhibit scale-free cascades of spatio-temporal activity. These cascades, or 'avalanches', have been detected at multiple scales, from in vitro and in vivo microcircuits to voltage imaging and brain-wide functional magnetic resonance imaging (fMRI) recordings. Criticality endows the cortex with certain information-processing capacities postulated as necessary for conscious wakefulness, yet it remains unknown how unresponsiveness impacts on the avalanche-like behaviour of large-scale human haemodynamic activity. We observed a scale-free hierarchy of co-activated connected clusters by applying a point-process transformation to fMRI data recorded during wakefulness and non-rapid eye movement (NREM) sleep. Maximum-likelihood estimates revealed a significant effect of sleep stage on the scaling parameters of the cluster size power-law distributions. Post hoc statistical tests showed that differences were maximal between wakefulness and N2 sleep. These results were robust against spatial coarse graining, fitting alternative statistical models and different point-process thresholds, and disappeared upon phase shuffling the fMRI time series. Evoked neural bistabilities preventing arousals during N2 sleep do not suffice to explain these differences, which point towards changes in the intrinsic dynamics of the brain that could be necessary to consolidate a state of deep unresponsiveness.
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Affiliation(s)
- H. Bocaccio
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Física, FCEyN, UBA, e Instituto de Física de Buenos Aires (IFIBA), Buenos Aires, Argentina
| | - C. Pallavicini
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Física, FCEyN, UBA, e Instituto de Física de Buenos Aires (IFIBA), Buenos Aires, Argentina
| | - M. N. Castro
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Fisiología, Facultad de Medicina, UBA, Buenos Aires, Argentina
- Departamento Salud Mental, Unidad Docente FLENI, Facultad de Medicina, UBA, Buenos Aires, Argentina
| | - S. M. Sánchez
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Física, FCEyN, UBA, e Instituto de Física de Buenos Aires (IFIBA), Buenos Aires, Argentina
| | - G. De Pino
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina
- Laboratorio de Neuroimágenes, Departamento de Imágenes, FLENI, Buenos Aires, Argentina
- Escuela de Ciencia y Tecnología (ECyT), Universidad Nacional de San Martín, Argentina
| | - H. Laufs
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | - M. F. Villarreal
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta, Instituto de Neurociencias FLENI-CONICET, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Física, FCEyN, UBA, e Instituto de Física de Buenos Aires (IFIBA), Buenos Aires, Argentina
| | - E. Tagliazucchi
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Departamento de Física, FCEyN, UBA, e Instituto de Física de Buenos Aires (IFIBA), Buenos Aires, Argentina
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15
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Burlando B, Blanchini F, Giordano G. Loop analysis of blood pressure/volume homeostasis. PLoS Comput Biol 2019; 15:e1007346. [PMID: 31513566 PMCID: PMC6759193 DOI: 10.1371/journal.pcbi.1007346] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2019] [Revised: 09/24/2019] [Accepted: 08/20/2019] [Indexed: 02/06/2023] Open
Abstract
We performed a mathematical analysis of the dynamic control loops regulating the vasomotor tone of vascular smooth muscle, blood volume, and mean arterial pressure, which involve the arginine vasopressin (AVP) system, the atrial natriuretic peptide system (ANP), and the renin-angiotensin-aldosterone system (RAAS). Our loop analysis of the AVP-ANP-RAAS system revealed the concurrent presence of two different regulatory mechanisms, which perform the same qualitative function: one affects blood pressure by regulating vasoconstriction, the other by regulating blood volume. Both the systems are candidate oscillators consisting of the negative-feedback loop of a monotone system: they admit a single equilibrium that can either be stable or give rise to oscillatory instability. Also a subsystem, which includes ANP and AVP stimulation of vascular smooth muscle cells, turns out to be a candidate oscillator composed of a monotone system with multiple negative feedback loops, and we show that its oscillatory potential is higher when the delays along all feedback loops are comparable. Our results give insight into the physiological mechanisms ruling long-term homeostasis of blood hydraulic parameters, which operate based on dynamical loops of interactions. The efficiency and resilience of our body are guaranteed by the presence of myriads of dynamic control loops that regulate fundamental vital functions. In this work, we studied the regulatory mechanisms that govern the interplay of vasoconstriction/vasodilation, blood volume and mean arterial pressure. We analysed the loops in the system and showed the presence of two coexisting mechanisms for blood pressure regulation, which perform the same qualitative function, conferring robustness to the system: one mechanism tunes vasoconstriction, the other blood volume. We showed that both systems are candidate oscillators: either they are stable or they oscillate regularly around their unique equilibrium. We analysed a subsystem that describes the stimulation of vascular smooth muscle cells due to the hormones arginine vasopressin (AVP) and atrial natriuretic peptide (ANP): also this system is a candidate oscillator ruled by multiple negative-feedback loops, and its potential for oscillations is higher when all the loops have similar delay. Our results cast light on the fundamental physiological phenomena that preserve the stable functioning of blood pressure and volume. This could have even wider relevance if other homeostasis and endocrine systems displayed similar features, with repercussions on the management of adverse homeostasis shifts like hypertension.
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Affiliation(s)
- Bruno Burlando
- Department of Pharmacy (DIFAR), University of Genova, Genova, Italy
- Biophysics Institute, National Research Council (CNR), Genova, Italy
| | - Franco Blanchini
- Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy
| | - Giulia Giordano
- Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
- * E-mail:
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16
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Günther M, Bartsch RP, Miron-Shahar Y, Hassin-Baer S, Inzelberg R, Kurths J, Plotnik M, Kantelhardt JW. Coupling Between Leg Muscle Activation and EEG During Normal Walking, Intentional Stops, and Freezing of Gait in Parkinson's Disease. Front Physiol 2019; 10:870. [PMID: 31354521 PMCID: PMC6639586 DOI: 10.3389/fphys.2019.00870] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 06/21/2019] [Indexed: 11/13/2022] Open
Abstract
In this paper, we apply novel techniques for characterizing leg muscle activation patterns via electromyograms (EMGs) and for relating them to changes in electroencephalogram (EEG) activity during gait experiments. Specifically, we investigate changes of leg-muscle EMG amplitudes and EMG frequencies during walking, intentional stops, and unintended freezing-of-gait (FOG) episodes. FOG is a frequent paroxysmal gait disturbance occurring in many patients suffering from Parkinson's disease (PD). We find that EMG amplitudes and frequencies do not change significantly during FOG episodes with respect to walking, while drastic changes occur during intentional stops. Phase synchronization between EMG signals is most pronounced during walking in controls and reduced in PD patients. By analyzing cross-correlations between changes in EMG patterns and brain-wave amplitudes (from EEGs), we find an increase in EEG-EMG coupling at the beginning of stop and FOG episodes. Our results may help to better understand the enigmatic pathophysiology of FOG, to differentiate between FOG events and other gait disturbances, and ultimately to improve diagnostic procedures for patients suffering from PD.
