Download full ebook of Heart Rate Variability Gernot Ernst instant download pdf

Heart Rate Variability Gernot Ernst download
https://ebookbell.com/product/heart-rate-variability-gernot-
ernst-43724640
Explore and download more ebooks at ebookbell.com

Here are some recommended products that we believe you will be
interested in. You can click the link to download.
Heart Rate Variability Hrv Signal Analysis Clinical Applications
Markad V Kamath
https://ebookbell.com/product/heart-rate-variability-hrv-signal-
analysis-clinical-applications-markad-v-kamath-4421768
Heart Rate Variability Analysis With The R Package Rhrv Martinez
https://ebookbell.com/product/heart-rate-variability-analysis-with-
the-r-package-rhrv-martinez-6753540
Heart Rate Variability Analysis With The R Package Rhrv 2nd
Constantino Antonio Garca Martnez
https://ebookbell.com/product/heart-rate-variability-analysis-with-
the-r-package-rhrv-2nd-constantino-antonio-garca-martnez-145494654
Poincar Plot Methods For Heart Rate Variability Analysis 1st Edition
Ahsan Habib Khandoker
https://ebookbell.com/product/poincar-plot-methods-for-heart-rate-
variability-analysis-1st-edition-ahsan-habib-khandoker-4325936

Longterm Study Of Heart Rate Variability Responses To Changes In The
Solar And Geomagnetic Environment Abdullah Alabdulgader Rollin Mccraty
Michael Atkinson York Dobyns Alfonsas Vainoras Minvydas Ragulskis
Viktor Stolc
https://ebookbell.com/product/longterm-study-of-heart-rate-
variability-responses-to-changes-in-the-solar-and-geomagnetic-
environment-abdullah-alabdulgader-rollin-mccraty-michael-atkinson-
york-dobyns-alfonsas-vainoras-minvydas-ragulskis-viktor-stolc-12229510
Upgrade Your Vagus Nerve Control Inflammation Boost Immune Response
And Improve Heart Rate Variability With New Sciencebacked Therapies
Boost Mood Improve Sleep And Unlock Stored Energy Navaz Habib
https://ebookbell.com/product/upgrade-your-vagus-nerve-control-
inflammation-boost-immune-response-and-improve-heart-rate-variability-
with-new-sciencebacked-therapies-boost-mood-improve-sleep-and-unlock-
stored-energy-navaz-habib-55417180
Heart Rate And Rhythm Molecular Basis Pharmacological Modulation And
Clinical Implications 1st Edition Onkar Nath Tripathi Auth
https://ebookbell.com/product/heart-rate-and-rhythm-molecular-basis-
pharmacological-modulation-and-clinical-implications-1st-edition-
onkar-nath-tripathi-auth-2225828
Heart Rate Training Roy Benson Declan Connolly
https://ebookbell.com/product/heart-rate-training-roy-benson-declan-
connolly-4730756
Heart Rate Training Customize Your Training Based On Individual Data
And Goals Second Roy Benson Declan Connolly
https://ebookbell.com/product/heart-rate-training-customize-your-
training-based-on-individual-data-and-goals-second-roy-benson-declan-
connolly-11264518

Heart Rate
Variability
Gernot Ernst
123

Gernot Ernst
Heart Rate Variability

ISBN 978-1-4471-4308-6 ISBN 978-1-4471-4309-3 (eBook)
DOI 10.1007/978-1-4471-4309-3
Springer London Heidelberg New York Dordrecht
© Springer-Verlag London 2014
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of
the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,
broadcasting, reproduction on microfilms or in any other physical way, and transmission or information
storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology
now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection
with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and
executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this
publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher's
location, in its current version, and permission for use must always be obtained from Springer.
Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations
are liable to prosecution under the respective Copyright Law.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
While the advice and information in this book are believed to be true and accurate at the date of
publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for
any errors or omissions that may be made. The publisher makes no warranty, express or implied, with
respect to the material contained herein.
Printed on acid-free paper
Springer is part of Springer Science+Business Media (www.springer.com)
Gernot Ernst
Kongsberg Hospital
Kongsberg
Norway

v
Preface
Organisms have rhythms, such as the rhythms of the cardiac and respiratory systems,
endocrinological networks, brain circuits, awake–sleep rhythms, and so on. All
these rhythms have a tendency to oscillate, increasing and decreasing depending on
several factors. Such oscillations can give information on the state of the complex
systems involved. Oscillations have been shown to be an integral part of the cardio-
respiratory circle (Lotric and Stefanovska 2000), peripheral blood flow (Bracic and
Stefanovska 1998a, b), renal functions (Constantinou and Yamaguchi 1981), the
immunological system, cell metabolism (Selkov 1968), the extrapyramidal system
(Brown 2003), and others. Several models have been developed to simulate systems
or subsystems. It has been hypothesized that oscillations in dynamic coupled non-
linear environments serve as communication pathways for biological systems.
Consequently, the uncoupling of oscillating organs would be the cause and not sur-
rogate of organ dysfunction (Godin and Buchman 1996). Recognition of the
dynamic nature of regulatory processes has challenged the traditional view of
homeostasis (Lipsitz 2002), leading to the introduction of the term homeodynamics
(Yates 1993).
During my training as an anesthesiologist at the Humboldt University in Berlin,
Germany, I became acquainted with an older, experienced consultant at the medical
intensive care unit. When he arrived before the morning round, he would simply
check the monitors for changes in the heart rhythm of individual patients over the
previous 24 h. I wondered what he was doing. He explained on one occasion that he
looked at the ups and downs of heart rhythm. If they decreased, he would be con-
cerned about the patient. He did not call this heart rate variability, but it was in fact
exactly the concept I will discuss in this book. In most cases we can summarize it
thus: variation is good and lack of variation is bad. This is probably true for many
body rhythms, but there is already now substantial evidence that this is particularly
true for the heart rhythm.
The cardiorespiratory circle is of special interest in many ways. Respiratory
sinus arrhythmia (RSA) has been described in terms of a weak coupling between
respiration and cardiac rhythms that are usually not phase locked (Lotric and
Stefanovska 2000). The cardiorespiratory system has a high level of complexity

vi
with different forms of self-organization, where oscillations show its complexity in
a simple manifestation (Stefanovska 2002, Stefanovska et al 2002). The complexity
of HRV decreases with increased age (Pikkujämsä et al. 1999; Acharya et al. 2004).
Physiological explanations for HRV have been imbalances in sympathovagal acti-
vation and parasympathetic tone (Hughes 2000), changes in β-adrenergic receptor
number and function, abnormal baroreflex function, central abnormalities of auto-
nomic regulatory function, and, recently, changes in mediator levels (TNF) (Malave
et al. 2003).
Increased interest developed as correlations between decreased heart rate vari-
ability and mortality, specially sudden heart death, was described early in landmark
papers (Kleiger et al. 1987; Singer et al. 1988). Interest in this issue arose specially
after the development of automated internal cardiac defibrillation devices as a thera-
peutic tool, when it became essential to identify risk patients who would benefit
from an implantation. Today, some hospitals use HRV for this (or other purposes),
others not at all. Karemaker concludes “The predictive value of (absence of) heart
rate variations is now an acknowledged risk factor, strongly associated with long-
term outcome of disease in cardiac patients” (Karemaker and Lie 2000, p. 435) and
asks “one wonders why cardiac monitors in our hospitals only represent mean heart
rate predominantly, but do not take heart rate variations into account” (Karemaker
and Lie 2000, p. 436).
In the last years, hypotheses are emerging that discuss nonlinear properties not
only as surrogate of a system but more as a property on its own. A diminished com-
plexity of a system (a patient) is thus not a consequence of aging or disease but on
the contrary, a more ordered system might be the cause of disease. Fractal dynamics
is hence a fundamental feature of living or complex adaptive systems, and their
disappearing is expected to have fatal consequences (Goldberger et al. 2002).
In this book I focus on heart rate variability in various ways. I decided in addition
to discuss some algorithms that have either similar properties or also propose com-
mon mechanisms, such as heart rate turbulence. I discuss extensively the basic
functional structures responsible for the generation of HRV. I summarize evidence
for which structures are involved. In addition we regard it as essential to understand
HRV under a systems biology perspective and present basic principles and mathe-
matical models based on them.
In the clinical part, I am most interested in diseases or conditions for which rele-
vant research has been done, like in the cardiologic field or intensive care. This is of
course also corresponds to my interests. I am intensivist, working together with car-
diologists and have special experience in pain treatment and palliative care. So it is
not only by chance that I focus on different pain syndromes and cancer symptoms.
On the other hand, I am mostly interested in syndromes that are clearly defined. In
some areas, particularly chronic fatigue, often synonymously called myalgic enceph-
alomyelitis, several studies with HRV measures have been published. In difference
to cancer fatigue or fatigue associated with former chemotherapeutic treatment, I
feel that this patient group is still not optimally characterized and HRV research in
heterogeneous groups seems to bring about confusion rather than clarity. This is also
the case for irritable bowel syndrome (IBS), but I chose to discuss it due to some
Preface

vii
evidence leading to the idea of IBS as specific visceral or autonomic neuropathic
pain. I will discuss some of the problematic issues briefly in the last chapter.
It is important for the reader to keep in mind that things changed around 1996. Before
1996 – see also the first chapter on history – no standard for HRV existed. Results were
not completely comparable, some measures were used that later disappeared (e.g., the
so-called middle band in frequency domain), and the technical equipment was rather
heterogeneous. Only after the publication of the report of the Task Force of the European
Society of Cardiology and the North American Society of Pacing and Electrophysiology
(1996) and similar excellent articles (e.g., Berntson et al. 1997), studies started to use
common methods and to report on them exactly. Even though many studies do not use
this standard (even when they claim to do so (Nunan et al. 2010)), it was a great break-
through and diminished somewhat the value of studies conducted previously.
My intention with this book is to introduce an affordable diagnostic measure that
provokes no adverse reactions and is feasible in hospitals and outpatient clinics as
well as for general practitioners or rehabilitation units. At the same time I wish to
make clear possibilities, but also some limitations. HRV is often used rather
mechanically without deeper understanding of the background. I hope that my read-
ers will regard this book as a contribution to their clinical and scientific work.
References
Acharya UR, Kannathal N, Sing OW, Ping LY, Chua T. Heart rate analysis in normal subjects of
various age groups. Biomed Eng Online. 2004;3:24; free at http://www.biomedical-engineer-
ing-online.com.
Berntson GG, Bigger JT Jr, Eckberg DL, Grossman P, Kaufmann PG, Malik M, Nagaraja HN,
Porges SW, Saul JP, Stone PH, van der Molen MW. Heart rate variability: origins, methods, and
interpretive caveats. Psychophysiology. 1997;34:623–48.
Bracic M, Stefanovska A. Wavelet-based analysis of human blood-flow dynamics. Bull Math Biol.
1998a;60:919–35.
Bracic M, Stefanovska A. Nonlinear dynamics of the blood flow studied by lyapunov exponents.
Bull Math Biol. 1998b;60:417–33.
Brown P. Oscillatory nature of human basal ganglia activity: relationship to the pathophysiology
of Parkinson’s disease. Mov Disord. 2003;18:357–63.
Constantinou CE, Yamaguchi O. Multiple-coupled pacemaker system in renal pelvis of the uni-
calyceal kidney. Am J Physiol. 1981;241:R412–8.
Godin PJ, Buchman TG. Uncoupling of biological oscillators: a complimentary hypothesis con-
cerning the pathogenesis of multiple organ dysfunction syndrome. Crit Care Med. 1996;24:
1107–16.
Goldberger AL, Amaral LA, Hausdorff JM, Ivanov PC, Peng CK, Stanley HE. Fractal dynamics in
physiology: alterations with disease and aging. Proc Natl Acad Sci U S A. 2002;99:2466–72.
Hughes JW, Stoney CM. Depressed mood is related to high-frequency heart rate variability during
stressors. Psychosom Med. 2000;62:796–803.
Karemaker JM, Lie KI. Heart rate variability: a telltale of health or disease (editorial). Eur Heart J.
2000;21:435–7.
Kleiger RE, Miller JP, Bigger JT, Moss AJ, Multicenter Postinfarction research group. Decreased
heart rate variability and its association with increased mortality after acute myocardial infarc-
tion. Am J Cardiol. 1987;59:256–62.
Preface

viii
Lipsitz LA. Dynamics of stability: the physiologic basis of functional health and frailty. J Gerontol.
2002;57A:B115–25.
Lotric MB, Stefanovska A. Synchronization and modulation in the human cardiorespiratory sys-
tem. Physica A. 2000;283:451–61.
Malave HA, Taylor AA, Nattama J, Deswal A, Mann DL. Circulating levels of tumor necrosis fac-
tor correlate with indexes of depressed heart rate variability. Chest. 2003;123:716–24.
Nunan D, Sandercock GR, Brodie DA. A quantitative systematic review of normal values for
short-term heart rate variability in healthy adults. Pacing Clin Electrophysiol.
2010;33:1407–17.
Pikkujämsä SM, Mäkikallio TH, Sourander LB, Räihä IJ, Puukka P, Skyttä J, Peng CK, Goldberger
A, Huikuri HV. Cardiac interbeat interval dynamics from childhood to senescence. Circulation.
1999;100:393–9.
Selkov EE. Self oscillations in glycolysis. Eur J Biochem. 1968;4:79–86.
Singer DH, Martin GJ, Magid N, Weiss JS, Schaad JW, Kehoe R, Zheutlin T, Fintel DJ, Hsieh AM,
Lesch M. Low heart rate variability and sudden cardiac death. J Electrocard. 1988;S46–55.
Stefanovska A. Cardiorespiratory interactions. Nonlinear Phenomena Complex Syst.
2002;5:462–9.
Stefanovska A, Bandrivskyv A, McClintock PVE. Cardiovascular dynamics – multiple time
scales, oscillations and noise. In: Third international conference on Unsolved Problems of
Noise and Fluctuation, Washington, DC; 2002.
Task Force of the European Society of Cardiology and the North American Society of Pacing and
Electrophysiology. Heart rate variability. Standards of Measurement, physiological interpreta-
tion and clinical use. Circulation. 1996;93:1043–65.
Yates FE. Selforganizing systems. In: Boyd CA, Noble R, editors. The logic of life – the challenge
of integrative physiology. New York: Oxford University Press; 1993. p. 189–218; cited after
Lipsitz 2002.
Preface

ix
Abbreviations
ACh Acetylcholine
ACTH Adrenocorticotropic hormone
AF Atrial fibrillation
AFR Atrial fibrillation rate
ANS Autonomic nerve system
AP Area postrema
ApEN Approximate entropy
ASDNN Average of the standard deviation of NN intervals
BP Blood pressure
BRS Baroreflex sensitivity
CABG Coronary artery bypass grafting
cAMP Cyclic adenosine monophosphate
CAN Cardiac autonomic neuropathy
CHF Congestive heart failure
CNS Central nervous system
COPD Chronic obstructive pulmonary disease
CRH Corticotropin releasing hormone
CVD Cardiovascular disease
CVRD Cardiac volatility-related dysfunction
DAN Diabetic autonomic neuropathy
DM Diabetes mellitus
DMN Dorsal motor nucleus of the vagus
DN Diabetic neuropathy
DVC Dorsal vagal complex
EPSP Excitatory postsynaptic potentials
FFT Fast Fourier transformation
HD Hemodialysis
Holter monitoring 24 h Holter monitoring
HPA Hypothalamic–pituitary axis
HRT Heart rate turbulence
HRV Heart rate variability

x
ICF Instant center frequency
IPSP Inhibitory postsynaptic potentials
LC Locus coeruleus
LLE Largest Lyapunov exponent
LVEF Left ventricular ejection fraction
MI Myocardial Infarction
MSNA Muscle sympathetic nerve activity
NN50 Number of adjacent NN intervals which differ by at least 50 ms during
a 24-h recording
NPY Neuropeptide Y
NTS Nucleus of the solitary tract
OVLT Organum vasculosum lamina terminalis
PAF Paroxysmal atrial fibrillation
pNN50 Percentage of adjacent NN intervals in a 24-h recording which differ
by at least 50 ms
PTSD Post-traumatic stress disorder
PVH Paraventricular nucleus of the hypothalamus
PVN Paraventricular nucleus
QoL Quality of life
QST Qualitative sensory testing
RMSSD Root mean square of successive differences
RR Relative risk
RVLM Rostral ventrolateral medulla
RVMM Rostral ventromedial medulla
SCD Sudden cardiac death
SDANN Standard deviation of average NN intervals
SDNN Standard deviation of NN intervals
SFO Subfornical organ
SNA Sympathetic nerve activity
SNS Sympathetic nervous system
SPWVT Pseudo-Wigner–Ville transformation
SVES Supraventricular extrasystole
VES Ventricular extrasystole
VF Ventricle fibrillation
VIP Vasoactive intestinal peptide
VMA Vanillylmandelic acid
VT Ventricle tachycardia
WBC White blood cell count
Abbreviations

xi
Contents
Part I Theoretical and Pathophysiological Background
1 History of Heart Rate Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2 Linear, Nonlinear, and Complex Systems. . . . . . . . . . . . . . . . . . . . . . . 9
Linear Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Nonlinear Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Chaos Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Complex Systems Contain Many Constituents Interacting
Nonlinearly. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
The Constituents of a Complex System Are Interdependent. . . . . . . . 19
A Complex System Possesses a Structure Spanning
Several Scales. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
A Complex System Is Capable of Emerging Behavior . . . . . . . . . . . . 20
Complexity Involves Interplay Between Chaos and Non-chaos . . . . . 21
Complexity Involves Interplay Between Cooperation
and Competition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Monitoring, Predicting, and Managing Complex Systems. . . . . . . . . . . . 22
Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Further Readings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3 The Autonomic Nervous System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Anatomical Structures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Supraspinal Autonomic Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Spinal and Peripheral Autonomic Nervous System. . . . . . . . . . . . . . . 30
Transmitter Substances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Basal Sympathetic Tone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

xii
Oscillations in the Sympathetic Nervous System . . . . . . . . . . . . . . . . . . . 38
Vegetative Control of the Heart. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Vegetative Control of Blood Pressure. . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Physiological Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Neural Control of Blood Pressure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Is There Something Like a General Sympathetic or Parasympathetic
Activation? Recent Views on the Interaction Between the Sympathetic
and the Parasympathetic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4 Methodological Issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Technical Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Time-Domain Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Geometric Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Frequency-Domain Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
LF, HF, and LF/HF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
VLF and ULF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Variants of Frequency-Domain Measures . . . . . . . . . . . . . . . . . . . . . . 62
Correlations Between Time Domain and Frequency Domain . . . . . . . 64
Nonlinear Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Entropy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Fractal Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Heart Rate Turbulence (HRT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
Further Methods Combining HRV and Other Measured
Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Modulating and Confounding Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
General Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
Short Term Versus Holter Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . 83
Different Forms of Measurement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Confounding Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Genetic Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Physiological Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Pathophysiological Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Medicaments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Antiarrhythmics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Antihypertensive Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Antidepressive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
Other Psychopharmacological Drugs. . . . . . . . . . . . . . . . . . . . . . . . . . 100
Catecholamines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Anesthesiological Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Other Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Contents