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Affiliation(s)
- Moritz Günther
- Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
- Department of Physics, Bar-Ilan University, Ramat Gan, Israel
| | | | - Yael Miron-Shahar
- Center of Advanced Technologies in Rehabilitation, Sheba Medical Center, Tel Hashomer, Israel
- Neuroscience Department, Sackler Faculty of Medicine, School of Graduate Studies, Tel-Aviv University, Tel Aviv, Israel
| | - Sharon Hassin-Baer
- Sagol Neuroscience Center and Department of Neurology, Sheba Medical Center, Movement Disorders Institute, Tel-Hashomer, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel
| | - Rivka Inzelberg
- Department of Neurology and Neurosurgery, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Applied Mathematics and Computer Science, The Weizmann Institute of Science, Rehovot, Israel
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
- Department of Physics, Humboldt University of Berlin, Berlin, Germany
- Saratov State University, Saratov, Russia
| | - Meir Plotnik
- Center of Advanced Technologies in Rehabilitation, Sheba Medical Center, Tel Hashomer, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Physiology and Pharmacology, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Gonda Brain Research Center, Bar Ilan University, Ramat-Gan, Israel
| | - Jan W. Kantelhardt
- Institute of Physics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
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17
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Platiša MM, Radovanović NN, Kalauzi A, Milašinović G, Pavlović SU. Differentiation of Heart Failure Patients by the Ratio of the Scaling Exponents of Cardiac Interbeat Intervals. Front Physiol 2019; 10:570. [PMID: 31139094 PMCID: PMC6527786 DOI: 10.3389/fphys.2019.00570] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 04/24/2019] [Indexed: 11/13/2022] Open
Abstract
Heart failure (HF) is one of the most frequent heart diseases. It is usually characterized with structural and functional cardiac abnormalities followed by dysfunction of autonomic cardiac control. Current methods of heartbeat interval analysis are not capable to differentiate HF patients and some new differentiation of HF patients could be useful in the determination of the direction of their treatment. In this study, we examined potential of the ratio of the short-term and long-term scaling exponents (α 1 and α 2) to separate HF patients with similar level of reduced cardiac autonomic nervous system control and with no significant difference in age, left ventricular ejection fraction (LVEF) and NYHA class. Thirty-five healthy control subjects and 46 HF patients underwent 20 min of continuous supine resting ECG recording. The interbeat interval time series were analyzed using standardized power spectrum analysis, detrended fluctuation analysis method and standard Poincaré plot (PP) analysis with measures of asymmetry of the PP. Compared with healthy control group, in HF patients linear measures of autonomic cardiac control were statistically significantly reduced (p < 0.05), heart rate asymmetry was preserved (C up > C down, p < 0.01), and long-term scaling exponent α 2 was significantly higher. Cluster analysis of the ratio of short- and long-term scaling exponents showed capability of this parameter to separate four clusters of HF patients. Clusters were determined by interplay of presence of short-term and long-term correlations in interbeat intervals. Complementary measure, commonly accepted ratio of the PP descriptors, SD2/SD1, showed tendency toward statistical significance to separate HF patients in obtained clusters. Also, heart rate asymmetry was preserved only in two clusters. Finally, a multiple regression analysis showed that the ratio α 1/α 2 could be used as an integrated measure of cardiac dynamic with complex physiological background which, besides spectral components as measures of autonomic cardiac control, also involves breathing frequency and mechanical cardiac parameter, left ventricular ejection fraction.
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Affiliation(s)
- Mirjana M. Platiša
- Institute of Biophysics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | | | - Aleksandar Kalauzi
- Department for Life Sciences, Institute for Multidisciplinary Research, University of Belgrade, Belgrade, Serbia
| | - Goran Milašinović
- Pacemaker Center, Clinical Center of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Siniša U. Pavlović
- Pacemaker Center, Clinical Center of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
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18
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Yoon H, Choi SH, Kim SK, Kwon HB, Oh SM, Choi JW, Lee YJ, Jeong DU, Park KS. Human Heart Rhythms Synchronize While Co-sleeping. Front Physiol 2019; 10:190. [PMID: 30914965 PMCID: PMC6421336 DOI: 10.3389/fphys.2019.00190] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 02/14/2019] [Indexed: 11/13/2022] Open
Abstract
Human physiological systems have a major role in maintenance of internal stability. Previous studies have found that these systems are regulated by various types of interactions associated with physiological homeostasis. However, whether there is any interaction between these systems in different individuals is not well-understood. The aim of this research was to determine whether or not there is any interaction between the physiological systems of independent individuals in an environment where they are connected with one another. We investigated the heart rhythms of co-sleeping individuals and found evidence that in co-sleepers, not only do independent heart rhythms appear in the same relative phase for prolonged periods, but also that their occurrence has a bidirectional causal relationship. Under controlled experimental conditions, this finding may be attributed to weak cardiac vibration delivered from one individual to the other via a mechanical bed connection. Our experimental approach could help in understanding how sharing behaviors or social relationships between individuals are associated with interactions of physiological systems.
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Affiliation(s)
- Heenam Yoon
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Sang Ho Choi
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Sang Kyong Kim
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Hyun Bin Kwon
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Seong Min Oh
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, South Korea
| | - Jae-Won Choi
- Department of Neuropsychiatry, Eulji University School of Medicine, Eulji General Hospital, Seoul, South Korea
| | - Yu Jin Lee
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, South Korea
| | - Do-Un Jeong
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, South Korea
| | - Kwang Suk Park
- Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul, South Korea
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Yoon H, Choi SH, Kwon HB, Kim SK, Hwang SH, Oh SM, Choi JW, Lee YJ, Jeong DU, Park KS. Sleep-Dependent Directional Coupling of Cardiorespiratory System in Patients With Obstructive Sleep Apnea. IEEE Trans Biomed Eng 2018; 65:2847-2854. [DOI: 10.1109/tbme.2018.2819719] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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20
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Racz FS, Stylianou O, Mukli P, Eke A. Multifractal Dynamic Functional Connectivity in the Resting-State Brain. Front Physiol 2018; 9:1704. [PMID: 30555345 PMCID: PMC6284038 DOI: 10.3389/fphys.2018.01704] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Accepted: 11/12/2018] [Indexed: 11/23/2022] Open
Abstract
Assessing the functional connectivity (FC) of the brain has proven valuable in enhancing our understanding of brain function. Recent developments in the field demonstrated that FC fluctuates even in the resting state, which has not been taken into account by the widely applied static approaches introduced earlier. In a recent study using functional near-infrared spectroscopy (fNIRS) global dynamic functional connectivity (DFC) has also been found to fluctuate according to scale-free i.e., fractal dynamics evidencing the true multifractal (MF) nature of DFC in the human prefrontal cortex. Expanding on these findings, we performed electroencephalography (EEG) measurements in 14 regions over the whole cortex of 24 healthy, young adult subjects in eyes open (EO) and eyes closed (EC) states. We applied dynamic graph theoretical analysis to capture DFC by computing the pairwise time-dependent synchronization between brain regions and subsequently calculating the following dynamic graph topological measures: Density, Clustering Coefficient, and Efficiency. We characterized the dynamic nature of these global network metrics as well as local individual connections in the networks using focus-based multifractal time series analysis in all traditional EEG frequency bands. Global network topological measures were found fluctuating–albeit at different extent–according to true multifractal nature in all frequency bands. Moreover, the monofractal Hurst exponent was found higher during EC than EO in the alpha and beta bands. Individual connections showed a characteristic topology in their fractal properties, with higher autocorrelation owing to short-distance connections–especially those in the frontal and pre-frontal cortex–while long-distance connections linking the occipital to the frontal and pre-frontal areas expressed lower values. The same topology was found with connection-wise multifractality in all but delta band connections, where the very opposite pattern appeared. This resulted in a positive correlation between global autocorrelation and connection-wise multifractality in the higher frequency bands, while a strong anticorrelation in the delta band. The proposed analytical tools allow for capturing the fine details of functional connectivity dynamics that are evidently present in DFC, with the presented results implying that multifractality is indeed an inherent property of both global and local DFC.