xiii
5 HRV and Alterations in the Vegetative Nervous System. . . . . . . . . . . 119
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Is There an Accordance Between Anatomical Structures Involved
in HRV and Supraspinal Structures Related to ANV? . . . . . . . . . . . . . . . 119
Is There General Increased Autonomic Activity That Might
Correlate with HRV Measures? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
Does HF Correlate with Parasympathetic Tone? . . . . . . . . . . . . . . . . . . . 122
Does LF Correlate with Sympathetic Tone?. . . . . . . . . . . . . . . . . . . . . . . 122
Baroreflex Gain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
6 Pathophysiological and Systems Biology Considerations . . . . . . . . . . 129
General Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Some Physiological Systems with Influence on Heart Rate
Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Sinoatrial Node. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Respiratory System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Endocrinological System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
Immunological System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Glucose Metabolism. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Psychological Functioning, Cardiac Health, and HRV . . . . . . . . . . . . 137
HRV and Complexity: Revisited. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Part II Clinical Studies and Applications
7 General Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
HRV as General Risk Factor in Population Samples . . . . . . . . . . . . . . . . 150
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
8 Cardiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Coronary Heart Disease and Myocardial Infarction . . . . . . . . . . . . . . . . . 158
HRV and General Prognosis After MI . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Angina Pectoris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Chronic Heart Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Pathophysiology and Phenomenology . . . . . . . . . . . . . . . . . . . . . . . . . 164
Heart Failure and HRV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Risk Prediction for Sudden Cardiac Death. . . . . . . . . . . . . . . . . . . . . . . . 172
SCD Summarized. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
SCD in Heart Failure Patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Contents

xiv
Special Subgroups. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Cachexia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Hypertrophic Cardiomyopathy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
HRV Biofeedback Training in Heart Failure Patients. . . . . . . . . . . . . . . . 178
Chronic Heart Failure and Heart Rate Turbulence . . . . . . . . . . . . . . . . . . 178
Other Newer Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
Paroxysmal and Permanent Atrial Fibrillation . . . . . . . . . . . . . . . . . . . . . 179
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Pathophysiology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
HRV Changes Prior to the Onset of Paroxysmal AF . . . . . . . . . . . . . . 180
HRV to Predict the Onset of AF After Thoracic Surgery . . . . . . . . . . 182
HRV to Predict Recurrence After Cardioversion
of Paroxysmal AF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
HRV in Persistent AF: A Challenge. . . . . . . . . . . . . . . . . . . . . . . . . . . 183
Effects of the Maze Procedure on HRV. . . . . . . . . . . . . . . . . . . . . . . . 187
Discussion and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
Hypertension. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
A Short Description of the Pathophysiology of Hypertension. . . . . . . 189
HRV in Normotensive Individuals Developing Hypertension. . . . . . . 192
HRV in Hypertensive Compared to Normotensive Persons. . . . . . . . . 193
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
Other Cardiologic Diseases and Problems . . . . . . . . . . . . . . . . . . . . . . . . 194
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
9 Perioperative Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Induction and Maintenance of General Anesthesia . . . . . . . . . . . . . . . . . 208
Prediction of Hypotension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
Prediction of Cardiac Events . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
Effects of Anesthesia on HRV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Spinal Anesthesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
Maintenance of Anesthesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
Postoperative Course. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
10 Intensive Care and Trauma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Sepsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Pathophysiological Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
Clinical Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
Neonatal Sepsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
Trauma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
Contents

xv
11 Neurologic Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Brain Damage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Neurogenic Cardiomyopathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
Generalized Brain Damage, Impaired Consciousness,
and HRV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
Acute Stroke. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
Poststroke. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
HRV and Stroke Prognosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
12 Pain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Experimental Pain Models and Acute Pain. . . . . . . . . . . . . . . . . . . . . . . . 246
Irritable Bowel Syndrome. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
Back Pain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252
Headaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
Migraine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
Tension-Type Headache. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
Cluster Headache . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
Fibromyalgia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254
The Case of Disability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
13 HRV in Oncology and Palliative Medicine . . . . . . . . . . . . . . . . . . . . . . 261
Cancer Pathophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
Prognosis for Cancer Patients in a Palliative Phase . . . . . . . . . . . . . . . . . 262
Cancer Treatment and HRV: The Case of Anthracyclines . . . . . . . . . . . . 264
Cancer Symptoms and HRV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266
14 Psychiatry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
Depression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
Pathophysiology of Depressive Disorders . . . . . . . . . . . . . . . . . . . . . . 270
Stress Reactions and Immune System . . . . . . . . . . . . . . . . . . . . . . . . . 270
Monoamines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
Glutamate and GABA Receptors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272
Neurotrophic Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272
Depression and Heart Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
Depression and Changes in HRV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
Contents

xvi
Psychosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
Phobias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
Stress-Related Disorders. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
Physiology and Pathophysiology of Stress . . . . . . . . . . . . . . . . . . . . . 280
HRV Changes in Stress-Related Disorders . . . . . . . . . . . . . . . . . . . . . 281
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283
15 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
HRV and Diabetes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291
Role of HRV in Evaluation of Diabetic Patients. . . . . . . . . . . . . . . . . . . . 294
Early Detection of DAN: Desirable or Not Necessary? . . . . . . . . . . . . . . 294
Concluding Remarks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295
16 Other Studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
Chronic Obstructive Pulmonary Disease . . . . . . . . . . . . . . . . . . . . . . . . . 299
Exercise in COPD Patients. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300
Kidney Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301
End-Stage Renal Disease and Dialysis . . . . . . . . . . . . . . . . . . . . . . . . 301
Transplantation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
General Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
Sleep Apnea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
Complementary Medicine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
Acupuncture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
HRV Biofeedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 306
17 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
HRV as Publication-Generating Machine. . . . . . . . . . . . . . . . . . . . . . . . . 313
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317
Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
Contents

Part I
Theoretical and Pathophysiological
Background

3
G. Ernst, Heart Rate Variability,
DOI 10.1007/978-1-4471-4309-3_1, © Springer-Verlag London 2014
The concept of heart rate variability is very old. Already early physicians observed
variation in heart frequency, but only in the last 150 years more specific methods
and ideas appeared. Rather than a comprehensive review, we offer here a sketch of
the history of HRV. We mention names knowing that to relate a complex concept
like HRV to single scientists is entirely wrong. In 1935, Ludwik Fleck was probably
the first to describe scientific progress as collective work, arguing that to relate
results to single scientists is not appropriate (Fleck 2012). We are convinced that his
approach and interpretation could be easily used in the history of HRV. Thus, if we
use specific names, this is not to highlight them at the expense of others who are
similarly important. The authors are rather examples that stand for emerging con-
cepts and discussions, while many more scientists and physicians also deserve
credit. Therefore, we dedicate this chapter to the large historical community of
clear-sighted and curious humans who have developed and are still developing the
concept of heart rate variability in permanent collective interaction.
As Billman (2011) suggests, already early in their history, humans undoubtedly
discovered pulsations at the thoracic wall and in peripheral arteria. The first written
remark about heart rhythm is found in quotations of Herophilus (ca. 335–280 BC),
who not only discovered arteries and veins (and their difference) but also described
the arteries as pulsing rhythmically. As Billman argues, this suggests that Herophilus
was probably the first person to measure heart rate. Herophilus was quoted by Galen
who also quoted Archigenes describing eight different characteristics of the pulse.
Galen of Pergamon focused on pulse and wrote not fewer than 18 books on it and at
least eight treatises describing the use of pulse measurement for prognosis of ill-
nesses (Billman 2011).
Western medical historians most often quote Galen regarding pulse, but pulse
diagnosis was also used early in Indian and Chinese medicine. In China, pulse diag-
nosis was developed (depending on historical sources) between 800 and 200 BC.
Bian Que (㓐烙, about 500 BC, also known as Qin Yueren, 䱵怙ⅉ) is on record as
one of the first Chinese physicians who used and described pulse diagnosis. Bian
Que, who lived about one generation before Hippocrates, was the first to describe
Chapter 1
History of Heart Rate Variability

4
the “four diagnostic methods” of Traditional Chinese Medicine including pulse and
tongue diagnostics (Fig.1.1).
The golden age of physiology started already in the eighteenth century. At this
time, there was no distinction between physiologists and physicists, something that
was reflected in both aims and methods. First observations of the permanent varia-
tion of pulse and arterial blood pressure were presented by Stephen Hales already in
1733. Hales also observed its relation to the respiratory cycle. Heartbeat interval
fluctuations linked to spontaneous respiration were first described by Ludwig in
1847 (Ludwig 1847). This was eventually called respiratory sinus arrhythmia and is
today regarded as part of the broad phenomenon of heart rate variability. He devel-
oped special instruments (“kymograph”) to measure amplitude and frequency of the
pulse wave in dogs. Another early observer of this property was one of the founders
of experimental psychology, Wilhelm Wundt. Already in 1868 Donders described a
respiration dependent activation of N. Vagus and discussed its relation to sinus
arrhythmia. Later on, several studies observed the manipulation of the vagus nerve
(Fig. 1.2).
Claude Bernard (12 July 1813–10 February 1878) was a French physiologist. He
was the first to define the term “milieu intérieur” (now known as homeostasis, a term
coined by Walter Bradford Cannon). His publications include “La fixité du milieu
intérieur est la condition d’une vie libre et indépendante” (“The constancy of the
internal environment is the condition for a free and independent life”). This is still
the basic principle related to homeostasis today. He also argued that “The living
body, though it has need of the surrounding environment, is nevertheless relatively
Fig. 1.1 Bian Que (about
500 BC)
1 History of Heart Rate Variability

5
independent of it. This independence which the organism has of its external environ-
ment derives from the fact that in the living being, the tissues are in fact withdrawn
from direct external influences and are protected by a veritable internal environment
which is constituted, in particular, by the fluids circulating in the body.”
Walter Bradford Cannon (1871–1945) was an American physiologist and profes-
sor and chairman of the Department of Physiology at Harvard Medical School.
Cannon expanded on Claude Bernard’s concept of homeostasis and developed four
propositions around it. Of these, the last two claimed that the regulating system that
determines the homeostatic state consists of a number of cooperating mechanisms
that act simultaneously or successively and that homeostasis does not occur by
chance but is the result of organized self-government. Dittmar proposed a vasomo-
tor center in rostral ventrolateral medulla (Dittmar 1873).
The classical model of autonomic control describes a continuum with parasym-
pathetic activation at one end and sympathetic activation at the other as Cannon
proposed it (Cannon 1915). Langley divided the autonomic outflow to the cardio-
vascular and visceral tissues into sympathetic and parasympathetic components,
based on their spinal origins (Langley 1921). He proposed that parasympathetic
Fig. 1.2 Claude Bernard
(Source: Académie nationale
de medicine)

6
efferents are more precise focused on target organs than sympathetic efferents. It
were beyond others Eppinger and Hess, who focused on abnormalities of the regu-
lations of autonomic functions. They asserted, that “clinical facts, such as respira-
tory arrhythmia, habitual bradycardia, etc. have furnished the means of drawing our
attention to the variations in the tonus of the vagal system in man” (Eppinger and
Hess 1915, p. 12, quoted after Berntson 1997). One report of early physiological
research came from Bainbridge who tried to explain HRV in terms of alterations in
baroreceptor and volume receptor responses associated with respiratoric alterations
of intrathoracic pressure (Bainbridge 1920).
A step further to understand the autonomic nervous system was made by Adrian,
who published the first recordings of sympathetic nervous system (SNS) activity in
anesthetized cats and rabbits (Adrian et al. 1932). In the same period, Malzberg
first described the association between major depression (then called “involution
melancholia”) and cardiac disease (Malzberg 1937), opening up a new area of
research.
After the Second World War, HRV started to be a clinical issue when Hon and
Lee observed in 1965 for the first time HRV fetal ECG. They noted that reduced
beat-to-beat variation of the fetal heart was associated with distress before other
detectable symptoms (Hon and Lee 1965), a principle still in use in every obstetric
unit. In cardiology, Wolf was the first to draw attention to the relationship between
heart rate variability and nervous system status (Wolf 1967), shortly after Valbona
found HRV changes in patients with brain injury in 1965.
Explanations of respiratory sinus arrhythmia were developed when Green and
Heffron described respiration-independent sympathetic rhythms in 1967. Katona
observed the activity of cardiac efferents in anesthetized dogs and its consequences
for hemodynamics in 1970. Shortly afterwards, a landmark study by Jose and
Collison described the intrinsic heart rate after blocking both SNS and PNS with
help of propranolol and atropine (Jose and Collison 1970).
A noninvasive approach to measure cardiac parasympathetic control in the anes-
thetized dog was introduced by Katona and Jih (1975), who suggested that changes
in the magnitude of sinus arrhythmia indicated proportional changes in vagal tone.
At this time, it was based on three assumptions: (a) the change of heart period is a
linear function of vagal efferent activity, (b) during inspiration cardiac vagal effer-
ent activity stops, and (c) the respiratory pattern and rate are constant (which at this
time was guaranteed by the anesthesia used during the test).
Major breakthroughs were made in the 1980s. Axelrod and others started to ana-
lyze the frequency domain of HRV, and in connection to this they started to use
short-term HRV of 10 min or less as well (Axelrod et al. 1987). Of particular impor-
tance was the increasing interest in nonlinear phenomena based on different lines of
research. Especially Goldberger, the later founder of the important website
PhysioNet, became increasingly interested in nonlinear algorithms (e.g., Goldberger
et al. 1984, 1986; Goldberger and West 1987). An overview of his articles reveals
the crucial influences, here he quotes significant European researchers like Hermann
Haken, May’s landmark paper about evolutionary models, and Shaw’s article about
chaos theory and strange attractors.

7
Probably the breakthrough of HRV in cardiology happened when Kleiger dem-
onstrated a possible role of SDNN for predicting mortality after acute myocardial
infarction (Kleiger et al. 1987). This was the starting point for several important
cardiologic studies. Together with Bigger’s introduction of short-term measures
(Bigger et al. 1993), Kleiger’s study sparked a crucial development in the more
recent history of HRV – the joint Task Force of the European Society of Cardiology
and the North American Society of Pacing and Electrophysiology (1996). The Task
Force established minimal technical requirements, definitions, range of Power
bands in frequency domain and recommendations on how to conduct clinical
research and patient examinations with the help of HRV. This paper is probably the
most frequently cited HRV paper. Literally no modern HRV study abstains from
relating to this important standard, and no major revision has been necessary until
today – because of the comprehensive presentation of currently accepted “linear
measures” and because of still insufficiently consistent results with respect to a
plethora of nonlinear algorithms.
Today, HRV is somewhere between. Astonishingly more than 10,000 papers
have been published on it today, it is part of any more expensive pulse watch for
sport enthusiasts, but its clinical use is very varied. We discuss the situation and
future of HRV in the last chapter.
References
Adrian ED, Bronk DW, Phillips G. Discharges in mammalian sympathetic nerves. J Physiol Lond.
1932;74:133–55. As cited in Barman 2000.
Axelrod S, Lishner M, Oz O, Bernheim J, Ravid M. Spectral analysis of fluctuations in heart rate:
an objective evaluation of autonomic nervous control in chronic renal failure. Nephron.
1987;45:202–6.
Bainbridge FA. The relation between respiration and the pulse rate. J Physiol. 1920;54:192–202.
Bigger JT, Fleiss JL, Rolnitzky LM, Steinman RC. The ability of several short time measures of
RR variability to predict mortality after myocardial infarction. Circulation. 1993;88:927–34.
Billman GE. Heart rate variability – a historical perspective. Front Physiol. 2011;2:1–13.
Cannon WB. Bodily changes in pain, hunger, fear, and rage. New York: Appleton; 1915; cited after
[Morrison 2000].
Dittmar C. Über die Lage des sogenannten Gefässcentrums in der Medulla oblongata. Ber Verh
Sachs Akad Wiss Leipzig Math Phys Kl. 1873;25:449–69; quoted by Barman 2000.
Eppinger H, Hess L. Vagotonia: a clinical study in vegetative neurology. New York: The Nervous
and Mental Disease Publishing Company; 1915.
Fleck L. Entstehung und Entwicklung einer wissenschaftlichen Tatsache. Einführung in die Lehre
von Denkstil und Denkkollektiv. Suhrkamp Taschenbuch Wissenschaft Frankfurt a.M. 2012.
Goldberger AL, West BJ. Applications of nonlinear dynamics to clinical cardiology. Ann N Y
Acad Sci. 1987;504:155–212.
Goldberger AL, Findley LJ, Blackburn MR, Mandell AJ. Nonlinear dynamics in heart failure:
implications of long-wavelength cardiopulmonary oscillations. Am Heart J. 1984;107:612–5.
Goldberger AL, Kobalter K, Bhargava V. 1/f scaling in normal neutrophil dynamics: implications
for hematologic monitoring. IEEE Trans Biomed Eng. 1986;33:874–6.
Hon EH, Lee ST. The fetal electrocardiogram. 3. Display techniques. Am J Obstet Gynecol.
1965;91:56–60.
References

8
Jose AD, Collison D. The normal range and determinants of the intrinsic heart rate in man.
Cardiovasc Res. 1970;4:160–7.
Katona PG, Jih F. Respiratory sinus arrhythmia: noninvasive measure of parasympathetic cardiac
control. J Appl Physiol. 1975;39:801–5.
Kleiger RE, Miller JP, Bigger JT, Moss AJ. Multicenter postinfarction research group: decreased
heart rate variability and its association with increased mortality after acute myocardial infarc-
tion. Am J Cardiol. 1987;59:256–62.
Langley JN. The autonomic nervous system, part I. Cambridge: Heffer and Sons; 1921; cited after
[Morrison 2000].
Ludwig C. Beiträge zur Kenntniss des Einflusses der Respirationsbewegungen auf den Blutlauf im
Aortensystem. Arch Anat Physiol Leipzig. 1847;13:242–302; quoted by Hayano 1996.
Malzberg B. Mortality among patients with involution melancholia. Am J Psychiatry.
1937;93:1231–8; quoted after Nemeroff 2012.
Task Force of the European Society of Cardiology and the North American Society of Pacing and
Electrophysiology. Heart rate variability. Standards of measurement, physiological interpreta-
tion and clinical use. Circulation. 1996;93:1043–65.
Wolf S. The end of the rope: the role of the brain in cardiac death. Can Med Assoc J.
1967;97:1022–5.