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Affiliation(s)
| | | | - Peter Mukli
- Department of Physiology, Semmelweis University, Budapest, Hungary
| | - Andras Eke
- Department of Physiology, Semmelweis University, Budapest, Hungary
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Ward RM, Kelty-Stephen DG. Bringing the Nonlinearity of the Movement System to Gestural Theories of Language Use: Multifractal Structure of Spoken English Supports the Compensation for Coarticulation in Human Speech Perception. Front Physiol 2018; 9:1152. [PMID: 30233386 PMCID: PMC6129613 DOI: 10.3389/fphys.2018.01152] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Accepted: 07/31/2018] [Indexed: 01/13/2023] Open
Abstract
Coarticulation is the tendency for speech vocalization and articulation even at the phonemic level to change with context, and compensation for coarticulation (CfC) reflects the striking human ability to perceive phonemic stability despite this variability. A current controversy centers on whether CfC depends on contrast between formants of a speech-signal spectrogram-specifically, contrast between offset formants concluding context stimuli and onset formants opening the target sound-or on speech-sound variability specific to the coordinative movement of speech articulators (e.g., vocal folds, postural muscles, lips, tongues). This manuscript aims to encode that coordinative-movement context in terms of speech-signal multifractal structure and to determine whether speech's multifractal structure might explain the crucial gestural support for any proposed spectral contrast. We asked human participants to categorize individual target stimuli drawn from an 11-step [ga]-to-[da] continuum as either phonemes "GA" or "DA." Three groups each heard a specific-type context stimulus preceding target stimuli: either real-speech [al] or [a], sine-wave tones at the third-formant offset frequency of either [al] or [aɹ], and either simulated-speech contexts [al] or [aɹ]. Here, simulating speech contexts involved randomizing the sequence of relatively homogeneous pitch periods within vowel-sound [a] of each [al] and [aɹ]. Crucially, simulated-speech contexts had the same offset and extremely similar vowel formants as and, to additional naïve participants, sounded identical to real-speech contexts. However, randomization distorted original speech-context multifractality, and effects of spectral contrast following speech only appeared after regression modeling of trial-by-trial "GA" judgments controlled for context-stimulus multifractality. Furthermore, simulated-speech contexts elicited faster responses (like tone contexts do) and weakened known biases in CfC, suggesting that spectral contrast depends on the nonlinear interactions across multiple scales that articulatory gestures express through the speech signal. Traditional mouse-tracking behaviors measured as participants moved their computer-mouse cursor to register their "GA"-or-"DA" decisions with mouse-clicks suggest that listening to speech leads the movement system to resonate with the multifractality of context stimuli. We interpret these results as shedding light on a new multifractal terrain upon which to found a better understanding in which movement systems play an important role in shaping how speech perception makes use of acoustic information.
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Assessment of ECG and respiration recordings from simulated emergency landings of ultra light aircraft. Sci Rep 2018; 8:7232. [PMID: 29740046 PMCID: PMC5940920 DOI: 10.1038/s41598-018-25528-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 04/23/2018] [Indexed: 12/02/2022] Open
Abstract
Pilots of ultra light aircraft have limited training resources, but with the use of low cost simulators it might be possible to train and test some parts of their training on the ground. The purpose of this paper is to examine possibility of stress inducement on a low cost flight simulator. Stress is assessed from electrocardiogram and respiration. Engine failure during flight served as a stress inducement stimuli. For one flight, pilots had access to an emergency navigation system. There were recorded some statistically significant changes in parameters regarding breathing frequency. Although no significant change was observed in ECG parameters, there appears to be an effect on respiration parameters. Physiological signals processed with analysis of variance suggest, that the moment of engine failure and approach for landing affected average breathing frequency. Presence of navigation interface does not appear to have a significant effect on pilots.
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Ma QDY, Ji C, Xie H, Yin K, Ma Z, Bian C. Transitions in physiological coupling between heartbeat and pulse across sleep stages. Physiol Meas 2018; 39:034006. [PMID: 29451501 DOI: 10.1088/1361-6579/aab024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The aim of this study is to investigate the coupling behavior between heartbeat and pulse of blood flow at different sleep stages, and to explore the feasibility of using this coupling strength for automatic sleep staging. APPROACH The electrocardiogram and photoplethysmography signals are recorded during sleep, and R-wave-to-R-wave intervals (RRI) and pulse-to-pulse intervals (PPI) are extracted respectively. The detrended cross-correlation analysis (DCCA) is applied to quantify long-range cross correlations between the RRIs and PPIs across sleep stages. The DCCA scaling exponents are used as the indicator of coupling strength between heartbeat and pulse, and are compared with detrended fluctuation analysis (DFA) scaling exponents of RRIs and PPIs in the application of sleep stage discrimination. MAIN RESULTS We find the DCCA scaling exponents between RRIs and PPIs decrease monotonously from wake, REM sleep to light and deep sleep, indicating that the coupling strength between heartbeat and pulse are reduced gradually when entering deep sleep. Statistical analysis shows that the DCCA scaling exponents possess better discrimination ability between wake/REM sleep and light/deep sleep, compared with DFA scaling exponents of RRIs and PPIs. SIGNIFICANCE Our study reveals the coupling strength between heartbeat and pulse changes regularly across sleep stages, which may help understand the regulation mechanism underlying the cardiovascular system. The DCCA scaling exponents between RRIs and PPIs can be used as an indicator for measuring vigilance level and automatic sleep staging.
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Affiliation(s)
- Qianli D Y Ma
- College of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210003, People's Republic of China. College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, People's Republic of China
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Yoon H, Hwang SH, Choi SH, Choi JW, Lee YJ, Jeong DU, Park KS. Wakefulness evaluation during sleep for healthy subjects and OSA patients using a patch-type device. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 155:127-138. [PMID: 29512493 DOI: 10.1016/j.cmpb.2017.12.010] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 10/30/2017] [Accepted: 12/11/2017] [Indexed: 06/08/2023]
Abstract
OBJECTIVES Obstructive sleep apnea (OSA) is a major sleep disorder that causes insufficient sleep, which is linked with daytime fatigue and accidents. Long-term sleep monitoring can provide meaningful information for patients with OSA to prevent and manage their symptoms. Even though various methods have been proposed to objectively measure sleep in ambulatory environments, less reliable information was provided in comparison with standard polysomnography (PSG). Therefore, this paper proposes an algorithm for distinguishing wakefulness from sleep using a patch-type device, which is applicable for both healthy individuals and patients with OSA. METHODS Electrocardiogram (ECG) and 3-axis accelerometer signals were gathered from the single device. Wakefulness was determined with six parallel methods based on information about movement and autonomic nervous activity. The performance evaluation was conducted with five-fold cross validation using the data from 15 subjects with a low respiratory disturbance index (RDI) and 10 subjects with high RDI. In addition, wakefulness information, including total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO), were extracted from the proposed algorithm and compared with those from PSG. RESULTS According to epoch-by-epoch (30 s) analysis, the performance results of detecting wakefulness were an average Cohen's kappa of 0.60, accuracy of 91.24%, sensitivity of 64.12%, and specificity of 95.73%. Moreover, significant correlations were observed in TST, SE, SOL, and WASO between the proposed algorithm and PSG (p < 0.001). CONCLUSIONS Wakefulness-related information was successfully provided using data from the patch-type device. In addition, the performance results of the proposed algorithm for wakefulness detection were competitive with those from previous studies. Therefore, the proposed system could be an appropriate solution for long-term objective sleep monitoring in both healthy individuals and patients with OSA.
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Affiliation(s)
- Heenam Yoon
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Su Hwan Hwang
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Sang Ho Choi
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, South Korea
| | - Jae-Won Choi
- Department of Neuropsychiatry, Eulji University School of Medicine, Eulji General Hospital, Seoul, South Korea
| | - Yu Jin Lee
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, South Korea
| | - Do-Un Jeong
- Department of Neuropsychiatry and Center for Sleep and Chronobiology, Seoul National University Hospital, Seoul, South Korea
| | - Kwang Suk Park
- Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul, South Korea.