9
Outline: In this chapter readers will be introduced to basic ideas and definitions of
system theory, nonlinearity, nonlinear deterministic systems, and complexity. It will
include examples and some hints to statistical and geometrical methods. This chap-
ter is not essential for the clinical part of the book, but it is meant to offer a deeper
understanding of the concepts of time series analysis, especially for nonlinear meth-
ods. We therefore recommended reading it.
Linear Systems
A linear system is simply something that can be defined completely by one or more
linear equations. We have summarized some (mathematical) definitions around sys-
tems in Table 2.1. As an example consider a bucket into which water flows. If the
amount of water per time unit is always the same, the amount of water in the bucket
can be described with help of a linear equation. The equation can be solved analyti-
cally. It is possible to calculate the amount of water at any time if you know the
beginning value (the amount of water in the bucket at t=0).
If you describe a system with the help of values taken at different intervals, you
have a time series. Time series consist of a set of data and are necessarily discrete
(not continuous). The linear numerical description of time series data consists of a
first-power mathematical equation. This equation has therefore no exponents and
describes a line in a Cartesian two-dimensional graphical system:
f x = a+bx.
( ) (2.1)
A given amount of input stimulus x produces a proportional corresponding mag-
nitude in output response y. The stimulus produces a response independent of initial
conditions. To describe a linear system, statistics are appropriate, the stimuli being
the independent, and response the dependent variable (Schumacher 2004).
Chapter 2
Linear, Nonlinear, and Complex Systems

10
The Eq. (2.1) is in fact the simplified form of a differential equation. A time
series, however, can also be described by one or more difference equations. A dif-
ference equation describes a system stepwise. It returns value at time step 1, 2, 3,
and so on. You obtain a numerical solution in a difference equation if you start with
an initial value, calculate it according to the equation, reaching so the first result r1.
You put this result again into the equation, obtaining so the next result r2. This pro-
cess can be repeated infinitely and is called iteration.
f x = a+bx .
n+ n
1
( ) (2.2)
Difference equations were important for the discovery of mathematical chaotic
systems, which will be explained later in this chapter.
Linear power spectrum techniques, which transform time series into frequency-
domain data, are considered as linear signal analysis too. All power spectrum analy-
sis techniques (like fast Fourier transformation or autoregressive modelling)
transform a time series data set into its frequency components by decomposing the
original signal into a series of sinusoidal waves analogous to a prism separating
light into its corresponding colors.
Nonlinear Systems
A nonlinear system is mathematically defined as a 2nd- or higher-power system,
that is, the independent variable in the mathematical equation contains an exponent.
In a linear system, the variables produce an output response; whereas, in a nonlinear
system the variables contribute to the output response. Although a linear system can
be decomposed into its component parts, in a nonlinear system the parts interfere,
cooperate, or compete with each other. A small change can alter the nonlinear sys-
tem dramatically because the initial condition of all variables along with the input
stimulus influences the output response (Strogatz 1994). Nonlinear dynamic sys-
tems theory allows for the mathematical reconstruction of an entire system from
one known variable since the reconstructed dynamics are geometrically similar to
the original dynamics.
Table 2.1 Definitions
A system is a collection of variables interacting with each other to accomplish some purpose
(McGillem and Cooper 1974).
A dynamic system is a system that evolves over time by accepting, then operating on, an original
signal to produce a new set of signals (Strogatz 1994).
Signals represent the means by which energy is propagated through a system and may depict any
variable within a system (McGillem and Cooper 1974).
A time series data set is a collection of observations (data points) made sequentially over time
(Chatfield 1989).
2 Linear, Nonlinear, and Complex Systems

11
Probably the simplest form of a nonlinear equation is
f x = x .
( ) 2
(2.3)
If you show a linear system in a graphical form, you see a (straight) line. Any non-
linear system will show a (more or less complicated) curve. A line has always the
same slope at any point, a curve, however, has different slopes, maxima and minima.
These kinds of equations can in principle be solved analytically. We can calcu-
late at any point the value of f(x), but also the slope, global and local maxima and
minima, or the position function. But in most cases, nonlinear systems cannot be
solved analytically. Why are nonlinear systems so much harder to analyze than lin-
ear ones? The essential difference is that linear systems can be broken down into
parts. Then each part can be solved separately and finally recombined to get the
answer (Strogatz 1994). The problem here is that in the real world we do not find
systems where variables act independently. It would be possible to describe the
behavior of the heart rate over time if respiration would not have an effect on pre-
load, blood pressure not on afterload, volume not on heart rate, and so on. In reality,
most systems have parts that interact in one way or another, and this makes it neces-
sary to describe such systems mathematically on a nonlinear way.
Chaos Theory
The misleading expression “chaos theory” describes the properties of nonlinear
deterministic systems. It is a specialized sub-theory of nonlinear systems that
describes the behavior of a system with few variables over time when the variables
of the time step n+1 are dependent on the variables at time step n (compare Eq.
(2.2)). The process of turning the result of one time step into the independent vari-
able of the next time step is called iteration. In contradiction to the associations
related with chaos, a chaotic system is directly dependent on its initial conditions,
but the terminal state of the system after infinite time steps can vary considerably.
With methods and algorithms of chaos theory it is possible to distinguish between
stochasticity (real independent changes without any rule) and chaos (changes
dependent on the conditions before). In fact, most biological time series are based
on a combination of these two elements. The robustness of a chaotic system seems
often to be dependent on stochasticity (also often called “noise”). This means that a
physiological system, which is considerably deterministic, can possibly only be
stable if some real random fluctuations are part of it.
Among many investigators and pioneers who paved the way of modern mathe-
matical chaos theory was the meteorologist E. Lorenz and the ethologist R. May.
Lorenz modelled atmospheric convection in terms of three differential equations
and described their extreme sensitivity to the starting values used for their calcula-
tions. May showed that even simple systems (in this case interacting populations)
Chaos Theory

12
could display very “complicated and disordered” behavior. Among other pioneers
in the field were D. Ruelle and F. Takens. They related the still mysterious turbu-
lence of fluids to chaos and were the first to use the name “strange attractor.” Soon
thereafter M. Feigenbaum revealed patterns in chaotic behavior by showing how the
quadratic map switches from one state to another via period doubling. The term
“chaos” had been already introduced by T.- Y. Li and J. Yorke during their analysis
of the same map. Several Russian mathematicians like A. Kolmogorov and Y.G.
Sinai have also contributed to the characterization of chaos, its relation to probabi-
listic laws, and information theory (Faure and Korn 2001).
There is no simple powerful and comprehensive theory of chaotic phenomena,
but rather a cluster of theoretical models, mathematical tools, and experimental
techniques. Chaos theory is a specialized application of dynamic system theory.
Nonlinear terms in the equations of these systems can involve algebraic or more
complicated functions and variables and these terms may have a physical counter-
part, such as forces of inertia that damp oscillations of a pendulum, viscosity of a
fluid, nonlinear electronic circuits, or the limits of growth of biological populations,
to name a few. Since this nonlinearity renders a closed form of the equations impos-
sible, investigations of chaotic phenomena try to find qualitative and quantitative
accounts of the behavior of nonlinear differentiable dynamical systems. Qualitative
approaches include the use of state spaces or phase spaces to characterize the behav-
ior of systems on the long run, or to describe fractals as pattern of self-similarity.
Phase space is a mathematical and abstract construct with orthogonal coordinate
directions representing each of the variables needed to specify the instantaneous
state of a system, such as velocity and position (of ,e.g., a pendulum) or pressure
and volume changes (e.g., of a lung connected to a respirator). Common for vari-
ables is that they are time dependent. Time itself is not represented as coordinate,
but on the phase space curve itself. Typically, a phase space starts at a certain point
and the system goes through a finite (or infinite) time length. The system might be
end at a certain point, which is often called an attractor or a limit point. A limit point
for instance is the point where a pendulum finally ends. In the absence of friction,
however, the pendulum moves on the same way for infinite time, which leads to a
limit circle that describes a stable oscillation. A normal attractor shows a kind of
equilibrium, either with or without movement of the system. A system can possibly
never reach equilibrium. But beyond attractors or limit cycles, chaotic systems can
also reach a kind of equilibrium without moving on the same track again. This is
described by the term “strange attractor” that is shown by curves in state space that
never repeat but are similar to each other. Limit points are in addition distinguished
with regards to local stability. An attractor is regarded as locally stable when pertur-
bations are damped over time, whereas they are seen as unstable if small perturba-
tions increase over time. Locally unstable attractors are also called repellors. A third
class of equilibrium points is saddle points that are attractors from some regions, but
repellors for other regions.
A physical system can undergo transitions if some of the parameters are dis-
turbed. Perturbations can cause the system to oscillate until it finally returns and
ends at the same end point. Consider a stress response of the body. Systemic-
released adrenaline and synaptically released noradrenaline results in an increased

13
heart rate. The system will eventually adapt, catecholamines will be eliminated, and
(if the stress becomes chronic) receptors will be internalized. At the end, the system
will return to a kind of equilibrium.
The amount of perturbations a system is able to tolerate without coming into
transition to another state correlates with its robustness. Most systems tend to be
robust to most perturbations. The cardiac system can be perturbed in many ways.
The blood volume can be increased or decreased, the concentrations of electrolytes
can change with some consequences for frequency and rhythm patterns, the rhythm
itself can be perturbed by the vegetative nervous system, but in most cases the heart
rhythm as signal returns eventually to its basic values, the system is robust. But
some quite small perturbations can change the system dramatically. This can lead to
a transition to, for instance, atrial fibrillation or asystole. It is typical for systems to
be generally robust but sensitive to some probably small perturbations.
Transitions can be showed in logistic maps. These usually two-dimensional maps
show a final value of a measured or observed parameter after finite (or infinite) itera-
tions (nothing other than the attractor) dependent on a control parameter (the indepen-
dent value). The classical logistic map is derived from the already named population
studies. The logistic equation is a first order difference equation of the form:
x = kx x
n+ n n
1 1−
( ) (2.4)
where x is the dependent value of the system and k is the independent factor. In
population biology, x was a relative value between 0 and 1, where 1 represents the
maximal possible population in an area and 0 extinction. k represents the growth
factor: the higher k is, the faster the population grows. It turns out that for low
values of k, the initial population settles down to a stable size that will reproduce
itself each year. As k increases, the first unstable fix point appears. The successive
value of the population x oscillates in a 2-year circle between two alternate num-
bers. For increasing values of k, a cycle repeats every 4 years, 8 years, and so on.
This is called a period doubling or cascade. Finally, the behavior becomes chaotic;
at this stage wild fluctuations hide very effectively the simplicity of the underlying
rule (Fig. 2.1).
The cardiac cycle represents a deterministic system in which the RR-distance
depends partially on the RR-distances of the last heartbeats. But there are only few
mere deterministic systems. Usually, as stated earlier, systems have both determin-
istic and stochastic elements. Stochastic elements again represent either other com-
plex systems that might be partially deterministic in nature (pseudostochasticity) or
might represent gradually real stochastic systems (consequences of quantum fluc-
tuations). This stochastic element is often called “noise” and is often of high impor-
tance. It has been repeatedly shown that noise is essential for the stability of artificial
and real neural networks. Reducing the “noise” leads to a breakdown of the system,
whereas a certain amount of stochasticity leads to stability and rhythmicity. Noise
in neuronal communication increases the efficacy of the signal recognition.1
1
For a larger discussion, see (Rieke et al. 1999).
Chaos Theory

14
Noise (stochasticity) is differentiated in white, brown, and pink noise. White
noise is a random signal with a flat power spectral density. In other words, the sig-
nal’s power spectral density has equal power in any frequency band, having a given
bandwidth. White noise is considered analogous to white light, which contains all
frequencies. Brown noise,2
also called red noise, is the kind of noise produced by
random Brownian motion. Its spectral density is 1/f2
denoting more energy at lower
frequencies. Pink noise is defined as a signal with a frequency spectrum propor-
tional to the reciprocal of the frequency. It is called pink noise for being intermedi-
ate between white noise and brown noise (Figs. 2.2, 2.3, and 2.4).
2
It is not called after the color but in honor of Robert Brown, the discoverer of Brownian motion.
0
−0.25
0.25
0.5
0.75
1
1.25
1.5
y
0.25 0.5 0.75 1 1.25 1.5 1.75 2 2.25 2.5 2.75 3 3.25 3.5 3.75 4
x
Fig. 2.1 Logistic map of the equation xn+1 =kxn(1−xn) (also called bifurcation diagram)
−20
−30
−40
−50
−60
170
Spectral
density
[dBm]
180 190 200
Frequency [MHz]
210 220 230
Fig. 2.2 White noise

15
An older linear tool for examining time series is Fourier analysis, specifically
FFT (fast Fourier transform). FFT transforms the time domain into a frequency
domain and examines the series for periodicity. The analysis produces a power
−5
−10
−15
−20
−25
−30
−35
−40
100 1,000 10,000
0
Brown noise
Intensity
(dB)
Frequency [Hz]
Fig. 2.3 Brown (red) noise
−5
−10
−15
−20
−25
−30
−35
−40
100 1,000 10,000
0
Pink Noise
Intensity
(dB)
Frequency [Hz]
Fig. 2.4 Pink noise
Chaos Theory

16
spectrum, the degree to which each frequency contributes to the series. If the series
is periodic, then the resulting power spectrum reveals peak power at the driving
frequency. Plotting log power versus log frequency:
• White noise (and many chaotic systems) has zero slope.
• Brown noise has slope equal to −2.
• 1/f (Pink) noise has a slope of −1.
1/f noise is interesting because it is ubiquitous in nature, and it is a sort of tempo-
ral fractal. In the way a fractal has self-similarity in space, 1/f noise has self-
similarity in time. Pink noise is also a major player in the area of complexity.
Several attempts have been made to quantify chaos (this means to describe the
amount of deterministic behavior if there is something that might resemble a strange
attractor). Some of them are based on the assumption that strange attractors fulfill
the condition satisfying the “ergodic” hypothesis, which proposes that trajectories
spend comparable amounts of time visiting the same regions near the attractor.
The Lyapunov exponent is used frequently. It is a measure of exponential diver-
gence of nearby trajectories in the state space. Otherwise stated, it depends on the
difference between a trajectory and the path it would have followed in the absence
of perturbation. Assuming two points x1 and x2 initially separated from each other
by a small distance δ0, and at time t by distance δt, then the Lyapunov exponent λ is
determined by the relation
d d
x t x
»t
= e
( ) ( )
0
(2.5)
where λ is positive if the motion is chaotic and equal to zero if the two trajectories are
separated by a constant amount as, for example, if they are periodic (a limit cycle).
Entropy is a quantity that comes originally from thermodynamics. It describes
the amount of disorder in a given system (this is a rather simplified description. A
probably better verbal approach is to term it as the number of degrees of freedom of
a system). A chaotic system can be considered as a source of information. It makes
prediction uncertain due to the sensitive dependence on initial conditions. Any
imprecision in our knowledge of the state is magnified as time goes by. A measure-
ment made at a later time provides additional information about the initial state.
From a macroscopic point of view, the second law of thermodynamics tells us that
a system tends to evolve toward the set of conditions that has the largest number of
accessible states compatible with the macroscopic conditions. In a phase space, the
entropy of a system can be written as
H = i p i
− p
i
n
=
∑ ( ) ( )
1
log (2.6)
where p is the probability that the system is in state i. In practice one has to divide
the region containing the attractor in n cells and calculate the relative frequency (or
probability p) with which the system visits each cell. Entropy has a special signifi-
cance in time series and we shall revisit the methodology in the Chap. 4. The

17
prototype is the Kolmogorov–Sinai entropy or Shannon entropy. In heart rate varia-
tion approximate entropy and more recently sample entropy are used.
Where Lyapunov exponent and entropy focus on the dynamic of trajectories in
the phase space, dimension emphasizes the geometric features of attractors.
Traditionally, dimension is understood in the classic Cartesian way. A dimension is
a parameter (or measurement) required to define the characteristic of an object. In
mathematics generally, dimensions are the parameters required to describe the posi-
tion and relevant characteristics of any object within a conceptual space – where the
number of dimensions of a space are the total number of different parameters used
for all possible objects considered in the model. An even more abstract perspective
generalizes the idea of dimensions in the terms of scaling laws. The so-called
Hausdorff dimension is an extended nonnegative real number associated to metric
space. To define the Hausdorff dimension for a given space X, we first consider the
number N(r) of circles of radius r which are required to cover X completely. Clearly,
as r gets smaller, N(r) gets larger. Roughly, if N(r) grows the same way as 1/rd
as r
is squeezed down to zero, then we say X has the dimension d. Related methods
include the box-counting dimension, also called Minkowski–Bouligand dimension.
Fractals are irregular geometric objects. An important (defining) property of a
fractal is self-similarity, which refers to an infinite nesting of structure on all scales.
Strict self-similarity refers to a characteristic of a form exhibited when a substruc-
ture resembles a superstructure in the same form. Heart rate on the frequency
domain (see time-domain analysis) is fractal in nature and measures of fractality
have been used to characterize the amount of nonlinearity (see fractal analysis).
Nonlinear statistic tools have been introduced in the last decades. Return maps,
also called Poincaré plots, have been used to distinguish between stochastic systems
or deterministic systems (Clayton 1997). Briefly, return maps plot a point in a
Cartesian system where x is the current value of the time series and y is the next
point of the time series. This is repeated for the next pair of values. Stochastic time
series show a distribution like in Figs. 2.1 and 2.5.
If we look at a time series produced with the already known logistic equation
xn+1 =kxn(1−xn) with a k of 3.99, this time series looks graphically highly stochastic
(Fig. 2.6).
A return map, however, reveals the deterministic properties of this time series
(Fig. 2.7).
Complexity
Complex systems are sometimes positioned between simple systems and stochastic
systems. One approach uses the idea of predictability. A system may be predictable
(we know how it will develop over a certain time range) or may not be predictable
(we know definitely that we don’t know how the system will develop over a certain
time range). Highly predictable and highly unpredictable systems are simple, since
the method of forecasting is so straightforward (Crutchfield 2002). But most inter-
esting systems are between those extremes. Interest in them arose because complex
Complexity

18
systems seem to be sensitive to some small perturbations, but at the same time
complex systems can be quite resistant to other perturbations, which makes them
robust and adaptable (Holt 2004).
There exist several different definitions of complex systems. At the present time,
the notion of complex system is not precisely delineated yet. The idea is somewhat
fuzzy and it differs from author to author. Main approaches include:
• The number of components in the system (the system’s dimension)
• The degree of connectivity between the components
1
0.75
0.5
0.25
0
0 0.25 0.5
x(n)
x(n
+
1)
0.75 1
Fig. 2.5 Return map of a stochastic
time series (From Clayton (1997))
1.0
0.9
0.8
0.7
0.6
0.5
Magnitude
(X
)
0.4
0.3
0.1
0.2
0.0
0 50 100 150
Cycle (n)
200 250 300
Fig. 2.6 Time series of xn+1 =3.99 xn(1−xn) (From Clayton (1997))