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Qin YH, Zhao ZD, Cai SM, Gao L, Stanley HE. Dual-induced multifractality in online viewing activity. CHAOS (WOODBURY, N.Y.) 2018; 28:013114. [PMID: 29390640 DOI: 10.1063/1.5003100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Although recent studies have found that the long-term correlations relating to the fat-tailed distribution of inter-event times exist in human activity and that these correlations indicate the presence of fractality, the property of fractality and its origin have not been analyzed. We use both detrended fluctuation analysis and multifractal detrended fluctuation analysis to analyze the time series in online viewing activity separating from Movielens and Netflix. We find long-term correlations at both the individual and communal levels and that the extent of correlation at the individual level is determined by the activity level. These long-term correlations also indicate that there is fractality in the pattern of online viewing. We first find a multifractality that results from the combined effect of the fat-tailed distribution of inter-event times (i.e., the times between successive viewing actions of individuals) and the long-term correlations in online viewing activity and verify this finding using three synthesized series. Therefore, it can be concluded that the multifractality in online viewing activity is caused by both the fat-tailed distribution of inter-event times and the long-term correlations and that this enlarges the generic property of human activity to include not just physical space but also cyberspace.
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Affiliation(s)
- Yu-Hao Qin
- Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Zhi-Dan Zhao
- Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Shi-Min Cai
- Web Sciences Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China
| | - Liang Gao
- Institute of Systems Science, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, People's Republic of China
| | - H Eugene Stanley
- Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA
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Lerma C, Echeverría JC, Infante O, Pérez-Grovas H, González-Gómez H. Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations? CHAOS (WOODBURY, N.Y.) 2017; 27:093906. [PMID: 28964157 DOI: 10.1063/1.4999470] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α1) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α1sign) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α1 and α1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α1magn) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α1magn > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α1 and α1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.
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Affiliation(s)
- Claudia Lerma
- Departamento de Instrumentación Electromecánica, Instituto Nacional de Cardiología Ignacio Chávez, Tlalpan, Ciudad de México, Mexico
| | - Juan C Echeverría
- Departamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana Unidad Iztapalapa, Iztapalapa, Ciudad de México, Mexico
| | - Oscar Infante
- Departamento de Instrumentación Electromecánica, Instituto Nacional de Cardiología Ignacio Chávez, Tlalpan, Ciudad de México, Mexico
| | - Héctor Pérez-Grovas
- Departamento de Nefrología, Instituto Nacional de Cardiología Ignacio Chávez, Tlalpan, Ciudad de México, Mexico
| | - Hortensia González-Gómez
- Taller de Biofísica de Sistemas Excitables, Facultad de Ciencias, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, Mexico
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Wiltshire TJ, Euler MJ, McKinney TL, Butner JE. Changes in Dimensionality and Fractal Scaling Suggest Soft-Assembled Dynamics in Human EEG. Front Physiol 2017; 8:633. [PMID: 28919862 PMCID: PMC5585189 DOI: 10.3389/fphys.2017.00633] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 08/14/2017] [Indexed: 01/20/2023] Open
Abstract
Humans are high-dimensional, complex systems consisting of many components that must coordinate in order to perform even the simplest of activities. Many behavioral studies, especially in the movement sciences, have advanced the notion of soft-assembly to describe how systems with many components coordinate to perform specific functions while also exhibiting the potential to re-structure and then perform other functions as task demands change. Consistent with this notion, within cognitive neuroscience it is increasingly accepted that the brain flexibly coordinates the networks needed to cope with changing task demands. However, evaluation of various indices of soft-assembly has so far been absent from neurophysiological research. To begin addressing this gap, we investigated task-related changes in two distinct indices of soft-assembly using the established phenomenon of EEG repetition suppression. In a repetition priming task, we assessed evidence for changes in the correlation dimension and fractal scaling exponents during stimulus-locked event-related potentials, as a function of stimulus onset and familiarity, and relative to spontaneous non-task-related activity. Consistent with predictions derived from soft-assembly, results indicated decreases in dimensionality and increases in fractal scaling exponents from resting to pre-stimulus states and following stimulus onset. However, contrary to predictions, familiarity tended to increase dimensionality estimates. Overall, the findings support the view from soft-assembly that neural dynamics should become increasingly ordered as external task demands increase, and support the broader application of soft-assembly logic in understanding human behavior and electrophysiology.
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Affiliation(s)
- Travis J Wiltshire
- Department of Psychology, University of UtahSalt Lake City, UT, United States.,Department of Language and Communication, Centre for Human Interactivity, University of Southern DenmarkOdense, Denmark
| | - Matthew J Euler
- Department of Psychology, University of UtahSalt Lake City, UT, United States
| | - Ty L McKinney
- Department of Psychology, University of UtahSalt Lake City, UT, United States
| | - Jonathan E Butner
- Department of Psychology, University of UtahSalt Lake City, UT, United States
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Lima GZDS, Corso G, Correa MA, Sommer RL, Ivanov PC, Bohn F. Universal temporal characteristics and vanishing of multifractality in Barkhausen avalanches. Phys Rev E 2017; 96:022159. [PMID: 28950597 DOI: 10.1103/physreve.96.022159] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Indexed: 06/07/2023]
Abstract
Barkhausen effect in ferromagnetic materials provides an excellent area for investigating scaling phenomena found in disordered systems exhibiting crackling noise. The critical dynamics is characterized by random pulses or avalanches with scale-invariant properties, power-law distributions, and universal features. However, the traditional Barkhausen avalanches statistics may not be sufficient to fully characterize the complex temporal correlation of the magnetic domain walls dynamics. Here we focus on the multifractal scenario to quantify the temporal scaling characteristics of Barkhausen avalanches in polycrystalline and amorphous ferromagnetic films with thicknesses from 50 to 1000 nm. We show that the multifractal properties are dependent on film thickness, although they seem to be insensitive to the structural character of the materials. Moreover, we observe for the first time the vanishing of the multifractality in the domain walls dynamics. As the thickness is reduced, the multifractal behavior gives place to a monofractal one over the entire range of time scales. This reorganization in the temporal scaling characteristics of Barkhausen avalanches is understood as a universal restructuring associated to the dimensional crossover, from three- to two-dimensional magnetization dynamics.
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Affiliation(s)
- G Z Dos Santos Lima
- Escola de Ciências e Tecnologia, Universidade Federal do Rio Grande do Norte, 59078-970 Natal, RN, Brazil
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, 59078-970 Natal, RN, Brazil
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - G Corso
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, 59078-970 Natal, RN, Brazil
| | - M A Correa
- Departamento de Física, Universidade Federal do Rio Grande do Norte, 59078-900 Natal, RN, Brazil
| | - R L Sommer
- Centro Brasileiro de Pesquisas Físicas, Rua Dr. Xavier Sigaud 150, Urca, 22290-180 Rio de Janeiro, RJ, Brazil
| | - P Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts 02215, USA
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women Hospital, Boston, Massachusetts 02115, USA
- Institute of Solid State Physics, Bulgarian Academy of Sciences, Sofia 1784, Bulgaria
| | - F Bohn
- Departamento de Física, Universidade Federal do Rio Grande do Norte, 59078-900 Natal, RN, Brazil
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Yoon H, Hwang SH, Choi JW, Lee YJ, Jeong DU, Park KS. Slow-Wave Sleep Estimation for Healthy Subjects and OSA Patients Using R-R Intervals. IEEE J Biomed Health Inform 2017; 22:119-128. [PMID: 28600268 DOI: 10.1109/jbhi.2017.2712861] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We developed an automatic slow-wave sleep (SWS) detection algorithm that can be applied to groups of healthy subjects and patients with obstructive sleep apnea (OSA). This algorithm detected SWS based on autonomic activations derived from the heart rate variations of a single sensor. An autonomic stability, which is an SWS characteristic, was evaluated and quantified using R-R intervals from an electrocardiogram (ECG). The thresholds and the heuristic rule to determine SWS were designed based on the physiological backgrounds for sleep process and distribution across the night. The automatic algorithm was evaluated based on a fivefold cross validation using data from 21 healthy subjects and 24 patients with OSA. An epoch-by-epoch (30 s) analysis showed that the overall Cohen's kappa, accuracy, sensitivity, and specificity of our method were 0.56, 89.97%, 68.71%, and 93.75%, respectively. SWS-related information, including SWS duration (min) and percentage (%), were also calculated. A significant correlation in these parameters was found between automatic and polysomnography scorings. Compared with similar methods, the proposed algorithm convincingly discriminated SWS from non-SWS. The simple method using only R-R intervals has the potential to be utilized in mobile and wearable devices that can easily measure this information. Moreover, when combined with other sleep staging methods, the proposed method is expected to be applicable to long-term sleep monitoring at home and ambulatory environments.