19
• The dynamic properties and regularity of the system’s behavior
• The information content and compressibility of data generated by the system
(Holt 2004)
But there is fairly complete agreement that the “ideal” complex systems, those
that we would like most to understand, are the biological ones and especially the
systems having to do with people: our bodies, our groupings, our society, and our
culture. Lacking a precise definition, it is possible to convey the meaning of com-
plexity by enumerating what seem to be the most typical properties. Some of these
properties are shared by many non-biological systems as well.
Complex Systems Contain Many Constituents Interacting
Nonlinearly
Nonlinearity is a necessary condition for complexity, and almost all nonlinear sys-
tems whose phase space has three or more dimensions are chaotic in at least part of
that phase space. This does not mean that all chaotic systems are complex. For one
thing, chaoticity does happen with very few constituents; complexity does not.
The Constituents of a Complex System Are Interdependent
Here is an example of interdependence. Consider first a non-complex system with
many constituents, say a gas in a container. Take away 10 % of its constituents,
which are its molecules. Nothing very dramatic happens. The pressure changes a
little or the volume or the temperature or all of them. But on the whole, the final gas
0.0
0.0
0.2
0.4
0.6
0.8
1.0
0.2 0.4
x(n)
x(n
+
1)
0.6 0.8 1.0
Fig. 2.7 Return map of
xn+1 =3.99 xn(1−xn) (From Clayton
(1997))
Complexity

20
looks and behaves much like the original gas. Now, do the same experiment with a
complex system. Take a human body and take away 10 %, let’s just cut out a leg!
The result will be rather more spectacular than for the gas.
A Complex System Possesses a Structure Spanning Several
Scales
Take the example of the human body again. Scale 1: head, trunk, limbs, and the
macroscopic scale; Scale 2: blood vessels, nerves, and tissue level; Scale 3: cells
and communications between individual cells; Scale 4: intracellular, genome, pro-
teonome, and translational processes; Scale 5: biological chemistry, enzymatic pro-
cesses, and physical chemistry. At every scale we find a structure. Different scales
influence each other. This is an essential and radically new aspect of a complex
system, and it leads to the fourth property.
A Complex System Is Capable of Emerging Behavior
Emergence happens when you switch the focus of attention from one scale to the
coarser scale above it. A certain behavior, observed at a certain scale, is said to be
emergent if it cannot be understood when you study, separately and one by one, every
constituent of this scale, each of which may also be a complex system made up of
finer scales. Thus, the emerging behavior is a new phenomenon special to the scale
considered, and it results from global interactions between the scale’s constituents.
The combination of structure and emergence leads to self-organization, which is
what happens when an emerging behavior has the effect of changing the structure or
creating a new structure. There is a special category of complex systems that was
especially created to accommodate living beings. They are the complex adaptive
systems. As their name indicates, they are capable of changing themselves to adapt
to a changing environment. They can also change the environment to suit themselves.
Among these, even narrower categories are self-reproducing: they know birth,
growth, and death. Needless to say, we know very little that is general about such
systems considered as theoretical abstractions. We know a lot about biology. But we
don’t know much, if anything, about other kinds of life, or life in general.
Let us return now to the relationship between complexity and chaos. They are not
at all the same thing. When you look at an elementary mathematical fractal, it may
seem to you very “complex”, but this is not the same meaning of complex as when
saying “complex systems.” The simple fractal is chaotic; it is not complex. Another
example would be the simple gas mentioned earlier: it is highly chaotic, but it is not
complex in the present sense. We already saw that complexity and chaos have in
common the property of nonlinearity. Since practically every nonlinear system is
chaotic some of the time, this means that complexity implies the presence of chaos.

21
But the reverse is not true. Chaos is a very big subject. There are many technical
papers. Many theorems have been proved. But complexity is much, much bigger. It
contains lots of ideas that have nothing to do with chaos. Chaos is basically pure
mathematics, and by now it is fairly well known. Complexity is still almost totally
unknown. It is not really mathematics, but more like theoretical physics. The field
of chaos is a very small subfield of the field of complexity. Perhaps the most striking
difference between the two is the following. A complex system always has several
scales. While chaos may reign on scale n, the coarser scale above it (scale n−1)
may be self-organizing, which in a sense is the opposite of chaos. Therefore, let us
add a fifth item to the list of the properties of complex systems.
Complexity Involves Interplay Between Chaos and Non-chaos
Many people have suggested that complexity occurs “at the edge of chaos” (Kauffman
2002), but this is not entirely clear. Presumably it means something like the follow-
ing: imagine that the equations of motion contain some “control” parameter that can
be changed depending on the environment (e.g., temperature, concentration, inten-
sity of some external factor like sunlight). We know that most nonlinear systems are
not 100 % chaotic: they are chaotic for some values of the control parameter and not
chaotic for others. Then there is the edge of chaos, i.e., the precise value of the con-
trol for which the nature of the dynamics switches. It is like a critical point in phase
transitions. It is the point where the long-range correlations are most important.
Perhaps complex systems, such as biological systems, manage to modify their envi-
ronment so as to operate as much as possible at this edge of chaos place, which
would also be the place where self-organization is most likely to occur. It makes
sense to expect self-organization to happen when there are strong long-range correla-
tions. Finally, there is one more property of complex systems that concerns all of us
very closely, which makes it especially interesting. Actually, it concerns all social
systems, all collections of organisms subject to the laws of evolution. Examples
could be plant populations, animal populations, other ecological groupings, our own
immune system, and human groups of various sizes such as families, tribes, city
states, social or economic classes, sports teams, Silicon Valley dotcoms, and of
course modern nations and supranational corporations. In order to evolve and stay
alive, in order to remain complex, all of the above need to obey the following rule.
Complexity Involves Interplay Between Cooperation
and Competition
Once again this is interplay between scales. The usual situation is that competition
on scale n is nourished by cooperation on the scale below it (scale n+1). Insect
colonies like ants, bees, or termites provide a spectacular demonstration of this. For
Complexity

22
a sociological example, consider the bourgeois families of the nineteenth century of
the kind described by Jane Austen or Honoré de Balzac. They competed with each
other toward economic success and toward procuring the most desirable spouses for
their young people. And they succeeded better in this if they had the unequivocal
devotion of all their members, and also if all their members had a chance to take part
in the decisions. Then of course there is war between nations and the underlying
patriotism that supports it. Once we understand this competition–cooperation
dichotomy, we are a long way from the old cliché of “the survival of the fittest,”
which has caused so much damage to the popular understanding of evolution
(Baranger).
Monitoring, Predicting, and Managing Complex Systems
The wish to monitor complex systems can have several reasons. The conditions of
complex systems might reflect their robustness or fragility. This can mirror robust-
ness against perturbations from outside the system, but also robustness against
internal oscillations. As described, complex systems can move to a point where a
transition occurs. Several forms of transitions have been described in theoretical
models and also partially observed in real-world systems (Scheffer et al. 2009).
Monitoring complex systems has to be done over time. Changes of surrogate param-
eters might describe that the system approach a possible threshold – a so-called
tipping point – where the systems shifts abruptly from one stage to the next.
It is well known that it is not possible to predict the state of any iterative system
beyond certain iterations. At the same time it is known that any system has a finite
number of states of equilibrium or quasi-equilibrium that it can reach. This is not
necessarily contradictory. The non-predictability of a system regards first the impos-
sibility to predict certain variables. It was originally recognized in meteorology –
that even the best computer using the best model is not able to forecast the weather
more than some days in advance. But on the other hand, rhythmicity leads to pre-
dictability. We know that usually winter is cooler than summer, rain falls in spring-
time even if we are not able to predict exactly a day’s temperature or the days when
it will rain. The predictability in complex systems can mean that the number of
possible states is known, but in the beginning, the attractor the system will be going
toward is not yet known.
Illness interpreted within a complex systems paradigm can be described as a
system being in equilibrium (an attractor state that means health) that is perturbed
by an external or internal event. This perturbation is big enough to cast the system
out of equilibrium. Then eventually it moves back to the same basin of attraction
(equilibrium in health) or to another basin of attraction (chronic illness or death).
The direction of the system (and the velocity of changes) might be more interesting
as the state of the system itself at a certain point of time. A systems dynamic
approach can be to monitor the system and in particular the system changes (using
special variables that represent a system state) and to react fast according to these

23
changes. Part of this theory is that early reactions in beginning changes might
require less measures or even minimal measures in difference to a system which is
already far in the direction of another basin of attraction.
In nonlinear systems, big perturbations might only have small effects, but in the
right moment, a small perturbation may be enough to cause a system change
(Scheffer et al. 2009). If we assume that the latter situation can be defined, it should
be possible either to perturb the system in an adequate manner, pushing it over the
tipping point, or conversely to avoid a transition by using countermeasures when
the system is evolving near transition points. It is important to recognize, however,
that there is not only one kind of transition. In models, critical thresholds for transi-
tions correspond to bifurcations (Kuznetsov 1995). Particularly relevant are cata-
strophic bifurcations that occur after passing a critical threshold when a positive
feedback propels the system through a phase of directional change toward a con-
trasting state (Scheffer et al. 2009). Other classes of bifurcations occur when one
kind of attractor is exchanged with another, e.g., a terminal cycle against a strange
(chaotic) attractor.
With help of models it is possible to identify clues that may be associated with a
system near a transition point. One of the most important clues has been discussed
as a “critical slowing down” phenomenon (Wissel 1984). “Critical slowing down”
has been observed in very distinct phenomena, as in cell-signaling pathways
(Bagowski and Frrell 2001), ecosystems (Scheffer et al. 2009), and climate (Lenton
et al. 2008). Close to the bifurcation points, the exchange rates of the system around
the equilibrium become zero. This implies that as the system approaches such criti-
cal points, it becomes increasingly slow in recovering from small perturbations
(Scheffer et al. 2009). This slowing can begin already far from the tipping point and
increases as the tipping point is approached (Van Nes and Scheffer 2007). In real
systems this phenomenon could be tested by inducing small perturbations that are
not sufficient to drive the system over the transition point and then by measuring the
rates of change. Otherwise it can be possible to observe the effects of usually always
existing natural perturbations on the exchange rates.
Slowing down can lead to an increase in autocorrelation in fluctuation patterns.
This can be shown mathematically (Scheffer et al. 2009). The reason is that in case
of a reduced exchange rate, the system at point b is more and more similar to the
system at one point a in the past, the system has a memory of itself, so to say. This
autocorrelation phenomenon can be measured with help of the frequency spectrum
of the system (Livina and Lenton 2007). Another consequence can be increased
variance – as eigenvalue approaches zero, the impacts of shock do not decay and
their accumulating effects increase the variance of the state variable (Scheffer et al.
2009). Another possibility is to look at the asymmetry of fluctuations (Guttal and
Jayaprakash 2008). This is not necessarily a result of critical slowing down. It has
rather something to with an approaching unstable attractor from one side in the state
space. Also flickering can occur, if the system is near a system shift, being alter-
nately attracted by two basins of attraction. This has been discussed as an alarming
sign before phase transitions, e.g., in models of lake eutrophication (Carpenter and
Brock 2006).
Monitoring, Predicting, and Managing Complex Systems

24
In conclusion, in the last years several interesting approaches to predict system
transitions have been proposed. However, sophisticated ideas to manage complex
systems are either lacking or only theoretical. Regarding complex social systems,
scientists are rather skeptical about managing theories (Willke 1999).
Summary
• Linear systems are only a special condition. Most systems are only linear if they
are simplified. Most biological systems are nonlinear in nature.
• In principle, systems consist of stochastic and deterministic elements. It is pos-
sible, but not always easy to analyze systems in order to quantify the fraction of
determinism. Determinism means simply that the behavior of a system over time
is dependent on its history.
• Nonlinear deterministic (“chaotic”) systems show robustness, which is partially
dependent on stochastic noise. This robustness is with respect to some kinds of
perturbation. On the other hand, nonlinear deterministic systems can be highly
sensitive to certain other perturbations, leading to fast disintegration of the
system
• Complex systems are nonlinear systems, where their parts interact nonlinear and
where there exist different interacting scales. Complex system show emergent
behavior, they can change from a disordered to an ordered state and vice versa.
Further Readings
Many excellent introductions to nonlinear and complex systems have been pub-
lished in the last years. Important ideas and materials of this chapter were obtained
from Strogatz (1994), Clayton (1997), Faure and Korn (2001), Kauffman (2002),
and Baranger.
References
Bagowski CP, Frrell JE. Bistability in the JNK cascade. Curr Biol. 2001;11:1176–82.
Baranger M. Chaos, complexity, and entropy: a physics talk for non-physicists. http://necsi.org/
projects/baranger/cce.pdf.
Carpenter SR, Brock WA. Rising variance: a leading indicator of ecological transition. Ecol Lett.
2006;9:308–15.
Chatfield C. The analysis of time series. London: Chapman and Hall; 1989.
Clayton K. Basic concepts in nonlinear dynamics and chaos. Workshop 1997. In: www.societyfor-
chaostheory.org/chaosprimer.pdf.
Crutchfield JP. What lies between order and chaos. In: Casti J, editor. Art and complexity. Oxford:
Oxford University Press; 2002. p. 31–45.

25
Faure P, Korn H. Is there chaos in the brain? I. Concepts of nonlinear dynamics and methods of
investigation. C R Acad Sci Paris. 2001;324:773–93.
Guttal V, Jayaprakash C. Changing skewness: an early warning signal of regime shifts in ecosys-
tems. Ecol Lett. 2008;11:450–60.
Holt TA, editor. Complexity for clinicians. Oxford: Radcliffe Publishing; 2004.
Kauffman S. Investigations. Oxford: Oxford University Press; 2002.
Kuznetsov YA. Elements of applied bifurcation theory. New York: Springer; 1995.
Lenton TM, Held H, Kriegler E, Hall JW, Lucht W, Rahmstorf S, Schellnhuber HJ. Tipping ele-
ments in the earth’s climate system. Proc Natl Acad Sci U S A. 2008;105:1786–93.
Livina VN, Lenton TM. A modified method for detecting incipient bifurcations in a dynamical
system. Geophys Res Lett. 2007;34, L03712.
McGillem CD, Cooper GR. Continuous and discrete signal and system analysis. Geneva: Holt
McDougal; 1974.
Rieke F, Warland D, van Steveninck R, Bialek W. Spikes – exploring the neural code. Cambridge:
MIT Press; 1999.
Scheffer M, Bascompte J, Brock WA, Brovkin V, Carpenter SR, Dakos V, Held H, van Nes EH,
Rietkerk M, Sugihara G. Early-warning signals for critical transitions. Nature. 2009;461:
S. 53–9.
Schumacher A. Linear and nonlinear approaches to the analysis of R-R interval variability. Biol
Res Nurs. 2004;5:211–21.
Strogatz SH. Nonlinear dynamics and chaos. With applications to physics, biology, chemistry and
engineering. Cambridge: Westview Press; 1994.
Van Nes EH, Scheffer M. Slow recovery from perturbations as a generic indicator of a nearby cata-
strophic shift. Am Nat. 2007;169:738–47.
Willke H. Systemtheorie II: Interventionstheorie. Stuttgart: Lucius und Lucius; 1999.
Wissel C. An universal law of characteristic return time near thresholds. Oecologia. 1984;65:101–7.
References

27
Outline: In this chapter we introduce the autonomic nervous system. Principles and
newer views from neuroscience are presented and discussed. It has a special focus
on effects and interactions of the autonomic nervous system and the cardiovascular
and respiratory systems, which are important for the understanding of the physiol-
ogy and pathophysiology of heart rate variations.
Introduction
The autonomic nervous system (or vegetative nervous system) controls the heart,
smooth muscles, endocrine, and exocrine glands and has an afferent (sensory) and
an efferent part. It is distinct from the somatic nervous system in several ways. The
central control of the vegetative nervous system is allocated in the hypothalamus
but several other brain regions including the amygdala, the prefrontal cortex, and
the association areas of the limbic cortex exert influence on the hypothalamus itself.
The efferent nervous activity of the ANS is largely regulated by autonomic reflexes;
in many of them sensory information is first transmitted to homoeostatic control
centers to be processed there with a specific reaction. The autonomic nervous sys-
tem has its specific transmitter substances and receptors and a particular form of
connections that can be divided in preganglionic and postganglionic fibers.
The main role of the autonomic nervous system is to maintain balance in the
body under varying conditions. The hypothalamus is able to control three different
systems. Apart from the ANS the hypothalamus controls the endocrine system and
an ill-defined neural system concerned with motivation (Saper et al. 2000). The
autonomic system is a visceral sensory and motor system based on reflexes. These
visceral reflexes are (almost) not under voluntary control. It has three major divi-
sions: sympathetic, parasympathetic, and enteral (the latter is often underestimated).
In principle, a real autonomic system (e.g., the enteric system) is sparsely connected
with other parts of the nervous system and is largely self-contained.
Chapter 3
The Autonomic Nervous System

28
In a traditional view, the sympathetic and the parasympathetic systems are
opposed to each other, the former responsible for stress reactions and the latter for
relaxing. Virtually all visceral reflexes are mediated by local circuits in the brain-
stem and spinal cord (Iversen et al. 2000). However, recently this view has been
challenged. We discuss more recent views discussed at the end of this chapter. A
more modern characterization is that the sympathetic nervous system is a “quick
response mobilizing system” and the parasympathetic is a “more slowly activated
dampening system.”
It has been proposed that there exist individual patterns in stress response that are
highly reliable, such as primarily vagal cardiac withdrawal, primarily sympathetic
cardiac activation, or both cardiac withdrawal and sympathetic activation.
Correlations between high-frequency power (often related to the parasympathetic
system) and sympathetic indices did not consistently covary across individuals and
the median correlation was low (Cacioppo 1994). We discuss the proposed relations
between ANS and HRV in particular in Chap. 5.
Anatomical Structures
Supraspinal Autonomic Network
The autonomic nervous system can be divided into sympathetic, parasympathetic,
and enteric parts. In addition it can be divided into a central nervous and a periph-
eral part. The central nervous part is rather a network, a highly interconnected set
of structures in forebrain and brain stem. One of the most important components is
the nucleus of the solitary tract (NTS), which receives extensive sensory inputs
(through, among others, cranial nerves VII, IX, and X and N vagus). The nucleus
itself projects to supraspinal and spinal circuits that control autonomic responses.
Ascending projections from the NTS reach the forebrain sites including hypotha-
lamic nuclei, amygdala, and insular cortex. This includes the carotid sinus reflex,
the gag reflex, the cough reflex, the baroreceptor and chemoreceptor reflexes, sev-
eral respiratory reflexes, the aortic reflex, and reflexes within the gastrointestinal
system regulating secretion and motility. The other important part of the NTS
regards integration of autonomic functions with a wider range of responses like
from the endocrine and behavioral systems. Together with NTS, the hypothalamus
plays a major role here. The projections from MTS to forebrain are partially pro-
cessed in the parabrachial nucleus (important for behavioral responses). This again
has projections to the periaqueductal gray, amygdala, visceral thalamus, hypothal-
amus, and cortex.
Synaptic contacts exist also between the neurons in the NTS and C1 neurons in
the rostral ventrolateral medulla (RVM), which have an important role in the control
of cardiovascular homoeostasis. The RVM neurons in turn project to the locus coe-
ruleus (LC), which is the main source of noradrenergic innervations of higher brain
sites including the hypothalamus and PVN. Projections arise from the RVM and LC
3 The Autonomic Nervous System