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30
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Multiscale Entropy Analysis of the Differential RR Interval Time Series Signal and Its Application in Detecting Congestive Heart Failure. ENTROPY 2017. [DOI: 10.3390/e19060251] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Cardiovascular systems essentially have multiscale control mechanisms. Multiscale entropy (MSE) analysis permits the dynamic characterization of the cardiovascular time series for both short-term and long-term processes, and thus can be more illuminating. The traditional MSE analysis for heart rate variability (HRV) is performed on the original RR interval time series (named as MSE_RR). In this study, we proposed an MSE analysis for the differential RR interval time series signal, named as MSE_dRR. The motivation of using the differential RR interval time series signal is that this signal has a direct link with the inherent non-linear property of electrical rhythm of the heart. The effectiveness of the MSE_RR and MSE_dRR were tested and compared on the long-term MIT-Boston’s Beth Israel Hospital (MIT-BIH) 54 normal sinus rhythm (NSR) and 29 congestive heart failure (CHF) RR interval recordings, aiming to explore which one is better for distinguishing the CHF patients from the NSR subjects. Four RR interval length for analysis were used ( N = 500 , N = 1000 , N = 2000 and N = 5000 ). The results showed that MSE_RR did not report significant differences between the NSR and CHF groups at several scales for each RR segment length type (Scales 7, 8 and 10 for N = 500 , Scales 3 and 10 for N = 1000 , Scales 2 and 3 for both N = 2000 and N = 5000 ). However, the new MSE_dRR gave significant separation for the two groups for all RR segment length types except N = 500 at Scales 9 and 10. The area under curve (AUC) values from the receiver operating characteristic (ROC) curve were used to further quantify the performances. The mean AUC of the new MSE_dRR from Scales 1–10 are 79.5%, 83.1%, 83.5% and 83.1% for N = 500 , N = 1000 , N = 2000 and N = 5000 , respectively, whereas the mean AUC of MSE_RR are only 68.6%, 69.8%, 69.6% and 67.1%, respectively. The five-fold cross validation support vector machine (SVM) classifier reports the classification Accuracy ( A c c ) of MSE_RR as 73.5%, 75.9% and 74.6% for N = 1000 , N = 2000 and N = 5000 , respectively, while for the new MSE_dRR analysis accuracy was 85.5%, 85.6% and 85.6%. Different biosignal editing methods (direct deletion and interpolation) did not change the analytical results. In summary, this study demonstrated that compared with MSE_RR, MSE_dRR reports better statistical stability and better discrimination ability for the NSR and CHF groups.
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Valenza G, Citi L, Garcia RG, Taylor JN, Toschi N, Barbieri R. Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control. Sci Rep 2017; 7:42779. [PMID: 28218249 PMCID: PMC5316947 DOI: 10.1038/srep42779] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 12/30/2016] [Indexed: 11/23/2022] Open
Abstract
The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson's Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.
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Affiliation(s)
- Gaetano Valenza
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- Department of Information Engineering and Bioengineering and Robotics Research Centre “E. Piaggio”, School of Engineering, University of Pisa, Italy
| | - Luca Citi
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK
| | - Ronald G. Garcia
- Masira Research Institute, School of Medicine, Universidad de Santander, Bucaramanga, Colombia
| | | | - Nicola Toschi
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- University of Rome “Tor Vergata”, Rome, Italy
| | - Riccardo Barbieri
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- Politecnico di Milano, Milan, Italy
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33
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Faes L, Marinazzo D, Stramaglia S, Jurysta F, Porta A, Giandomenico N. Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2016; 374:rsta.2015.0177. [PMID: 27044993 PMCID: PMC4822440 DOI: 10.1098/rsta.2015.0177] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/30/2016] [Indexed: 05/03/2023]
Abstract
This work introduces a framework to study the network formed by the autonomic component of heart rate variability (cardiac processη) and the amplitude of the different electroencephalographic waves (brain processes δ, θ, α, σ, β) during sleep. The framework exploits multivariate linear models to decompose the predictability of any given target process into measures of self-, causal and interaction predictability reflecting respectively the information retained in the process and related to its physiological complexity, the information transferred from the other source processes, and the information modified during the transfer according to redundant or synergistic interaction between the sources. The framework is here applied to theη,δ,θ,α,σ,βtime series measured from the sleep recordings of eight severe sleep apnoea-hypopnoea syndrome (SAHS) patients studied before and after long-term treatment with continuous positive airway pressure (CPAP) therapy, and 14 healthy controls. Results show that the full and self-predictability of η, δ and θ decreased significantly in SAHS compared with controls, and were restored with CPAP forδandθbut not forη The causal predictability of η and δ occurred through significantly redundant source interaction during healthy sleep, which was lost in SAHS and recovered after CPAP. These results indicate that predictability analysis is a viable tool to assess the modifications of complexity and causality of the cerebral and cardiac processes induced by sleep disorders, and to monitor the restoration of the neuroautonomic control of these processes during long-term treatment.
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Affiliation(s)
- Luca Faes
- Biotech, Department of Industrial Engineering, University of Trento, Trento, Italy IRCS Program, PAT-FBK Trento, Italy
| | | | - Sebastiano Stramaglia
- Department of Physics, University of Bari, Bari, Italy INFN Sezione di Bari, Bari, Italy
| | - Fabrice Jurysta
- Sleep Laboratory, Department of Psychiatry, ULB-Erasme Academic Hospital, Brussels, Belgium
| | - Alberto Porta
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | - Nollo Giandomenico
- Biotech, Department of Industrial Engineering, University of Trento, Trento, Italy IRCS Program, PAT-FBK Trento, Italy
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Lin A, Liu KKL, Bartsch RP, Ivanov PC. Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2016; 374:rsta.2015.0182. [PMID: 27044991 PMCID: PMC4822443 DOI: 10.1098/rsta.2015.0182] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/26/2016] [Indexed: 05/03/2023]
Abstract
Within the framework of 'Network Physiology', we ask a fundamental question of how modulations in cardiac dynamics emerge from networked brain-heart interactions. We propose a generalized time-delay approach to identify and quantify dynamical interactions between physiologically relevant brain rhythms and the heart rate. We perform empirical analysis of synchronized continuous EEG and ECG recordings from 34 healthy subjects during night-time sleep. For each pair of brain rhythm and heart interaction, we construct a delay-correlation landscape (DCL) that characterizes how individual brain rhythms are coupled to the heart rate, and how modulations in brain and cardiac dynamics are coordinated in time. We uncover characteristic time delays and an ensemble of specific profiles for the probability distribution of time delays that underly brain-heart interactions. These profiles are consistently observed in all subjects, indicating a universal pattern. Tracking the evolution of DCL across different sleep stages, we find that the ensemble of time-delay profiles changes from one physiologic state to another, indicating a strong association with physiologic state and function. The reported observations provide new insights on neurophysiological regulation of cardiac dynamics, with potential for broad clinical applications. The presented approach allows one to simultaneously capture key elements of dynamic interactions, including characteristic time delays and their time evolution, and can be applied to a range of coupled dynamical systems.
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Affiliation(s)
- Aijing Lin
- Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing 100044, People's Republic of China Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA 02215, USA
| | - Kang K L Liu
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA 02215, USA Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Ronny P Bartsch
- Department of Physics, Bar-Ilan University, Ramat Gan, 5290002, Israel
| | - Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA 02215, USA Division of Sleep Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA Institute of Solid State Physics, Bulgarian Academy of Sciences, Sofia, 1784, Bulgaria
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Soliński M, Gierałtowski J, Żebrowski J. Modeling heart rate variability including the effect of sleep stages. CHAOS (WOODBURY, N.Y.) 2016; 26:023101. [PMID: 26931582 DOI: 10.1063/1.4940762] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
We propose a model for heart rate variability (HRV) of a healthy individual during sleep with the assumption that the heart rate variability is predominantly a random process. Autonomic nervous system activity has different properties during different sleep stages, and this affects many physiological systems including the cardiovascular system. Different properties of HRV can be observed during each particular sleep stage. We believe that taking into account the sleep architecture is crucial for modeling the human nighttime HRV. The stochastic model of HRV introduced by Kantelhardt et al. was used as the initial starting point. We studied the statistical properties of sleep in healthy adults, analyzing 30 polysomnographic recordings, which provided realistic information about sleep architecture. Next, we generated synthetic hypnograms and included them in the modeling of nighttime RR interval series. The results of standard HRV linear analysis and of nonlinear analysis (Shannon entropy, Poincaré plots, and multiscale multifractal analysis) show that-in comparison with real data-the HRV signals obtained from our model have very similar properties, in particular including the multifractal characteristics at different time scales. The model described in this paper is discussed in the context of normal sleep. However, its construction is such that it should allow to model heart rate variability in sleep disorders. This possibility is briefly discussed.
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Affiliation(s)
- Mateusz Soliński
- Faculty of Physics, Warsaw University of Technology, Warsaw 00-662, Poland
| | - Jan Gierałtowski
- Faculty of Physics, Warsaw University of Technology, Warsaw 00-662, Poland
| | - Jan Żebrowski
- Faculty of Physics, Warsaw University of Technology, Warsaw 00-662, Poland
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Bartsch RP, Liu KKL, Bashan A, Ivanov PC. Network Physiology: How Organ Systems Dynamically Interact. PLoS One 2015; 10:e0142143. [PMID: 26555073 PMCID: PMC4640580 DOI: 10.1371/journal.pone.0142143] [Citation(s) in RCA: 213] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 10/19/2015] [Indexed: 11/23/2022] Open
Abstract
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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Affiliation(s)
- Ronny P. Bartsch
- Department of Physics, Bar-Ilan University, Ramat Gan, 52900, Israel
- Department of Physics, Boston University, Boston, MA 02215, United States of America
| | - Kang K. L. Liu
- 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
| | - Amir Bashan
- Harvard Medical School and Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, United States of America
| | - Plamen Ch. Ivanov
- Department of Physics, Boston University, Boston, MA 02215, 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
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Liu KKL, Bartsch RP, Lin A, Mantegna RN, Ivanov PC. Plasticity of brain wave network interactions and evolution across physiologic states. Front Neural Circuits 2015; 9:62. [PMID: 26578891 PMCID: PMC4620446 DOI: 10.3389/fncir.2015.00062] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Accepted: 10/02/2015] [Indexed: 11/13/2022] Open
Abstract
Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of network connectivity and link strength, while at the same time each frequency-specific network is characterized by a different signature pattern of sleep-stage stratification, reflecting a remarkable flexibility in response to change in physiologic state. These new aspects of neural plasticity demonstrate that in addition to dominant brain waves, the network of brain wave interactions is a previously unrecognized hallmark of physiologic state and function.
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Affiliation(s)
- Kang K. L. Liu
- Laboratory for Network Physiology, Department of Physics, Boston UniversityBoston, MA, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical SchoolBoston, MA, USA
| | | | - Aijing Lin
- Laboratory for Network Physiology, Department of Physics, Boston UniversityBoston, MA, USA
- Department of Mathematics, School of Science, Beijing Jiaotong UniversityBeijing, China
| | - Rosario N. Mantegna
- Dipartimento di Fisica e Chimica, Viale delle Scienze, University of PalermoPalermo, Italy
- Center for Network Science and Department of Economics, Central European UniversityBudapest, Hungary
| | - Plamen Ch. Ivanov
- Laboratory for Network Physiology, Department of Physics, Boston UniversityBoston, MA, USA
- Division of Sleep Medicine, Brigham and Women's Hospital, Harvard Medical SchoolBoston, MA, USA
- Institute of Solid State Physics, Bulgarian Academy of SciencesSofia, Bulgaria
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Liu KKL, Bartsch RP, Ma QDY, Ivanov PC. Major component analysis of dynamic networks of physiologic organ interactions. JOURNAL OF PHYSICS. CONFERENCE SERIES 2015; 640:012013. [PMID: 30174717 PMCID: PMC6119077 DOI: 10.1088/1742-6596/640/1/012013] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and non-linear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function.
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Affiliation(s)
- Kang K L Liu
- Department of Physics, Boston University, 590 Commonwealth Ave, Boston, MA 02215, USA
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, USA
| | - Ronny P Bartsch
- Department of Physics, Bar-Ilan University, Ramat-Gan, 52900, Israel
| | - Qianli D Y Ma
- Department of Physics, Boston University, 590 Commonwealth Ave, Boston, MA 02215, USA
- College of Geographical and Biological Information, Nanjing University of Posts and Telecommunications, Nanjing, China
| | - Plamen Ch Ivanov
- Department of Physics, Boston University, 590 Commonwealth Ave, Boston, MA 02215, USA
- Division of Sleep Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
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Makowiec D, Wejer D, Kaczkowska A, Żarczyńska-Buchowiecka M, Struzik ZR. Chronographic Imprint of Age-Induced Alterations in Heart Rate Dynamical Organization. Front Physiol 2015; 6:201. [PMID: 26236241 PMCID: PMC4501288 DOI: 10.3389/fphys.2015.00201] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Accepted: 06/16/2015] [Indexed: 11/20/2022] Open
Abstract
Beat-to-beat changes in the heart period are transformed into a network of increments between subsequent RR-intervals, which enables graphical descriptions of short-term heart period variability. Three types of such descriptions are considered: (1) network graphs arising from a set of vertices and directed edges, (2) contour plots of adjacency matrices A, representing the networks and transition matrices T, resulting from A, and (3) vector plots of gradients of the matrices A and T. Two indices are considered which summarize properties of A and T: the approximate deceleration capacity and the entropy rate. The method, applied to time series of nocturnal RR-intervals recorded from healthy subjects of different ages, reveals important aspect of changes in the autonomic activity caused by biological aging. Independent of the subject’s age, following accelerations, a pendulum-like dynamics appears. With decelerations, this dynamics develops in line with the subject’s age. This aging transition can be graphically visualized by vectors connecting the maxima of the transition probabilities of T, which, metaphorically, resemble a chronometer or the hands of a clock.