29
to sympathetic preganglionic neurons in the spinal cord. There are also descending
pathways from the PVN to the RVM and NTS.
The periaqueductal gray coordinates vegetative reaction (e.g., in stress).
Amygdala and prefrontal cortex regions have an important role in conditioned
behavioral responses but also in the connection between visceral input, output, and
emotional states. A typical clinical conditioning happens in cancer patients who get
nausea already when they see the cancer clinic or cancer nurses. Repeated treat-
ments with emetogene cytostatics lead to an association between the view of the
clinic and nausea, which is partially processed in the amygdala and forwarded to the
hypothalamus and brain stem structures.
The connection between the parabrachial nucleus and thalamus is relayed to the
anterior insular cortex where the internal organs are represented topically. This part
of the visceral sensory cortex interacts with parts of the cingulate cortex (the
infralimbic area), which represents the motoric part of the system and can cause
blood pressure changes or gastric contractions.
The hypothalamus is a small, complex brain region. In case of the ANS, it has an
integrative function by regulating five basic physiological needs:
• Blood pressure and electrolyte composition control by a set of regulatory mecha-
nisms (control of drinking, salt appetite, maintenance of blood osmolality, vaso-
motor tone, and others)
• Regulation of body temperature (control of metabolic increase of temperature,
behavioral)
• Energy metabolism control (regulating eating, digestion, metabolic rate)
• Reproduction control (by hormonal regulation of pregnancy, lactation, and
breastfeeding)
• Control of emergency functions and reactions to stress (muscle blood flow and
tissue blood flow regulation, release of adrenal stress hormones) (Iversen et al.
2000)
The hypothalamus is able to regulate this based on indirect and direct projections
reporting internal states; own internal sensory neurons measuring changes in local
temperature, osmolality, glucose, and sodium; and neurons responsive to circulating
hormones like leptin and angiotensin II through circumventricular organs. Integrated
in hypothalamic circuits are set points. For instance, the hypothalamus acts like a
thermostat. A temperature is set (normally around 37 °C). In case of differences
between the set temperature and the measured temperature, the hypothalamus acti-
vates cooling (e.g., sweating) or heating (e.g., shivering) mechanisms to reach the
set temperature. In case of fever, the set temperature is increased (due to circulating
interleukins, among other factors), which induces the typical shivering reaction in
beginning infections. To accomplish this control function, the hypothalamus con-
tains a complex structure of interlinked nuclei, whose description is beyond the aim
of this chapter.
One of the hypothalamic nuclei receiving input from the NTS is the paraven-
tricular nucleus (PVN). The PVN is associated with the synthesis and release of
corticotropin-releasing hormone (CRH), an important substance in the HPA axis.

30
This ascending link between the NTS and PVN provides a pathway that can modu-
late neurohormonal anti-inflammatory responses. The role of the medial prefrontal
cortex has been emphasized; it has a critical role in the regulation and harmoniza-
tion of behavioral and physiological responses (Thayer 2006).
In a network-like structure like the brain, it is in fact not easy to designate brain
regions that do not influence HRV. In ongoing research it is important to distinguish
between the orders of magnitude of influences. The structures mentioned are major
players, but they are not the only ones: the whole system consists of several inter-
linked subnetworks connected to each other. In fact, this reflects the significance of
HRV as a possible surrogate index of this supraspinal networks (Thayer et al. 2012).
Spinal and Peripheral Autonomic Nervous System
In the somatic motor system the motor neurons are part of the central nervous sys-
tem. They are located in the spinal cord and the brain stem and project directly to
skeletal muscle. In contrast to this, the motor neurons of the sympathetic and para-
sympathetic motor systems are located outside the spinal cord in autonomic gan-
glia. The autonomic motor neurons, also called postganglionic neurons, are
innervated by central neurons (also called preganglionic neurons). Thus, there is
one synapse between the central control and the target tissue. The sympathetic and
parasympathetic system has sensory elements that project to the vegetative centers
in the brain stem. Some branches project also directly to the autonomic ganglia as
part of a local reflex circuit.
Differently from somatic motor neurons, autonomic motor neurons have no spe-
cialized postsynaptic regions, but have their effects through nerve endings with
several swellings (varicosities) where vesicles containing transmitter substances
accumulate. Synaptic transmission occurs thus at multiple sides of the highly
branched axon terminals of autonomic nerves. The neurotransmitter diffuses
through the interstitial fluid to wherever its receptors are located in the tissue.
Control is therefore not exact, goal orientated, but more diffuse. On the other hand,
a few autonomic nerves are able to control large areas of smooth muscle or other
target tissues. This is due to gap junctions that allow the spread of electrical activity
from cell to cell. As a result, the discharge of few autonomic nerve fibers to an effec-
tor tissue might alter the activity of the whole area.
The ANS is composed of two anatomically and functionally different divisions
called the sympathetic and the parasympathetic system (SNS, PNS, respectively).
Their function is at all times tonical that means that it has every time some activity
in form of action potentials, which can increase or decrease. Most though not all
target tissues are innervated by both divisions, often with opposing effects. In gen-
eral, SNS dominates in stress situations, whereas PNS is idle. In addition, the PNS
in particular is involved in basic body functions like digestion and urination.
Sympathetic preganglionic fibers form a column in the intermediolateral horn of the
spinal cord extending from the first thoracic spinal segment to rostral lumbar segments

31
(Iversen et al. 2000). They leave the spinal cord and form synapses in the ganglia of the
sympathetic chains, which lie along each side of the spinal cord. Preganglionic fibers
are thin but myelinated and are relatively slow conducting. Postganglionic fibers in
contrast are not myelinated. There exists a preganglionic/postganglionic fiber ratio of
1:10–1:20. A few preganglionic fibers control many postganglionic fibers by having
synapses with them in often more than one ganglion. Apart from the postganglionic
nerves in the head, postganglionic fibers represent about 9 % of the spinal nerve. The
fibers that innervate the heart, lung, and vessels are probably most relevant for the
physiology of heart rate variability. In addition, the adrenal medulla consists of pregan-
glionic SNS neurons synapsing directly with glandular tissue. The cells of the medulla
do not have endocrinological origin, but came during the embryological development
from neuronal lines. The medulla can so be seen as an aggregation of postganglionic
SNS neurons that send their transmitter substances through the whole body with the
help of blood circulation. A particular feature of SNS is to innervate blood vessels,
primarily arterioles and veins, most of them only receiving SNS, not PNS fibers.
Therefore vascular tone (and sweating) is regulated by SNS only.
Cardiovascular sympathetic efferents can be broadly classified into three groups
according to their dominant characteristic: thermosensitivity, glucosensitivity, and
barosensitivity (Lohmeier 2001). The thermosensitive cardiovascular efferents con-
sist mainly of cutaneous vasoconstrictors, which are activated by hypothermia,
emotional stimuli, and hyperventilation. The glucosensitive group controls adren-
alin release from the adrenal medulla and is activated by hypoglycemia and physi-
cal exercise. The barosensitive group is the largest of the three. Regardless of organ
or tissue being innervated, these neurons show ongoing activity in rest (sympathetic
tone) and they discharge in bursts that are highly synchronized with the arterial
pulse and respiration (Dempsey et al. 2002; Jänig and Habler 2003). Barosensitive
sympathetic efferents control the heart and the kidneys as well as the release of
noradrenalin from a subset of adrenal chromaffin cells. They also constrict resis-
tance arterioles with the exception of those in the skin (Jänig and Habler 2003).
Barosensitive efferents are subject to numerous reflex regulations that operate as
either feedback or feedforward mechanisms. For example, whereas ventilation
(afferents of the lung) and arterial pressure (carotid and aortic receptors) inhibit
activity, muscle receptors during exercise, nociceptors in the heart and skin, or cen-
tral and peripheral chemoreceptors (activated by hypoxia or hypercapnia) increase
the discharge. Barosensitive receptors are usually activated in all organs simultane-
ously, with the exception of the selective inhibition of real sympathetic nerves by
atrial stretch or volume expansion (Figs. 3.1 and 3.2) (Coote 2005).
Barosensitive efferents seem to be regulated mainly by the rostral ventrolateral
medulla (RVLM) and the cutaneous circulation by the rostral ventromedial medulla
(RVMM). The central control of adrenalin secretion is not completely understood.
It is not under baroreceptor control, but well regulated by the RVLM. One group of
adrenaline-producing cells is the C1-cells located in the RVLM. Their discharge is
similar to the barosensitive fibers. In addition, most RVLM cells release glutamate.
Some C1-cells are connected with the hypothalamus, probably involved in sodium
and water balance.

32
The sympathetic baroreflex is a feedback loop. The afferent loop involves mech-
anoreceptors that are activated by distension of the arterial wall. Increase in blood
pressure activates baroreceptors and cause inhibition of cardiac, real, and vasomo-
tor sympathetic efferents, which, in turn, leads to restoration of blood pressure. This
reflex effects in dampening short-term blood pressure fluctuations (Dempsey et al.
2002) and can be modulated in case of need without decreasing reflex sensitivity
that involves both neural and humeral elements (see Fig. 3.3). The mechanisms
include activating C1 neurons in the RVLM by glutamate release induced by, for
example, pain or exercise and simultaneous activation of GABAergic pathways that
inhibit efferent parts of the reflex circuit, blocking partially the baroreceptor reflexes.
Angiotensin II’s effects on vessel endothelium involving production of nitrite oxide
can increase this effect (Fig. 3.3).
In contradiction to the sympathetic part, parasympathetic preganglionic nerves
are located in several brain stem nuclei (beyond others, nucleus ambiguous, the
dorsal vagal nucleus, and the Edinger-Westphal nucleus) and in parts of the sacral
spinal cord. Preganglionic parasympathetic nerves innervating targets in thorax and
abdomen leave the brain stem mainly through the vagal nerve (nerve X). The pre-
ganglionic to postganglionic fiber ratio in the parasympathetic system is 1:3.
Differently than sympathetic ganglia, parasympathetic ganglia are often localized
near their target organs, making axons of the preganglionic neurons often quite long
compared to those of SNS. Terminal ganglia are frequently near their target organs.
Sympathetic
Sympathetic ganglia
Constricts
pupils
Stimulates
salivation
Bronchial
constriction
Stimulates digestion
Stimulates
gallbladder
Contracts
bladder
Relaxes rectum
Vaginal lubrication
erection
Orgasm
ejaculation
Contracts rectum
Relaxes bladder
Stimulates epinephrine and
norepinephrine release
Stimulates glucose
release by liver
Inhibits digestion
Bronchial
dilation
Inhibits
salivation
Dilates pupils
Peripheral vasodilation
Peripheral vasoconstriction
Increases
Increases heart rate
contractility
Decreases
Decreases heart rate
contractility
Parasympathetic
Fig. 3.1 A diagrammatic illustrations of the role of the two arms of the autonomic nervous system
(with permission of the Vinik 2012)

33
Midbrain
Medulla
IC.
IT.
IL.
IS.
Pelcic nerve
Inferior
mesenteric
gang.
Superior
mesenteric
gang.
Caliac
Otic
Submaxillary
Sphenopalatine
Ciliary
III
VII
VII
IX
X
Sup. cere. g.
Eye
Lacrimal gland
Mucous mem.
nose and palate
Submaxillary gland
Sublingual gland
Mucous mem. mouth
Parotid gland
Heart
Larynx
Trachea
Bronchi
Esophagus
Stomach
Bloodves. of abd.
Liver and ducts
Pancreas
Adrenal
Small intestine
Large intestine
Rectum
Kidney
Bladder
Sexual organs
External genitalla
S
m
a
l
l
s
p
l
a
nchnic
Great splanchnic
Fig. 3.2 Classical graphical view of the sympathetic and parasympathetic system (Grays 1918)

34
Several preganglionic neurons exit the CNS through cranial nerves, in particular
nerve III (oculomotorius, innervates the eyes), nerve VII (facial nerve, innervates
the lacrimal gland, the salivary glands, and the mucus membranes of the nasal cav-
ity), nerve IX (pharyngeal nerve, innervates the saliva glands), and, most impor-
tantly, nerve X (vagal nerve, innervates visceral thoracal and most visceral
abdominal organs). The vagal nerve is at the same time the main source for informa-
tion about the internal state of thoracic and abdominal organs. Visceral vagus affer-
ent fibers, residing in the nodose ganglion, terminate primarily within the dorsal
vagal complex (DVC) of the medulla oblongata. The DVC consists of the already
mentioned nucleus tractus solitarius (NTS), the dorsal motor nucleus of the vagus
(DMN), and the area postrema (AP) (Berthoud and Neuhuber 2000). The DMN is
the major origin of preganglionic vagus efferent fibers; cardiovascular vagal effer-
ents originate also within the medullar nucleus ambiguous. The AP, which lacks a
blood–brain barrier, is an important circumventricular organ and the site for humoral
immune-to-brain communication, as described below. The main portion of vagal
sensory input is received by neurons in the NTS that coordinate autonomic function
and interaction with the endocrine system (Iversen et al. 2000).
Ascending and descending vagal connections provide a neuronal substrate for
interaction between HPA axis and SNS as an immunomodulatory mechanism. The
transmission of cytokine signals to the brain through the vagal sensory neurons
depends on the magnitude of the immune challenge. It is likely that the vagal affer-
ent neural pathway plays a dominant role in mild to moderate peripheral inflamma-
tory responses, whereas, acute, robust inflammatory responses signal the brain
primarily via humoral mechanisms (Pavlov et al. 2003). The role of the vagal affer-
ent pathway has been underlined by experimental studies where manipulation of the
pathway resulted in changed system reactions after exposure to endotoxins.
Ang II
NO
Endothelium
RVLM
Blood vessel
1
From. for example.
nociceptors. muscle
metabotropic receptors
and hypothalamus
SPGNs SGNs
Anterioles, kidney,
adrenals, and heart
CVLM
NTS
2
3
GABA
GABA
Baroreceptor
Glu
Glu
Fig. 3.3 Neural and humoral control
of the baroreflex (Guyenet (2006),
with friendly permission of Nature
Publishing Group)

35
Transmitter Substances
The main neurotransmitters of the vegetative nervous system are well known.
Acetylcholine (ACh) and noradrenalin (NA, also called norepinephrine) have been
discovered in relation to research targeted on the ANS. Preganglionic neurons of the
ANS use ACh as neurotransmitter. Postganglionic sympathetic neurons use nor-
adrenalin and postganglionic parasympathetic neurons use ACh. Nerve fibers
releasing ACh are also termed cholinergic fibers. Nerve fibers releasing noradrena-
lin are also termed adrenergic. ACh is rapidly inactivated by acetylcholinesterase
(to its components choline and acetate). Acetylcholinesterase is one of the fastest
enzymes in the body, needing less than 1 ms to remove ACh from the synaptic gap.
Noradrenalin is taken up presynaptically where it is reused or metabolized by
monoamine oxidase (MAO) transforming it to 3-methoxy-4-hydroxymandelic acid
(vanillyl mandelic acid; VMA) that can be found in the urine. By contrast, circulat-
ing noradrenalin and adrenalin are inactivated by catechol-O-methyltransferase
(COMT) in the liver. Catecholamines are often described as metabolized at sites
distant from their sites of synthesis and release after their entry into the extracellular
fluid or even the blood stream. But there is overwhelming evidence suggesting that
most noradrenalin is eliminated in presynaptic cells (Eisenhofer et al. 2004). In a
first step, catecholamines are transformed to 3-methoxy-4-hydroxyphenylglycol.
Most VMA is produced by oxidation of circulating MHPG by alcohol dehydroge-
nase located mainly in the liver.
Not only noradrenaline but probably adrenaline as well plays a role in sympa-
thetic nerves as co-transmitter, being incorporated in postganglionic sympathetic
nerves and released with noradrenaline up to 24 h after its uptake (Majewski et al.
1981; Quinn et al. 1984). Furthermore, infusion of pharmacologic doses of adrena-
line has been shown to promote noradrenergic transmission, probably by stimulat-
ing prejunctional β2 receptors (Majewski et al. 1982). More recent studies showed
evidence for cardiac adrenaline release also in chronic heart failure patients under
baseline conditions possibly released by cardiac sympathetic nerve cells. There has
also evidence for uptake both in heart and kidney neurons (Johansson et al. 1997).
As mentioned above, adrenaline is co-released in the RVLM central barosensitive
pathways together with glutamate. Normally the influence of glutamate is substan-
tially low; in dehydration or abnormal blood gas conditions, however, it makes a
greater contribution (Guyenet 2000; Brooks et al. 2004). Autonomic ganglia also
receive afferent fibers containing neurokinins (SP, CGRP).
Adenosine triphosphate (ATP) is an important co-transmitter together with nor-
adrenaline in many postganglionic sympathetic neurons. By acting on ATP-gated ion
channels (P2 purinergic receptors), they are responsible for some of the fast reactions
of the target tissues (for example smooth muscles). Adenosine is formed by the
hydrolysis of ATP and acts on the P1 purinergic receptor located both pre- and post-
synaptically. It possibly plays an important role in sympathetic transmission.
Adenosine may dampen sympathetic function after intense sympathetic activation by
activating receptors on sympathetic nerve endings that inhibit further noradrenaline
and ATP release. Adenosine has also inhibitory actions in cardiac and smooth muscle
Transmitter Substances

Another Random Document on
Scribd Without Any Related Topics

6292. Both planten most. 6296. Both feyne; F. dire. 6314. Both ins. shal bef. never. 6316.
G. warre; Th. ware. 6317, 8. Words supplied by Kaluza. 6323. Both myght. 6336. I supply
and. 6341. Both and reyned (!) for streyned; see 7366. 6342. I supply y-. 6346. Both I a;
om. a.
6354. G. bete; Th. beate (for lete). 6355. Both Ioly (for blynde); I supply ther. 6356. Th.
habite. 6359. Th. beare; G. were. 6361. G. om. Thus and I; both in to (for in). 6372. Both
omit; supplied as in Morris; F. Si n'en sut mes si receus. 6375. Both I a.; om. a. 6377. G.
shreuen. 6378. Both I (for me); both yeuen. 6386. G. ony. 6388. G. mych. 6392. Both
yeuen. 6393. G. ins. For bef. Penaunce. 6399. Both ought. 6407. Both not; read yit.
6425. G. cheueys; Th. chuse; F. chevir. 6426. Th. hamper. 6432. I supply Ne. 6452. Th.
this is ayenst. 6453. G. heerde. 6454. G. beeste. 6460. Both it is; F. Porquoi. 6462, 7. G.
fat. 6465. G. grucche; Th. grutche. 6466. Both woth (!). 6469. I supply the. 6470. G. Yhe.
6481. Both seruest; F. sembles. 6482. Both I am but an. 6484. G. Yhe. 6487. Both good.
6491. Both bettir; G. that queyntaunce. 6492. Th. tymes; G. tyme. 6493. Both of a pore.
6496. G. myxnes; Th. myxins. 6500. Both me a dyne. 6513. G. ony. 6515. Both not. 6516.
Both swere. 6522. Both Hath a soule.
6531. Th. of; G. to. 6532. G. thrittene; Th. thirtene; read thrittethe. 6536. G. myche.
6539. Both beggith (-eth). 6542. Both goddis (-es). 6543. G. Salamon; Th. Salomon.
6546. G. yhe. 6550. Both nolden. 6551. G. was. 6557. Both myght. 6565. G. ther; Th.
their. 6569. Both yaf. 6570. Both folkis (-es). 6572. Both they; read leye; F. Ains gisoient.
6581. Perhaps om. That.
6598. Both tolde (against grammar). 6600. G. desily (!). 6601. Th. To; G. Go. 6606. Both
Ben somtyme in; see 6610. 6616. G. old; Th. olde. 6650. Both myght. 6653. I supply
wher; F. la ou. 6655. Both yeue.
6667. Both haue bidde; (om. haue). 6679. Both good. 6682. Th. -of; G. -fore. 6684. Both
wryne. 6688. G. omits: Th. hondis. 6699. Th. -wayes; G. -weys. 6700. If] Both Yit. 6707.
Both mendiciens (-ence); see 6657.
6721. Both without. 6728. Th. noriture; G. norture. 6737. Both had. 6748. G. Ony. 6756.
Both clothe; read clothes; see 6684. 6759. Both this. 6766. Both solemply. 6782. Th.
This; G. The. 6784. Th. agylte; G. agilt. 6786. So Th.; G. Of thyngis that he beste myghte
(in late hand).
6792. G. wille. 6797. Both this that; om. that. 6803. Both yeuen. 6806. G. sene. 6808, 10.
Supply ne, hir. 6819. Both wrine. Both hem, at. 6820. Both Without. 6823, 4. Both
robbyng, gilyng. 6827. G. fast. 6828. Both high. 6834. G. gret; Th. great. 6841. Both
Without. 6844. Both boldly. 6850. Both emperours. 6851. G. om. and.
6860, 6901. Supply thise, be. 6862. G. gret; Th. great. 6880. Th. Ne wol; G. Wol; read
Nil. 6890. Both doutles (-lees). 6902, 7, 11. Both burdons.
6925, 6. Both him; read hem. 6936. Both good. 6939. Th. wete. 6949. G. Yhe. 6952. Th.
parceners; G. perseners. 6974. Both tymes a; om. a.

6997. G. gret; Th. great. 7002. Th. al; G. om. 7012. After this line, both in Th. and G.,
come ll. 7109-7158. 7018. G. werrien; Th. werryen. 7019. Both al. 7022. Th. bougerons;
G. begger. 7029. Both these that; F. lerres ou. 7035. G. ony. 7037. we] G. me. 7038. hem]
Both them. 7041. G. cheffis; Th. cheffes; F. fromages. 7047. he] G. we. 7048. Both bake.
7056. Both his; read our. 7059. G. sleght; Th. sleight. 7060. G. hight; Th. heyght. 7063.
Both vounde. 7070. Both good. 7071. G. sleghtes. I supply as. 7075. G. om. he have.
7092. Th. We had ben turmented al and 7093. I supply fals. 7104. Both brent. 7109. G.
has here l. 7110, followed by a blank line; Th. has That they [read he] ne might 7110.
Th. To the copye, if hem talent toke; after which, Of the Euangelystes booke (spurious).
7113. G. gret; Th. great. 7119, 21. G. ony. 7123. G. many a such. 7125. Th. booke; G.
book. 7127. Perhaps omit that. 7133, 37, 42. G. om. for, it, they. 7143. Th. Awaye; G.
Alwey. 7144. G. durst. 7145. Both no. 7148. Th. booke; G. book. 7151. Supply boke.
7159. Both vpon. Before this line G. and Th. wrongly insert ll. 7013-7110, 7209-7304.
7164. Th. booke; G. book. 7165. G. mych. 7166. I supply that.
7173, 4. Supplied by conjecture; F. Par Pierre voil le Pape entendre. 7175, 99. I supply
eek, men. 7178. G. Ayens; Th. Ayenst. 7180. And] Both That. that] Both to. 7189. G.
orribilite; Th. horriblete. 7190. Th. booke; G. book. 7196. G. Petre. 7200. G. Petres. 7205.
G. thilk. 7209. See note to l. 7159. 7217. Th. Empresse; G. Emperis. 7221. Both worthy;
see 7104. Both mynystres. 7234. G. iye.
7236. Th. recketh; G. rekke. 7243. Both may us (om. may). 7244. G. om. hem. 7254. Th.
hem; G. hym; supply it. 7255. Th. hem; G. hym. 7257. G. steight (!). 7258. Th. graye; G.
grey. 7260. G. high. 7262. Th. ryuelyng; G. reuelyng. 7263. G. dyuyse. 7272. The] G. To.
7292. Both shulde.
7303. G. forwordis. 7304. G. Yhe. Th. hence; G. hens. 7307. Th. ayenst; G. ayens. 7316.
Both slayn; see note. 7317. G. alto defyle. 7325. G. Myn; Th. My. G. streyneth (!). 7331.
Both Without. 7336. Th. Thankyng. 7355. G. countynaunce. 7358. G. heelde. 7362. Th.
laste; G. last.
7368. G. gracche; Th. gratche. G. bygynne; Th. bygyne. 7371. Th. psaltere; G. sawter.
7380. G. ony. 7385-7576. From Th.; lost in G. 7386. Th. made. 7389. Th. shappe;
denysed. 7394. tho] Th. to. 7409. Had] Th. And. 7429. Th. humbly. 7432. Th. remeued.
7435. Th. thought. 7444. I supply as. 7458. Th. Frere. 7460. Supply that. 7463. Th. al.
7464. Th. greet. 7471, 72. Th. sopheme, enueneme; F. sophime, envenime. 7473. Th.
hath hadde the. 7488. Th. doughty (!); F. poudreus; read dusty. 7494. Th. herborowe.
7504. Th. sir. 7513. Th. styll. 7532. Th. styl. 7533. Th. she nat herselfe. 7546. Th. sothe.
7548, 50. I supply for, wel. 7553. Th. thought harme. 7560. Th. her.
7568. Th. Without. 7577. G. begins again. 7582. Th. herbered; G. herberd. 7585. Both
herbegere. 7590. Both sothe. Th. sawe; G. saugh. 7600. Both where. G. ony. 7625. I
supply he. 7626. G. saloweth.

7628. Th. comynge. 7630. Supply that. 7637. G. I nerer (!). 7653. G. wole; Th. wol: read
wolde. 7662. doth] F. fait; both wot. 7663. Th. we (for ye); G. om. 7666. Both giltles.
7678. Both repent. 7686. Th. tymes; G. tyme.
7693. So Th. (but with for to for to); G. To reden in diuinite. 7694. G. And longe haue red
(wrongly); here G. abruptly ends. 7694-8. From Th. 7697. Th. abode. Colophon. G.
Explicit, following And longe haue red (see note to 7694); Th. Finis. Here endeth the
Romaunt of the Rose.
THE MINOR POEMS.
I. AN A. B. C.
Incipit carmen secundum ordinem literarum Alphabeti.
hty and al merciable quene,
om that al this world fleeth for socour,
ve relees of sinne, sorwe and tene,
us virgine, of alle floures flour,
5
ee I flee, confounded in erreur!
and releve, thou mighty debonaire,
mercy on my perilous langour!
uisshed me hath my cruel adversaire.
A toy du monde le refui,
Vierge glorieuse, m'en fui
Tout confus, ne puis miex faire;
A toy me tíen, a toy m'apuy.
Relieve moy, abatu suy:
Vaincu m'a mon aversaire.
Puis qu'en toy ont tous repaire
Bien me doy vers toy retraire
Avant que j'aie plus d'annuy.
10
N'est pas luite necessaire
A moy, se tu, debonnayre,
Ne me sequeurs comme a autrui.
tee so fix hath in thyn herte his tente,
10
wel I wot thou wolt my socour be,
canst not warne him that, with good entente,
thyn help. Thyn herte is ay so free,
art largesse of pleyn felicitee,
n of refut, of quiete and of reste.
15
ow that theves seven chasen me!
lady bright, er that my ship to-breste!
Bien voy que par toy confortés
Sera mes cuers desconfortés,
Quer tu es de salu porte.
Se je me suis mal tresportez
Par .vij. larrons, pechiés mortez,
Et erre par voie torte,
Esperance me conforte
20
Qui à toy hui me raporte
A ce que soie deportez.
Ma povre arme je t'aporte:
Sauve la: ne vaut que morte;
En li sont tous biens avortez.
Contre moy font une accion

ort is noon, but in yow, lady dere,
, my sinne and my confusioun,
oughten not in thy presence appere,
20
ake on me a grevous accioun
rrey right and desperacioun;
as by right, they mighten wel sustene
were worthy my dampnacioun,
mercy of you, blisful hevene quene.
25
e is ther noon, thou queen of misericorde,
hou nart cause of grace and mercy here;
ouched sauf thurgh thee with us tacorde.
ertes, Cristes blisful moder dere,
Ma vergoigne et confusion,
Que devant toy ne doy venir
Pour ma très grant transgression.
Rayson et desperacion
30
Contre moy veulent maintenir;
Mès pour ce que veil plait fenir,
Devant toy les fès convenir
En faisant replicacion.
C'est que je di appartenir
A toy du tout et convenir
Pitié et miseracion.
Dame es de misericorde
Par qui Diex bien se recorde
A sa gent estre racordé.
40
Par toy vint pes et concorde,
now the bowe bent in swich manere,
30
was first, of Iustice and of yre,
ghtful God nolde of no mercy here;
urgh thee han we grace, as we desyre.
hath myn hope of refut been in thee,
eer-biforn ful ofte, in many a wyse,
35
hou to misericorde receyved me.
ercy, lady, at the grete assyse,
we shul come bifore the hye Iustyse!
el fruit shal thanne in me be founde,
but thou er that day me wel chastyse,
40
rrey right my werk me wol confounde.
g, I flee for socour to thy tente
r to hyde from tempest ful of drede,
Et fu pour oster discorde
L'arc de justice descordé;
Et pour ce me sui acordé
Toi mercier et concordé,
Pour ce que ostas la corde;
Quar, ainsi com j'ay recordé,
S'encore fust l'arc encordé
Comparé l'eust ma vie orde.
En toy ay m'esperance eü
50
Quant a merci m'as receü
Autre foys en mainte guise,
Du bien qui ou ciel fu creü
As ravivé et repeü
M'ame qui estoit occise.
Las! mès quant la grant assise
Sera, se n'y es assise
Pour moy mal y seray veü.
De bien n'ay nulle reprise.
Las m'en clain quant bien m'avise,
60
Souvent en doy dire heü!
Fuiant m'en viens a ta tente
Moy mucier pour la tormente
Qui ou monde me tempeste.

hing you that ye you not absente,
gh I be wikke. O help yit at this nede!
Pour mon pechié ne t'absente,
45
ve I been a beste in wille and dede,
dy, thou me clothe with thy grace.
enemy and myn—lady, tak hede,
my deth in poynt is me to chace.
us mayde and moder, which that never
50
bitter, neither in erthe nor in see,
l of swetnesse and of mercy ever,
hat my fader be not wroth with me!
thou, for I ne dar not him y-see.
ve I doon in erthe, allas ther-whyle!
55
certes, but-if thou my socour be,
nk eterne he wol my gost exyle.
uched sauf, tel him, as was his wille,
e a man, to have our alliaunce,
with his precious blood he wroot the bille
60
the crois, as general acquitaunce,
ery penitent in ful creaunce;
herfor, lady bright, thou for us praye.
shalt thou bothe stinte al his grevaunce,
make our foo to failen of his praye.
A moy garder met t'entente,
A mon besoing soiez preste.
Se lonc temps j'ay esté beste
A ce, Vierge, je m'arreste
Que de ta grace me sente.
70
Si te fais aussi requeste
Que ta pitié nu me veste,
Car je n'ay nulle autre rente.
Glorieuse vierge mere
Qui a nul onques amere
Ne fus en terre ne en mer,
Ta douceur ores m'apere
Et ne sueffres que mon pere
De devant li me jecte puer.
Se devant li tout vuit j'apper,
80
Et par moy ne puis eschapper
Que ma faute ne compere.
Tu devant li pour moy te per
En li moustrant que, s'a li per
Ne sui, si est il mon frere.
Homme voult par sa plaisance
Devenir, pour aliance
Avoir a humain lignage.
Avec li crut dès enfance
Pitié dont j'ai esperance
90
Avoir eu en mon usage.
Elle fu mise a forage
Quant au cuer lui vint mesage
Du cruel fer de la lance.
Ne puet estre, se sui sage,
Que je n'en aie avantage,
Se tu veus et abondance.
65
it wel, thou wolt ben our socour,
art so ful of bountee, in certeyn.
han a soule falleth in errour,
tee goth and haleth him ayeyn.
makest thou his pees with his sovereyn,
Ie ne truis par nulle voie
Ou mon salut si bien voie
Com, après Dieu, en toy le voy;
100
Quar quant aucun se desvoie,
A ce que tost se ravoie,

70
ringest him out of the crooked strete.
so thee loveth he shal not love in veyn,
shal he finde, as he the lyf shal lete.
deres enlumined ben they
n this world ben lighted with thy name,
75
who-so goth to you the righte wey,
har not drede in soule to be lame.
queen of comfort, sith thou art that same
om I seche for my medicyne,
ot my foo no more my wounde entame,
80
ele in-to thyn hand al I resigne.
thy sorwe can I not portreye
the cros, ne his grevous penaunce.
or your bothes peynes, I you preye,
ot our alder foo make his bobaunce,
De ta pitié li fais convoy.
Tu li fès lessier son desroy
Et li refaiz sa pais au roy,
Et remez en droite voie.
Moult est donc cil en bon arroy,
En bon atour, en bon conroy
Que ta grace si conroie.
Kalendier sont enluminé
110
Et autre livre enteriné
Quant ton non les enlumine.
A tout meschief ont resiné
Ceus qui se sont acheminé
A toy pour leur medicine.
A moy donc, virge, t'encline,
Car a toy je m'achemine
Pour estre bien mediciné;
Ne sueffre que de gaïnne
Isse justice devine
120
Par quoy je soye exterminé.
La douceur de toy pourtraire
Je ne puis, a qui retraire
Doit ton filz de ton sanc estrait;
Pour ce a toy m'ay volu traire
85
he hath in his listes of mischaunce
ct that ye bothe have bought so dere.
eide erst, thou ground of our substaunce,
nue on us thy pitous eyen clere!
s, that saugh the bush with flaumes rede
90
inge, of which ther never a stikke brende,
igne of thyn unwemmed maidenhede.
art the bush on which ther gan descende
oly Gost, the which that Moises wende
en a-fyr; and this was in figure.
95
Afin que contre moy traire
Ne le sueuffres nul cruel trait.
Je recongnois bien mon mesfait
Et qu'au colier j'ai souvent trait
Dont l'en me devroit detraire;
130
Mez se tu veus tu as l'entrait
Par quoy tantost sera retrait
Le mehain qui m'est contraire.
Moyses vit en figure
Que tu, vierge nete et pure,
Jesu le filz Dieu conceüs:
Un bysson contre nature
Vit qui ardoit sans arsure.
C'es tu, n'en suis point deceüs,
Dex est li feus qu'en toy eüs;
140

ady, from the fyr thou us defende
that in helle eternally shal dure.
princesse, that never haddest pere,
s, if any comfort in us be,
cometh of thee, thou Cristes moder dere,
100
an non other melodye or glee
reioyse in our adversitee,
vocat noon that wol and dar so preye
s, and that for litel hyre as ye,
helpen for an Ave-Marie or tweye.
Et tu, buisson des recreüz
Es, pour tremper leur ardure.
A ce veoir, vierge, veüs
Soie par toy et receüs,
Oste chaussement d'ordure.
Noble princesse du monde
Qui n'as ne per ne seconde
En royaume n'en enpire,
De toy vient, de toy redonde
Tout le bien qui nous abonde,
150
N'avons autre tirelire.
En toy tout povre homme espire
Et de toy son salu tire,
Et en toy seule se fonde.
Ne puet nul penser ne dire,
Nul pourtraire ne escrire
Ta bonté comme est parfonde.
105
rey light of eyen that ben blinde,
rey lust of labour and distresse,
orere of bountee to mankinde,
whom God chees to moder for humblesse!
his ancille he made thee maistresse
110
vene and erthe, our bille up for to bede.
world awaiteth ever on thy goodnesse,
ou ne failest never wight at nede.
s I have sum tyme for tenquere,
fore and why the Holy Gost thee soughte,
115
Gabrielles vois cam to thyn ere.
t to werre us swich a wonder wroughte,
r to save us that he sithen boughte.
nedeth us no wepen us for to save,
nly ther we did not, as us oughte,
120
nitence, and mercy axe and have.
O Lumiere des non voians
Et vrai repos des recreans
Et de tout bien tresoriere,
160
A toy sont toutez gens beans
Qui en la foy sont bien creans
Et en toy ont foy entiere;
A nul onques ne fus fiere,
Ains toy deïs chamberiere
Quant en toy vint li grans geans.
Or es de Dieu chanceliere
Et de graces aumosniere
Et confort a tous recreans.
Pris m'est volenté d'enquerre
170
Pour savoir que Diex vint querre
Quant en toy se vint enserrer;
En toy devint vers de terre;
Ne cuit pas que fust pour guerre
Ne pour moy jus aterrer.
Vierge, se ne me sens errer,
D'armes ne me faut point ferrer
Fors sans plus de li requerre.
Quant pour moy se vint enterrer,
Se il ne se veut desterrer

n of comfort, yit whan I me bithinke
agilt have bothe, him and thee,
hat my soule is worthy for to sinke,
I, caitif, whider may I flee?
180
Encor puis s'amour acquerre.
Quant pourpensé après me sui
Qu'ay offendu et toy et lui,
Et qu'a mal est m'ame duite,
Que, fors pechié, en moi n'estui,
125
shal un-to thy sone my mene be?
but thy-self, that art of pitee welle?
hast more reuthe on our adversitee
in this world mighte any tunge telle.
sse me, moder, and me chastyse,
130
erteynly, my fadres chastisinge
dar I nought abyden in no wyse:
dous is his rightful rekeninge.
r, of whom our mercy gan to springe,
ye my Iuge and eek my soules leche;
135
ver in you is pitee haboundinge
h that wol of pitee you biseche.
s, that God ne graunteth no pitee
oute thee; for God, of his goodnesse,
eth noon, but it lyke un-to thee.
140
th thee maked vicaire and maistresse
Et que mal hyer et pis m'est hui,
Tost après si me ranvite,
Vierge douce, se pren fuite,
Se je fui a la poursuite,
Ou fuiray, qu'a mon refui?
190
S'a nul bien je ne m'affruite
Et mas sui avant que luite,
Plus grief encore en est l'anuy.
Reprens moy, mere, et chastie
Quar mon pere n'ose mie
Attendre a mon chastiement.
Son chastoy si fiert a hie;
Rien n'ataint que tout n'esmie
Quant il veut prendre vengement.
Mere, bien doi tel batement
200
Douter, quar en empirement
A tous jours esté ma vie.
A toy dont soit le jugement,
Car de pitié as l'oingnement,
Mès que merci l'en te prie.
Sans toy nul bien ne foysonne
Et sans toy Diex riens ne donne,
Quar de tout t'a fet maistresse.
Quant tu veus trestout pardonne;
the world, and eek governeresse
vene, and he represseth his Iustyse
thy wille, and therefore in witnesse
th thee crouned in so ryal wyse.
Et par toy est mise bonne
210
A justice la mairesse;
N'est royne ne princesse
Pour qui nul ainsi se cesse
Et de droit se dessaisonne.
Du monde es gouverneresse,
Et du ciel ordeneresse;