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Affiliation(s)
- Danuta Makowiec
- Institute of Theoretical Physics and Astrophysics, University of Gdańsk , Gdańsk , Poland
| | - Dorota Wejer
- Institute of Theoretical Physics and Astrophysics, University of Gdańsk , Gdańsk , Poland
| | - Agnieszka Kaczkowska
- Faculty of Applied Physics and Mathematics, Gdańsk University of Technology , Gdańsk , Poland
| | | | - Zbigniew R Struzik
- Institute of Theoretical Physics and Astrophysics, University of Gdańsk , Gdańsk , Poland ; RIKEN Brain Science Institute , Wako-shi , Japan ; Graduate School of Education, The University of Tokyo , Tokyo , Japan
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Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population. ENTROPY 2015. [DOI: 10.3390/e17031253] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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Li P, Liu C, Li K, Zheng D, Liu C, Hou Y. Assessing the complexity of short-term heartbeat interval series by distribution entropy. Med Biol Eng Comput 2014; 53:77-87. [PMID: 25351477 DOI: 10.1007/s11517-014-1216-0] [Citation(s) in RCA: 105] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2014] [Accepted: 10/20/2014] [Indexed: 10/24/2022]
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Abstract
In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slow-wave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity - a typical 1/f complex pattern - while for large time intervals there is anti-correlation. High correlation of short intervals ( to : waking state and to : SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales ( to : waking state and to : SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anti-correlation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep-wake dynamics could lead to a better understanding of neuroautonomic regulation mechanisms.
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Valenza G, Citi L, Barbieri R. Estimation of instantaneous complex dynamics through Lyapunov exponents: a study on heartbeat dynamics. PLoS One 2014; 9:e105622. [PMID: 25170911 PMCID: PMC4149483 DOI: 10.1371/journal.pone.0105622] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2014] [Accepted: 07/25/2014] [Indexed: 11/21/2022] Open
Abstract
Measures of nonlinearity and complexity, and in particular the study of Lyapunov exponents, have been increasingly used to characterize dynamical properties of a wide range of biological nonlinear systems, including cardiovascular control. In this work, we present a novel methodology able to effectively estimate the Lyapunov spectrum of a series of stochastic events in an instantaneous fashion. The paradigm relies on a novel point-process high-order nonlinear model of the event series dynamics. The long-term information is taken into account by expanding the linear, quadratic, and cubic Wiener-Volterra kernels with the orthonormal Laguerre basis functions. Applications to synthetic data such as the Hénon map and Rössler attractor, as well as two experimental heartbeat interval datasets (i.e., healthy subjects undergoing postural changes and patients with severe cardiac heart failure), focus on estimation and tracking of the Instantaneous Dominant Lyapunov Exponent (IDLE). The novel cardiovascular assessment demonstrates that our method is able to effectively and instantaneously track the nonlinear autonomic control dynamics, allowing for complexity variability estimations.
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Affiliation(s)
- Gaetano Valenza
- Neuroscience Statistics Research Laboratory, Department of Anesthesia, Critical Care & Pain Medicine, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States of America; and Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Research Center E. Piaggio and Department of Information Engineering, University of Pisa, Pisa, Italy
- * E-mail:
| | - Luca Citi
- Neuroscience Statistics Research Laboratory, Department of Anesthesia, Critical Care & Pain Medicine, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States of America; and Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom
| | - Riccardo Barbieri
- Neuroscience Statistics Research Laboratory, Department of Anesthesia, Critical Care & Pain Medicine, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States of America; and Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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A Review of Theoretical Perspectives in Cognitive Science on the Presence of 1/f Scaling in Coordinated Physiological and Cognitive Processes. ACTA ACUST UNITED AC 2014. [DOI: 10.1155/2014/962043] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Time series of human performances present fluctuations around a mean value. These fluctuations are typically considered as insignificant, and attributable to random noise. Over recent decades, it became clear that temporal fluctuations possess interesting properties, however, one of which the property of fractal 1/f scaling. 1/f scaling indicates that a measured process extends over a wide range of timescales, suggesting an assembly over multiple scales simultaneously. This paper reviews neurological, physiological, and cognitive studies that corroborate the claim that 1/f scaling is most clearly present in healthy, well-coordinated activities. Prominent hypotheses about the origins of 1/f scaling are confronted with these reviewed studies. It is concluded that 1/f scaling in living systems appears to reflect their genuine complex nature, rather than constituting a coincidental side-effect. The consequences of fractal dynamics extending from the small spatial and temporal scales (e.g., neurons) to the larger scales of human behavior and cognition, are vast, and impact the way in which relevant research questions may be approached. Rather than focusing on specialized isolable subsystems, using additive linear methodologies, nonlinear dynamics, more elegantly so, imply a complex systems methodology, thereby exploiting, rather than rejecting, mathematical concepts that enable describing large sets of natural phenomena.
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Wuehr M, Pradhan C, Brandt T, Jahn K, Schniepp R. Patterns of optimization in single- and inter-leg gait dynamics. Gait Posture 2014; 39:733-8. [PMID: 24210648 DOI: 10.1016/j.gaitpost.2013.10.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2013] [Revised: 10/08/2013] [Accepted: 10/12/2013] [Indexed: 02/02/2023]
Abstract
INTRODUCTION We examined the influence of walking speed on the fluctuation and synchronization dynamics of stride intervals and ground reaction force (GRF) profiles. Our aim was to identify patterns of optimization in the single-leg and inter-leg dynamics at preferred walking speed (PWS). PWS is thought to bring about the most stable walking pattern in terms of the attractor dynamics of the locomotion system. METHODS Twenty healthy subjects (29.1 ± 1.8 years; 10 women) walked on a treadmill for 5-min periods at their PWS and at 20, 40, 70, and 80% of maximal walking speed. The coefficient of variation (CV) and long-range correlations α of GRF profile and stride time fluctuations as well as the phase synchronization ρ of inter-leg stride timing were analyzed. RESULTS GRF profile α increased with increasing walking speed (p < 0.001). In contrast, stride time CV and α showed a U-shaped speed-dependency with lowest values at PWS (p < 0.05). The speed-dependency of single-leg stride time fluctuations was mirror-inverted in the speed-dependency of inter-leg stride timing ρ; its highest values occurred at PWS (p < 0.001). CONCLUSIONS Fluctuations in GRF profiles become more consistent with increasing walking speed. In contrast, the dynamics of single-leg and inter-leg timing show a collective pattern of optimization at PWS. Less correlated noise in single-leg timing at PWS, imposed on the two coupled oscillating legs, increases the phase synchronization of bilateral timing, thereby enhancing gait stability at the attractor of self-paced walking. Thus, the attractor dynamics of locomotion appear to rely on the interaction of single- and inter-leg timing.
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Affiliation(s)
- Max Wuehr
- German Center for Vertigo and Balance Disorders, University of Munich, Germany.
| | - Cauchy Pradhan
- German Center for Vertigo and Balance Disorders, University of Munich, Germany
| | - Thomas Brandt
- German Center for Vertigo and Balance Disorders, University of Munich, Germany; Institute for Clinical Neurosciences, University of Munich, Germany
| | - Klaus Jahn
- German Center for Vertigo and Balance Disorders, University of Munich, Germany; Department of Neurology, University of Munich, Germany
| | - Roman Schniepp
- German Center for Vertigo and Balance Disorders, University of Munich, Germany; Department of Neurology, University of Munich, Germany
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Zhou J, Manor B, Liu D, Hu K, Zhang J, Fang J. The complexity of standing postural control in older adults: a modified detrended fluctuation analysis based upon the empirical mode decomposition algorithm. PLoS One 2013; 8:e62585. [PMID: 23650518 PMCID: PMC3641070 DOI: 10.1371/journal.pone.0062585] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2012] [Accepted: 03/23/2013] [Indexed: 11/18/2022] Open
Abstract
Human aging into senescence diminishes the capacity of the postural control system to adapt to the stressors of everyday life. Diminished adaptive capacity may be reflected by a loss of the fractal-like, multiscale complexity within the dynamics of standing postural sway (i.e., center-of-pressure, COP). We therefore studied the relationship between COP complexity and adaptive capacity in 22 older and 22 younger healthy adults. COP magnitude dynamics were assessed from raw data during quiet standing with eyes open and closed, and complexity was quantified with a new technique termed empirical mode decomposition embedded detrended fluctuation analysis (EMD-DFA). Adaptive capacity of the postural control system was assessed with the sharpened Romberg test. As compared to traditional DFA, EMD-DFA more accurately identified trends in COP data with intrinsic scales and produced short and long-term scaling exponents (i.e., α(Short), α(Long)) with greater reliability. The fractal-like properties of COP fluctuations were time-scale dependent and highly complex (i.e., α(Short) values were close to one) over relatively short time scales. As compared to younger adults, older adults demonstrated lower short-term COP complexity (i.e., greater α(Short) values) in both visual conditions (p>0.001). Closing the eyes decreased short-term COP complexity, yet this decrease was greater in older compared to younger adults (p<0.001). In older adults, those with higher short-term COP complexity exhibited better adaptive capacity as quantified by Romberg test performance (r(2) = 0.38, p<0.001). These results indicate that an age-related loss of COP complexity of magnitude series may reflect a clinically important reduction in postural control system functionality as a new biomarker.