145
le devout, ther god hath his woninge.
hich these misbileved pryved been,
u my soule penitent I bringe.
ve me! I can no ferther fleen!
thornes venimous, O hevene queen,
150
hich the erthe acursed was ful yore,
so wounded, as ye may wel seen,
am lost almost;—it smert so sore.
e, that art so noble of apparaile,
edest us in-to the hye tour
155
radys, thou me wisse and counsaile,
may have thy grace and thy socour;
ve I been in filthe and in errour.
un-to that court thou me aiourne
cleped is thy bench, O fresshe flour!
160
as that mercy ever shal soiourne.
Sans reson n'as pas couronne.
Temple saint ou Dieu habite
Dont privé sont li herite
Et a tous jours desherité,
220
A toy vieng, de toy me herite,
Reçoif moy par ta merite
Quar de toy n'ay point hesité.
Et se je me sui herité
Des espines d'iniquité
Pour quoy terre fu maudite,
Las m'en clain en verité,
Car a ce fait m'a excité
L'ame qui n'en est pas quite.
Vierge de noble et haut atour,
230
Qui au chastel et a la tour
De paradis nous atournes,
Atourne moy ens et entour
De tel atour que au retour
De ta grace me retournes,
Se vil sui, si me raournes.
A toy vieng, ne te destournes,
Quer au besoing es mon destour.
Sequeur moy, point ne sejournes,
Ou tu a la court m'ajournes,
240
Ou ta pitié fait son sejour.
s, thy sone, that in this world alighte,
the cros to suffre his passioun,
ek, that Longius his herte pighte,
made his herte blood to renne adoun;
165
l was this for my salvacioun;
to him am fals and eek unkinde,
it he wol not my dampnacioun—
hanke I you, socour of al mankinde.
was figure of his deeth, certeyn,
Xristus, ton filz, qui descendi
En terre et en la crois pendi,
Ot pour moy le costé fendu.
Sa grant rigour il destendi
Quant pour moy l'esperit rendi,
Son corps pendant et estendu;
Pour moy son sanc fu espandu.
Se ceci j'ai bien entendu
A mon salut bien entendi,
250
Et pour ce, se l'ay offendu
Et il ne le m'a pas rendu,
Merci t'en rens, graces l'en di.
Ysaac le prefigura

170
so fer-forth his fader wolde obeye
him ne roughte no-thing to be slayn;
so thy sone list, as a lamb, to deye.
ady, ful of mercy, I you preye,
e his mercy mesured so large,
175
not skant; for alle we singe and seye
ye ben from vengeaunce ay our targe.
rie you clepeth the open welle
sshe sinful soule out of his gilt.
ore this lessoun oughte I wel to telle
180
nere thy tender herte, we weren spilt.
Qui de sa mort rien ne cura
En obeïsant au pere.
Comme .j. aignel tout endura;
En endurant tout espura
Par crueuse mort amere.
O très douce vierge mere,
260
Par ce fait fai que se pere
Par plour l'ame qui cuer dura;
Fai que grace si m'apere;
Et n'en soiez pas avere
Quar largement la mesura.
Zacharie de mon somme
Me exite, et si me somme
D'en toy ma merci atendre;
Fontaine patent te nomme
ady brighte, sith thou canst and wilt
o the seed of Adam merciable,
ng us to that palais that is bilt
184
nitents that ben to mercy able. Amen.
Pour laver pecheür homme:
270
C'est leçon bonne a aprendre.
Se tu donc as le cuer tendre
Et m'offense n'est pas mendre
De cil qui menga la pomme,
Moy laver veillez entendre,
Moy garder et moy deffendre,
Que justice ne m'asomme.

Explicit carmen.
The MSS. used to form this text are: C. = MS. Ff. 5. 30 in the Camb.
Univ. Library; Jo. = MS. G. 21, in St. John's College, Cambridge; Gl.
= Glasgow MS. Q. 2. 25; L. = MS. Laud 740, in the Bodleian Library;
Gg. = MS. Gg. 4. 27 in the Camb. Univ. Library; F. = MS. Fairfax 16,
in the Bodleian Library; B = MS. Bodley 638; Sion = Sion Coll. MS.
The text closely follows the first of these; and all variations from it
are recorded (except sometimes i for y, and y for i).
1. C. Almihty; queene. 3. L. B. sorwe; F. Jo. sorowe; the rest insert
of before sorwe. 4. C. Gloriowse. 6. C. releeue; mihti. 8. Jo.
Venquist; Gg. Venquyst. Read m'hath. C. cruelle.
10. C. bee. 11. F. B. werne. 12. C. helpe. 14. C. Hauene; refute. 15.
C. Loo; theeves sevene; mee. 16. C. briht. 17. C. ladi deere. 18. C.
loo. 19. C. ouhten; thi; appeere. 20. C. greevous. 21. C. riht. 22. C.
riht þei mihten; susteene. 23. C. wurthi. 24. C. queene. 25. C.
Dowte. 26. C. merci heere. 27. C. Gl. Gg. saf; Jo. saff; L. F. saufe; B.
sauf. C. thoruh; L. F. þurgh. Gl. F. B. tacorde; C. L. to accorde. 28. C.
crystes; mooder deere.
29. C. maneere. 31. C. rihtful; heere. 32. C. thoruh; Jo. L. F. B.
thurgh. 33. C. Euere. C. refuit; Gl. refuyt; Gg. refut; rest refute. 35.
C. resceyued. 36. C. merci ladi. 37. C. shule. 39. wel is supplied from
the Sion MS.; nearly all the copies give this line corruptly; see note.
40. C. riht; wole. 41. C. Fleeinge; thi. 42. C. tempeste; dreede. 43.
C. Biseeching yow. 44. C. Thouh; neede.
45. C. ben. Jo. wille; C. wil. 46. C. thi. 47. C. Thin; ladi; heede. 49.
C. Gloriows; mooder; neuere. 50. C. eerthe. 51. C. euere. 54. C.
eerthe. 55. C. bee. 56. C. wole. 57. C. saaf; F. B. sauf; L. saufe; Jo.
saffe; Gl. Gg. saf. 58. C. Bicomen; oure. 59. C. wrot. 61. C. criaunce;
Gg. cryaunce; rest creaunce. 62. C. ladi briht. 63. C. Thanne.

64, 65: C. oure. 66: C. bowntee. 69: C. Thanne. 73: C. Kalendeeres
enlumyned. 74: C. thi. 75: C. yow; rihte. 77: C. sithe. 78: C. seeche.
79: C. vntame; Sion, vntaame (wrongly); rest entame.] 80: C.
resyne; Gl. B. resigne. 81: C. kan. 82: C. greevous. 84: C. oure.
85. C. hise lystes. 86. C. bouht. 87. C. oure. 88. C. thi; cleere. 89. C.
sauh; F. B. saugh. C. flawmes. 93. C. holigost. 94. C. a fyir. 95. C.
fyir; Gl. fyr. C. deufende (sic). 96. C. eternalli. 97. C. neuere; peere.
98. C. bee. 99. C. mooder deere. 100. C. noon ooþer. 101. C. oure.
102. C. wole. 103. C. yee.
107. C. tresoreere. 108. F. chees; C. ches. C. mooder. 109. C. the.
110. C. eerthe; oure; beede. 111. C. euere; thi. 112. C. neuere;
neede. 113. Gg. F. B. tenquere; C. to enquere. 114. C. whi; holi;
souhte. 115. C. Sion, vn-to; rest to. 116. C. wunder wrouhte. 117. C.
bouhte. 118. C. Thanne needeth; wepene. 119. C. oonly. Jo. F. B.
did; C. diden. C. ouhte. 120. C. Doo; merci. 123. C. wurthi.
125. C. thi; bee. 126. C. thi-. 128. C. miht. 129. C. mooder. 130. F.
Fadres; B. fadrys; C. faderes; Jo. fader. 131. C. nouht. 132. Gg. F. B.
is his; rest it is. C. rihful (sic). 133. C. Mooder; merci. 135. C. euere.
136. C. eche; wole; biseeche. 137. C. granteth; F. graunteth. 140. C.
vicair; Gg. F. vicaire; Gl. B. Sion, vicayre.
141. C. gouernowresse; Gl. Gg. gouerneresse. 143. C. thi wil. 144. L.
crowned; Gg. crounnyd; C. Jo. F. corowned. C. rial. 146. C.
misbileeued. Jo. L. pryued; rest depriued. 148. C. Resceyve; ferþere.
149. C. venymous. 150. C. eerthe. 151. C. (alone) om. so. 156. C.
thi (twice). 157. Gg. Al; B. C. All. C. ben. 158. C. Ladi. 159. Sion MS.
fresshe; Gg. frosche (sic); the rest wrongly omit the final e. 160. C.
merci; euere.
161. C. Xpc (= Gk. χρς). 163. All the MSS. insert suffred after eek,
caught from the line above; see note. 167. C. wole. 171. C. rouhte.
172. C. Riht soo thi. C. lust; rest list, liste. 173. C. ladi; merci; yow.
174. C. Sithe; merci. 177. C. yow; opene. 179. C. ouht. 180. C. thi.

181. C. ladi. Gg. bryȝt; which the rest omit. C. Gg. sithe; F. B. sith.
Harl. 2251 supplies bothe after thou. 183. Sion MS. alone supplies
So; Jo. supplies And. MS. Harl. 2251 has un-to; rest to. 184. Gl.
penytentz; C. penitentes; Jo. Penitence (for penitents). C. merci.
II. THE COMPLEYNTE UNTO PITE.
Pite, that I have sought so yore ago,
With herte sore, and ful of besy peyne,
That in this world was never wight so wo
With-oute dethe; and, if I shal not feyne,
5
My purpos was, to Pite to compleyne
Upon the crueltee and tirannye
Of Love, that for my trouthe doth me dye.
And when that I, by lengthe of certeyn yeres,
Had ever in oon a tyme sought to speke,
10
To Pite ran I, al bespreynt with teres,
To preyen hir on Crueltee me awreke.
But, er I might with any worde out-breke,
Or tellen any of my peynes smerte,
I fond hir deed, and buried in an herte.
15
Adoun I fel, when that I saugh the herse,
Deed as a stoon, whyl that the swogh me laste;
But up I roos, with colour ful diverse,
And pitously on hir myn yën caste,
And ner the corps I gan to presen faste,
20
And for the soule I shoop me for to preye;
I nas but lorn; ther nas no more to seye.

Thus am I slayn, sith that Pite is deed;
Allas! that day! that ever hit shulde falle!
What maner man dar now holde up his heed?
25
To whom shal any sorwful herte calle?
Now Crueltee hath cast to sleen us alle,
In ydel hope, folk redelees of peyne—
Sith she is deed—to whom shul we compleyne?
But yet encreseth me this wonder newe,
30
That no wight woot that she is deed, but I;
So many men as in hir tyme hir knewe,
And yet she dyed not so sodeynly;
For I have sought hir ever ful besily
Sith first I hadde wit or mannes mynde;
35
But she was deed, er that I coude hir fynde.
Aboute hir herse ther stoden lustily,
Withouten any wo, as thoughte me,
Bountee parfit, wel armed and richely,
And fresshe Beautee, Lust, and Iolitee,
40
Assured Maner, Youthe, and Honestee,
Wisdom, Estaat, [and] Dreed, and Governaunce,
Confedred bothe by bonde and alliaunce.
A compleynt hadde I, writen, in myn hond,
For to have put to Pite as a bille,
45
But whan I al this companye ther fond,
That rather wolden al my cause spille
Than do me help, I held my pleynte stille;
For to that folk, withouten any faile,
Withoute Pite may no bille availe.

50
Then leve I al thise virtues, sauf Pite,
Keping the corps, as ye have herd me seyn,
Confedred alle by bonde of Crueltee,
And been assented that I shal be sleyn.
And I have put my compleynt up ageyn;
55
For to my foos my bille I dar not shewe,
Theffect of which seith thus, in wordes fewe:—
The Bille.
¶ 'Humblest of herte, hyest of reverence,
Benigne flour, coroune of vertues alle,
Sheweth unto your rial excellence
60
Your servaunt, if I durste me so calle,
His mortal harm, in which he is y-falle,
And noght al only for his evel fare,
But for your renoun, as he shal declare.
Hit stondeth thus: your contraire, Crueltee,
65
Allyed is ageynst your regalye
Under colour of womanly Beautee,
For men [ne] shuld not knowe hir tirannye,
With Bountee, Gentilesse, and Curtesye,
And hath depryved you now of your place
70
That hight "Beautee, apertenant to Grace."
For kyndly, by your heritage right,
Ye been annexed ever unto Bountee;
And verrayly ye oughte do your might
To helpe Trouthe in his adversitee.
75

Ye been also the coroune of Beautee;
And certes, if ye wanten in thise tweyne,
The world is lore; ther nis no more to seyne.
¶ 'Eek what availeth Maner and Gentilesse
Withoute you, benigne creature?
80
Shal Crueltee be your governeresse?
Allas! what herte may hit longe endure?
Wherfor, but ye the rather take cure
To breke that perilous alliaunce,
Ye sleen hem that ben in your obeisaunce.
85
'And further over, if ye suffre this,
Your renoun is fordo than in a throwe;
Ther shal no man wite wel what Pite is.
Allas! that your renoun shuld be so lowe!
Ye be than fro your heritage y-throwe
90
By Crueltee, that occupieth your place;
And we despeired, that seken to your grace.
Have mercy on me, thou Herenus quene,
That you have sought so tenderly and yore;
Let som streem of your light on me be sene
95
That love and drede you, ay lenger the more.
For, sothly for to seyne, I bere the sore,
And, though I be not cunning for to pleyne,
For goddes love, have mercy on my peyne!
¶ 'My peyne is this, that what so I desire
100
That have I not, ne no-thing lyk therto;
And ever set Desire myn herte on fire;

Eek on that other syde, wher-so I go,
What maner thing that may encrese wo
That have I redy, unsoght, everywhere;
105
Me [ne] lakketh but my deth, and than my bere.
What nedeth to shewe parcel of my peyne?
Sith every wo that herte may bethinke
I suffre, and yet I dar not to you pleyne;
For wel I woot, al-though I wake or winke,
110
Ye rekke not whether I flete or sinke.
But natheles, my trouthe I shal sustene
Unto my deth, and that shal wel be sene.
This is to seyne, I wol be youres ever;
Though ye me slee by Crueltee, your fo,
115
Algate my spirit shal never dissever
Fro your servyse, for any peyne or wo.
Sith ye be deed—allas! that hit is so!—
Thus for your deth I may wel wepe and pleyne
119
With herte sore and ful of besy peyne.'
Here endeth the exclamacion of the Deth of Pyte.
The MSS. are: Tn. (Tanner 346); F. (Fairfax 16); B. (Bodley 638); Sh.
(Shirley's MS., Harl. 78); Ff. (Ff. 1. 6, in Camb. Univ. Library); T., here
used for Trin. (Trin. Coll. Camb. R. 3. 19); also Ha. (Harl. 7578). I
follow F. mainly, noting all variations of importance.
Title; in B. 1. F. agoo. 2. F. hert. 3. F. worlde; woo. 5. F. purpose. 8.
F. be; B. Sh. T. by. F. certeyne. 9. Sh. Ha. a tyme sought; rest sought
a tyme (badly). 10. F. bespreynte. 11. F. prayen. Sh. Ha. wreke; rest
awreke. 14. F. fonde; dede. 15. F. Adovne. Ha. alone supplies that.

16. F. Dede; stone; while. T. (and Longleat) a; rest om. 17. F. roose;
coloure. 18. F. petously; B. pitously. B. yen; F. eyen; after which all
but Sh. and Ha. insert I. 19. Sh. Ha. to; which the rest omit. 20. Sh.
shoope; rest shope. F. prey; Sh. preye. 21. For nas, the MSS.
wrongly have was; in both places. F. lorne; sey.
22. F. slayne; dede. 23. Tn. shulde; F. shuld. 24. F. hold; hede. 25.
All but Sh. and Ha. ins. now bef. any. F. eny. 26. F. caste. Sh. Ha.
sleen; F. slee. 27. F. folke redelesse. 30. F. dede. 31. F. mony. 32. F.
B. omit she; the rest have it. Only Sh. and T. retain so. 33. F. besely.
For ever, Ten Brink reads ay. 34. Only Sh. gives this line correctly; so
Ha. (but with any for mannes). F. Sith I hadde firste witte or mynde.
35. F. dede. Sh. Ha. that; rest omit. 36. F. there; lustely. 38. F.
Bounte. 39. F. beaute; iolyte. 40. F. honeste. 41. F. Wisdome. F. B.
estaat; rest estate; Ten Brink rightly supplies and after Estat (sic). F.
drede. 43. Ha. hadde; Sh. hade; rest had. F. honde. 44. Sh. Ha. For;
rest omit. F. pittee. 45. F. when. F. fonde. 46. Sh. wolden; F. wolde.
47. F. helpe; helde. Sh. Ha. compleynt; T. cause; rest pleynte or
pleynt.
48. F. folke. F. withoute; B. without; Ha. withouten. 49. F. pitee. Ha.
may; Sh. ne may; rest ther may. 50. Sh. Ha. þanne leve I alle þees
vertues sauf pitee; F.B. Then leve we al vertues save oonly pite; Tn.
Ff. T. Then leueall vertues save onely pite. 51. F. Kepynge; herde.
52. F. Cofedered (sic). Sh. alle by bonde of (Ha. om. alle); F. Tn. B.
Ff. by bonde and by; T. by bound and. 53. Sh. that; rest when. 54. F.
complaynt. 55. F. Foes; Tn. foos. 57. F. highest. 59. F. youre rialle.
60. F. Youre; durst. 61. Sh. whiche he is Inne falle; rest in which he
is falle: Thynne has yfal; read y-falle. 62. F. oonly. 64. The MSS.
insert that after thus, except Sh. and Ha. Sh. contraire; rest contrary.
65. Sh. ageynst; F. ayenst. 66. F. beaute. 67. The MSS. omit ne. F.
shulde. 68. F. bounte. 69. Sh. nowe; which the rest omit. 70. Sh.
heghte (for highte); Ha. hight; Tn. is hye; F. B. T. is hygh. F. beaute
apertenent. The MSS. (except Sh. and Ha.) insert your after to.