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Affiliation(s)
- Junhong Zhou
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Brad Manor
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Divisions of Gerontology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Dongdong Liu
- College of Engineering, Peking University, Beijing, China
| | - Kun Hu
- Medical Biodynamics Program, Division of Sleep Medicine, Brigham and Women’s Hospital/Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan
| | - Jue Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- College of Engineering, Peking University, Beijing, China
| | - Jing Fang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- College of Engineering, Peking University, Beijing, China
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Abstract
Integrated physiological systems, such as the cardiac and the respiratory system, exhibit complex dynamics that are further influenced by intrinsic feedback mechanisms controlling their interaction. To probe how the cardiac and the respiratory system adjust their rhythms, despite continuous fluctuations in their dynamics, we study the phase synchronization of heartbeat intervals and respiratory cycles. The nature of this interaction, its physiological and clinical relevance, and its relation to mechanisms of neural control is not well understood. We investigate whether and how cardiorespiratory phase synchronization (CRPS) responds to changes in physiological states and conditions. We find that the degree of CRPS in healthy subjects dramatically changes with sleep-stage transitions and exhibits a pronounced stratification pattern with a 400% increase from rapid eye movement sleep and wake, to light and deep sleep, indicating that sympatho-vagal balance strongly influences CRPS. For elderly subjects, we find that the overall degree of CRPS is reduced by approximately 40%, which has important clinical implications. However, the sleep-stage stratification pattern we uncover in CRPS does not break down with advanced age, and surprisingly, remains stable across subjects. Our results show that the difference in CRPS between sleep stages exceeds the difference between young and elderly, suggesting that sleep regulation has a significantly stronger effect on cardiorespiratory coupling than healthy aging. We demonstrate that CRPS and the traditionally studied respiratory sinus arrhythmia represent different aspects of the cardiorespiratory interaction, and that key physiologic variables, related to regulatory mechanisms of the cardiac and respiratory systems, which influence respiratory sinus arrhythmia, do not affect CRPS.
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Bernaola-Galván P, Oliver J, Hackenberg M, Coronado A, Ivanov P, Carpena P. Segmentation of time series with long-range fractal correlations. THE EUROPEAN PHYSICAL JOURNAL. B 2012; 85:211. [PMID: 23645997 PMCID: PMC3643524 DOI: 10.1140/epjb/e2012-20969-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Segmentation is a standard method of data analysis to identify change-points dividing a nonstationary time series into homogeneous segments. However, for long-range fractal correlated series, most of the segmentation techniques detect spurious change-points which are simply due to the heterogeneities induced by the correlations and not to real nonstationarities. To avoid this oversegmentation, we present a segmentation algorithm which takes as a reference for homogeneity, instead of a random i.i.d. series, a correlated series modeled by a fractional noise with the same degree of correlations as the series to be segmented. We apply our algorithm to artificial series with long-range correlations and show that it systematically detects only the change-points produced by real nonstationarities and not those created by the correlations of the signal. Further, we apply the method to the sequence of the long arm of human chromosome 21, which is known to have long-range fractal correlations. We obtain only three segments that clearly correspond to the three regions of different G + C composition revealed by means of a multi-scale wavelet plot. Similar results have been obtained when segmenting all human chromosome sequences, showing the existence of previously unknown huge compositional superstructures in the human genome.
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Affiliation(s)
| | - J.L. Oliver
- Dpto. de Genética, Inst. de Biotecnología, Universidad de Granada, 18071 Granada, Spain
| | - M. Hackenberg
- Dpto. de Genética, Inst. de Biotecnología, Universidad de Granada, 18071 Granada, Spain
| | - A.V. Coronado
- Dpto. de Física Aplicada II, Universidad de Málaga, 29071 Málaga, Spain
| | - P.Ch. Ivanov
- Harvard Medical School, Division of Sleep Medicine, Brigham & Women’s Hospital, 02115 Boston, MA, USA
- Department of Physics and Center for Polymer Studies, Boston University, 2215 Boston, MA, USA
- Institute of Solid State Physics, Bulgarian Academy of Sciences, 1784 Sofia, Bulgaria
| | - P. Carpena
- Dpto. de Física Aplicada II, Universidad de Málaga, 29071 Málaga, Spain
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Reyes JJ, Peña MA, Echeverría JC, García MT, Ortiz MR, Vargas C, González-Camarena R. Short-term heart rate dynamics of women during labor. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2011:1929-32. [PMID: 22254709 DOI: 10.1109/iembs.2011.6090545] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We studied 10 minutes segments of heartbeat interval fluctuations from 18 young women in labor with normal outcome of pregnancy. Data of each studied case were classified into two distinct groups. One group involving segments where the uterine activity was observable (three or more contractions in ten minutes), and the other group of reference having segments with fewer uterine activity or not presenting contractions at all. For comparison, we also included segments collected during the last trimester of gestation prior to labor from a third group of women. Corresponding RR interval series were analyzed to estimate RR(mean), RMSSD, α(1), α(1(MAG)) and α(1(SIGN)) parameters. No significant differences among groups were identified in RMSSD, α(1) and α(1(MAG)) Nevertheless, α(1(SIGN)) did present significant differences in comparison with the last trimester results (p<0.007), revealing a subtle change in the temporal organization of maternal RR series during labor. Results of these parameters then suggest that during labor, despite preserving a concomitant non-linear influence, the maternal short-term autonomic cardiac regulation behaves with less antagonism.
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Affiliation(s)
- J J Reyes
- Postgraduate Biomedical Engineering Program, Universidad Autónoma Metropolitana-Izt, San Rafael Atlixco #186, CP09340 Mexico City, Mexico.
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Xu Y, Ma QD, Schmitt DT, Bernaola-Galván P, Ivanov PC. Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals. PHYSICA A 2011; 390:4057-4072. [PMID: 25392599 PMCID: PMC4226277 DOI: 10.1016/j.physa.2011.05.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences.
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Affiliation(s)
- Yinlin Xu
- Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
- College of Physics Science and Technology, Nanjing Normal University, Nanjing 210097, China
| | - Qianli D.Y. Ma
- Harvard Medical School and Division of Sleep Medicine, Brigham & Women’s Hospital, Boston, MA 02215, USA
- College of Geography and Biological Information, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
| | - Daniel T. Schmitt
- Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
| | | | - Plamen Ch. Ivanov
- Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA
- Harvard Medical School and Division of Sleep Medicine, Brigham & Women’s Hospital, Boston, MA 02215, USA
- Departamento de Física Aplicada II, Universidad de Málaga, 29071 Málaga, Spain
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