71. F. kyndely; youre. 72. Most MSS. be; Ha. been; read been (and
in l. 75). 73. F. verrely; youre. 75. F. beaute. 76. Tn. Ff. Ha. wante;
rest want; read wanten. F. these tweyn. 77. F. worlde. For nis, all
have is. F. seyn. 78. F. Eke. 79. F. yow. 82. F. Wherfore. 86. F.
fordoo. Sh. than; rest omit. 87. F. wete well; rest omit well; Tn.
wyte. 88. F. Tn. B. Ff. T. insert euer after that, which Sh. rightly
omits. Sh. Ha. shoulde be; rest is falle. 89. Sh. thanne; rest also. F.
youre. 90. F. youre. 91. Sh. sechen to; B. sekyn to; Tn. Ff. T. seken;
F. speken to (for seken to). 92. Tn. F. B. Ff. herenus; T. heremus; Sh.
vertuouse (!). 93. F. yow; tendirly. 94. B. som; F. somme. F. streme.
Sh. Ha. youre; which the rest omit. 95. Sh. ay; rest euer. Sh. Ha.
om. the. 96. F. sothely. Sh. the hevy sore; Ha. the sore; rest so sore
(which gives no sense).
97. F. kunnynge. 98. F. goddis. 100. F. lyke. 101. F. Sh. setteth; Ha.
set; rest settith; see note. F. hert. 102. F. Eke. F. sydes; rest side,
syde. F. where so; goo. 103. Sh. Ha. we; rest insert my before wo.
104. F. vnsoghte. 105. All omit ne; see note. 107. F. woo. 109. F.
wote. Sh. al-þaughe; rest though, thogh. 110. F. B. where; rest
whether. 111. All but Sh. and Ha. needlessly insert yet before my.
114. F. soo; rest foo, fo. 115. F. spirite. 116. F. youre; eny. 117. B.
yet (sic) be ded; F. Tn. Ff. T. ye be yet ded (which will not scan); Sh.
Ha. have a diferent line—Now pitee þat I haue sought so yoore
agoo.
III. THE BOOK OF THE DUCHESSE.
The Proem.
I have gret wonder, by this lighte,
How that I live, for day ne nighte
I may nat slepe wel nigh noght;
I have so many an ydel thoght
5
Purely for defaute of slepe,

That, by my trouthe, I take kepe
Of no-thing, how hit cometh or goth,
Ne me nis no-thing leef nor loth.
Al is y-liche good to me—
10
Ioye or sorowe, wherso hit be—
For I have feling in no-thing,
But, as it were, a mased thing,
Alway in point to falle a-doun;
For [sory] imaginacioun
15
Is alway hoolly in my minde.
And wel ye wite, agaynes kinde
Hit were to liven in this wyse;
For nature wolde nat suffyse
To noon erthely creature
20
Not longe tyme to endure
Withoute slepe, and been in sorwe;
And I ne may, ne night ne morwe,
Slepe; and thus melancolye,
And dreed I have for to dye,
25
Defaute of slepe, and hevinesse
Hath sleyn my spirit of quiknesse,
That I have lost al lustihede.
Suche fantasyes ben in myn hede
So I not what is best to do.
30
But men mighte axe me, why so
I may not slepe, and what me is?
But natheles, who aske this
Leseth his asking trewely.
My-selven can not telle why
35
The sooth; but trewely, as I gesse,

I holdë hit be a siknesse
That I have suffred this eight yere,
And yet my bote is never the nere;
For ther is phisicien but oon,
40
That may me hele; but that is doon.
Passe we over until eft;
That wil not be, moot nede be left;
Our first matere is good to kepe.
So whan I saw I might not slepe,
45
Til now late, this other night,
Upon my bedde I sat upright,
And bad oon reche me a book,
A romaunce, and he hit me took
To rede and dryve the night away;
50
For me thoghte it better play
Then playen either at chesse or tables.
And in this boke were writen fables
That clerkes hadde, in olde tyme,
And other poets, put in ryme
55
To rede, and for to be in minde
Whyl men loved the lawe of kinde.
This book ne spak but of such thinges,
Of quenes lyves, and of kinges,
And many othere thinges smale.
60
Amonge al this I fond a tale
That me thoughte a wonder thing.
This was the tale: Ther was a king
That highte Seys, and hadde a wyf,
The beste that mighte bere lyf;
65
And this quene highte Alcyone.

So hit befel, therafter sone,
This king wolde wenden over see.
To tellen shortly, whan that he
Was in the see, thus in this wyse,
70
Soche a tempest gan to ryse
That brak hir mast, and made it falle,
And clefte hir ship, and dreinte hem alle,
That never was founden, as it telles,
Bord ne man, ne nothing elles.
75
Right thus this king Seys loste his lyf.
Now for to speken of his wyf:—
This lady, that was left at home,
Hath wonder, that the king ne come
Hoom, for hit was a longe terme.
80
Anon her herte gan to erme;
And for that hir thoughte evermo
Hit was not wel [he dwelte] so,
She longed so after the king
That certes, hit were a pitous thing
85
To telle hir hertely sorwful lyf
That hadde, alas! this noble wyf;
For him she loved alderbest.
Anon she sente bothe eest and west
To seke him, but they founde nought.
90
'Alas!' quoth she, 'that I was wrought!
And wher my lord, my love, be deed?
Certes, I nil never ete breed,
I make a-vowe to my god here,
But I mowe of my lorde here!'
95
Such sorwe this lady to her took

That trewely I, which made this book,
Had swich pite and swich rowthe
To rede hir sorwe, that, by my trowthe,
I ferde the worse al the morwe
100
After, to thenken on her sorwe.
So whan [she] coude here no word
That no man mighte fynde hir lord,
Ful oft she swouned, and seide 'alas!'
For sorwe ful nigh wood she was,
105
Ne she coude no reed but oon;
But doun on knees she sat anoon,
And weep, that pite was to here.
'A! mercy! swete lady dere!'
Quod she to Iuno, hir goddesse;
110
'Help me out of this distresse,
And yeve me grace my lord to see
Sone, or wite wher-so he be,
Or how he fareth, or in what wyse,
And I shal make you sacrifyse,
115
And hoolly youres become I shal
With good wil, body, herte, and al;
And but thou wilt this, lady swete,
Send me grace to slepe, and mete
In my slepe som certeyn sweven,
120
Wher-through that I may knowen even
Whether my lord be quik or deed.'
With that word she heng doun the heed,
And fil a-swown as cold as ston;
Hir women caughte her up anon,
125
And broghten hir in bed al naked,

And she, forweped and forwaked,
Was wery, and thus the dede sleep
Fil on her, or she toke keep,
Through Iuno, that had herd hir bone,
130
That made hir [for] to slepe sone;
For as she prayde, so was don,
In dede; for Iuno, right anon,
Called thus her messagere
To do her erande, and he com nere.
135
Whan he was come, she bad him thus:
Go bet,' quod Iuno, 'to Morpheus,
Thou knowest him wel, the god of sleep;
Now understond wel, and tak keep.
Sey thus on my halfe, that he
140
Go faste into the grete see,
And bid him that, on alle thing,
He take up Seys body the king,
That lyth ful pale and no-thing rody.
Bid him crepe into the body,
145
Aud do it goon to Alcyone
The quene, ther she lyth alone,
And shewe hir shortly, hit is no nay,
How hit was dreynt this other day;
And do the body speke so
150
Right as hit was wont to do,
The whyles that hit was on lyve.
Go now faste, and hy thee blyve!'
This messager took leve and wente
Upon his wey, and never ne stente
155
Til he com to the derke valeye

That stant bytwene roches tweye
Ther never yet grew corn ne gras,
Ne tree, ne nothing that ought was,
Beste, ne man, ne nothing elles,
160
Save ther were a fewe welles
Came renning fro the cliffes adoun,
That made a deedly sleping soun,
And ronnen doun right by a cave
That was under a rokke y-grave
165
Amid the valey, wonder depe.
Ther thise goddes laye and slepe,
Morpheus, and Eclympasteyre,
That was the god of slepes heyre,
That slepe and did non other werk.
170
This cave was also as derk
As helle pit over-al aboute;
They had good leyser for to route
To envye, who might slepe beste;
Some henge hir chin upon hir breste
175
And slepe upright, hir heed y-hed,
And some laye naked in hir bed,
And slepe whyles the dayes laste.
This messager com flying faste,
And cryed, 'O ho! awak anon!'
180
Hit was for noght; ther herde him non.
Awak!' quod he, 'who is, lyth there?'
And blew his horn right in hir ere,
And cryed 'awaketh!' wonder hyë.
This god of slepe, with his oon yë
185
Cast up, axed, 'who clepeth there?'

Hit am I,' quod this messagere;
Iuno bad thou shuldest goon'—
And tolde him what he shulde doon
As I have told yow here-tofore;
190
Hit is no need reherse hit more;
And wente his wey, whan he had sayd.
Anon this god of slepe a-brayd
Out of his slepe, and gan to goon,
And did as he had bede him doon;
195
Took up the dreynte body sone,
And bar hit forth to Alcyone,
His wyf the quene, ther-as she lay,
Right even a quarter before day,
And stood right at hir beddes fete,
200
And called hir, right as she hete,
By name, and seyde, 'my swete wyf,
Awak! let be your sorwful lyf!
For in your sorwe ther lyth no reed;
For certes, swete, I nam but deed;
205
Ye shul me never on lyve y-see.
But good swete herte, [look] that ye
Bury my body, [at whiche] a tyde
Ye mowe hit finde the see besyde;
And far-wel, swete, my worldes blisse!
210
I praye god your sorwe lisse;
To litel whyl our blisse lasteth!'
With that hir eyen up she casteth,
And saw noght; '[A]!' quod she, 'for sorwe!'
And deyed within the thridde morwe.
215
But what she sayde more in that swow

I may not telle yow as now,
Hit were to longe for to dwelle;
My first matere I wil yow telle,
Wherfor I have told this thing
220
Of Alcione and Seys the king.
For thus moche dar I saye wel,
I had be dolven everydel,
And deed, right through defaute of sleep,
If I nad red and taken keep
225
Of this tale next before:
And I wol telle yow wherfore;
For I ne might, for bote ne bale,
Slepe, or I had red this tale
Of this dreynte Seys the king,
230
And of the goddes of sleping.
Whan I had red this tale wel,
And over-loked hit everydel,
Me thoughte wonder if hit were so;
For I had never herd speke, or tho,
235
Of no goddes that coude make
Men [for] to slepe, ne for to wake;
For I ne knew never god but oon.
And in my game I sayde anoon—
And yet me list right evel to pleye—
240
'Rather then that I shulde deye
Through defaute of sleping thus,
I wolde yive thilke Morpheus,
Or his goddesse, dame Iuno,
Or som wight elles, I ne roghte who—
245
To make me slepe and have som reste—

I wil yive him the alder-beste
Yift that ever he abood his lyve,
And here on warde, right now, as blyve;
If he wol make me slepe a lyte,
250
Of downe of pure dowves whyte
I wil yive him a fether-bed,
Rayed with golde, and right wel cled
In fyn blak satin doutremere,
And many a pilow, and every bere
255
Of clothe of Reynes, to slepe softe;
Him thar not nede to turnen ofte.
And I wol yive him al that falles
To a chambre; and al his halles
I wol do peynte with pure golde,
260
And tapite hem ful many folde
Of oo sute; this shal he have,
If I wiste wher were his cave,
If he can make me slepe sone,
As did the goddesse Alcione.
265
And thus this ilke god, Morpheus,
May winne of me mo feës thus
Than ever he wan; and to Iuno,
That is his goddesse, I shal so do,
I trow that she shal holde her payd.'
270
I hadde unneth that word y-sayd
Right thus as I have told hit yow,
That sodeynly, I niste how,
Swich a lust anoon me took
To slepe, that right upon my book
275
I fil aslepe, and therwith even

Me mette so inly swete a sweven,
So wonderful, that never yit
I trowe no man hadde the wit
To conne wel my sweven rede;
280
No, not Ioseph, withoute drede,
Of Egipte, he that redde so
The kinges meting Pharao,
No more than coude the leste of us;
Ne nat scarsly Macrobeus,
285
(He that wroot al thavisioun
That he mette, king Scipioun,
The noble man, the Affrican—
Swiche mervayles fortuned than)
I trowe, a-rede my dremes even.
290
Lo, thus hit was, this was my sweven.
The Dream.
Me thoughte thus:—that hit was May,
And in the dawning ther I lay,
Me mette thus, in my bed al naked:—
[I] loked forth, for I was waked
295
With smale foules a gret hepe,
That had affrayed me out of slepe
Through noyse and swetnesse of hir song;
And, as me mette, they sate among,
Upon my chambre-roof withoute,
300
Upon the tyles, al a-boute,
And songen, everich in his wyse,
The moste solempne servyse
By note, that ever man, I trowe,

Had herd; for som of hem song lowe,
305
Som hye, and al of oon acorde.
To telle shortly, at oo worde,
Was never y-herd so swete a steven,
But hit had be a thing of heven;—
So mery a soun, so swete entunes,
310
That certes, for the toune of Tewnes,
I nolde but I had herd hem singe,
For al my chambre gan to ringe
Through singing of hir armonye.
For instrument nor melodye
315
Was nowher herd yet half so swete,
Nor of acorde half so mete;
For ther was noon of hem that feyned
To singe, for ech of hem him peyned
To finde out mery crafty notes;
320
They ne spared not hir throtes.
And, sooth to seyn, my chambre was
Ful wel depeynted, and with glas
Were al the windowes wel y-glased,
Ful clere, and nat an hole y-crased,
325
That to beholde hit was gret Ioye.
For hoolly al the storie of Troye
Was in the glasing y-wroght thus,
Of Ector and king Priamus,
Of Achilles and Lamedon,
330
Of Medea and of Iason,
Of Paris, Eleyne, and Lavyne.
And alle the walles with colours fyne
Were peynted, bothe text and glose,

[Of] al the Romaunce of the Rose.
335
My windowes weren shet echon,
And through the glas the sunne shon
Upon my bed with brighte bemes,
With many glade gilden stremes;
And eek the welken was so fair,
340
Blew, bright, clere was the air,
And ful atempre, for sothe, hit was;
For nother cold nor hoot hit nas,
Ne in al the welken was a cloude.
And as I lay thus, wonder loude
345
Me thoughte I herde an hunte blowe
Tassaye his horn, and for to knowe
Whether hit were clere or hors of soune.
I herde goinge, up and doune,
Men, hors, houndes, and other thing;
350
And al men speken of hunting,
How they wolde slee the hert with strengthe,
And how the hert had, upon lengthe,
So moche embosed, I not now what.
Anon-right, whan I herde that,
355
How that they wolde on hunting goon,
I was right glad, and up anoon;
[I] took my hors, and forth I wente
Out of my chambre; I never stente
Til I com to the feld withoute.
360
Ther overtook I a gret route
Of huntes and eek of foresteres,
With many relayes and lymeres,
And hyed hem to the forest faste,

And I with hem;—so at the laste
365
I asked oon, ladde a lymere:—
Say, felow, who shal hunten here
Quod I; and he answerde ageyn,
Sir, themperour Octovien,'
Quod he, 'and is heer faste by.'
370
'A goddes halfe, in good tyme,' quod I,
Go we faste!' and gan to ryde.
Whan we came to the forest-syde,
Every man dide, right anoon,
As to hunting fil to doon.
375
The mayster-hunte anoon, fot-hoot,
With a gret horne blew three moot
At the uncoupling of his houndes.
Within a whyl the hert [y]-founde is,
Y-halowed, and rechased faste
380
Longe tyme; and at the laste,
This hert rused and stal away
Fro alle the houndes a prevy way.
The houndes had overshote hem alle,
And were on a defaute y-falle;
385
Therwith the hunte wonder faste
Blew a forloyn at the laste.
I was go walked fro my tree,
And as I wente, ther cam by me
A whelp, that fauned me as I stood,
390
That hadde y-folowed, and coude no good.
Hit com and creep to me as lowe,
Right as hit hadde me y-knowe,
Hild doun his heed and Ioyned his eres,

And leyde al smothe doun his heres.
395
I wolde han caught hit, and anoon
Hit fledde, and was fro me goon;
And I him folwed, and hit forth wente
Doun by a floury grene wente
Ful thikke of gras, ful softe and swete,
400
With floures fele, faire under fete,
And litel used, hit seemed thus;
For bothe Flora and Zephirus,
They two that make floures growe,
Had mad hir dwelling ther, I trowe;
405
For hit was, on to beholde,
As thogh the erthe envye wolde
To be gayer than the heven,
To have mo floures, swiche seven
As in the welken sterres be.
410
Hit had forgete the povertee
That winter, through his colde morwes,
Had mad hit suffren, and his sorwes;
Al was forgeten, and that was sene.
For al the wode was waxen grene,
415
Swetnesse of dewe had mad it waxe.
Hit is no need eek for to axe
Wher ther were many grene greves,
Or thikke of trees, so ful of leves;
And every tree stood by him-selve
420
Fro other wel ten foot or twelve.
So grete trees, so huge of strengthe,
Of fourty or fifty fadme lengthe,
Clene withoute bough or stikke,

Welcome to our website – the perfect destination for book lovers and
knowledge seekers. We believe that every book holds a new world,
offering opportunities for learning, discovery, and personal growth.
That’s why we are dedicated to bringing you a diverse collection of
books, ranging from classic literature and specialized publications to
self-development guides and children's books.
More than just a book-buying platform, we strive to be a bridge
connecting you with timeless cultural and intellectual values. With an
elegant, user-friendly interface and a smart search system, you can
quickly find the books that best suit your interests. Additionally,
our special promotions and home delivery services help you save time
and fully enjoy the joy of reading.
Join us on a journey of knowledge exploration, passion nurturing, and
personal growth every day!
ebookbell.com

Download full ebook of Heart Rate Variability Gernot Ernst instant download pdf

More Related Content

Similar to Download full ebook of Heart Rate Variability Gernot Ernst instant download pdf

Recently uploaded

Download full ebook of Heart Rate Variability Gernot Ernst instant download pdf