Functional Brain-Heart Interplay: From Physiology to Advanced Methodology of Signal Processing and Modeling

238 Pages·2021·11.204 MB·English

by  Vincenzo Catrambone, Gaetano Valenza

Vincenzo Catrambone
Gaetano Valenza
Functional
Brain-Heart
Interplay
From Physiology to Advanced
Methodology of Signal Processing and
Modeling
Functional Brain-Heart Interplay
Vincenzo Catrambone • Gaetano Valenza
Functional Brain-Heart
Interplay
From Physiology to Advanced Methodology
of Signal Processing and Modeling
VincenzoCatrambone GaetanoValenza
DepartmentofInformationEngineering DepartmentofInformationEngineering
UniversityofPisa,Bioengineering& UniversityofPisa,Bioengineering&
RoboticsResearchCenter“E.Piaggio” RoboticsResearchCenter“E.Piaggio”
Pisa,Italy Pisa,Italy
ISBN978-3-030-79933-5 ISBN978-3-030-79934-2 (eBook)
https://doi.org/10.1007/978-3-030-79934-2
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Foreword
For many years, cognitive neuroscience has been dominated by the computer
metaphor, in which the brain is regarded as the CPU, cerebral working memory
systems correspond to RAM, and the cerebral memory systems correspond to
hard disk or solid-state memory storage. According to this metaphor, all aspects
of cognition, emotions, memory, etc., are located in the brain, while the body’s
roleisratheranalogoustoperipherals,forexample,inputdevices(hands),sensors
(eye, skin, etc.), or power supply (heart). While the latter are important, they do
not directly impact on the CPU, that is, in the metaphor, they do not impact on
how/whatwethink,feel,ordecide.Contrastingthisview,aplenitudeofevidenceis
nowavailablewhichmaintainsthatthereisastrongmutualinteractionbetweenthe
bodyandthebrainwhichcanhaveaprofoundimpactonourmentalactivities.The
strongest case can be made for emotions, which very likely reflect mutual brain-
body interactions. However, the role of the body may go far beyond emotions, as
suggested, for example, in concepts such as embodied cognition. While we are
stillawaitingdefiniteanswersforthepreciseroleofbrain-bodyinteractionsinour
thinking,feeling,andacting,whatisurgentlyneededtoadvanceresearchonthese
topicsaretestable—ideallymathematicalorcomputational—models.
Thisbookbytwopioneersandoutstandingexpertsinthefieldoffersawonderful
summary and perspective on modeling brain-heart interactions (BHI). In addition
to reviewing all the important BHI modeling approaches, the authors also provide
intriguing summaries and perspectives on applications in fields such as emotion
research,psychiatricandneurologicaldisorders,sleep,andmotorcontrol.
AbetterunderstandingofBHIandbrain-bodyinteractionsingeneralwillhave
profoundimplications.Inbasicscience,itwillhelptoovercomeourcurrentbrain-
centric view towards a more integrated perspective, and may even get us closer to
solving some of the most enigmatic concepts/research topics such as the self and
consciousness.Furthermore—andofmorepracticalrelevance—itwillimpactmany
fieldsofmedicine,suchascardiology,neurology,psychiatry,andpsychosomatics.
In medicine, the notion of brain-body interaction transcends the classical medical
disciplines and calls for a more holistic view on the concept of disease. As a
physician(andneurologist),Iamconvincedthatnohumandiseaseisconfinedtoone
v
vi Foreword
organorbodypart,butalldiseasesaffectmind,brain,andbodysimultaneously.This
shouldbereflectedmoreinourresearchaswellasinourdailypracticalmedicine!
Whetheryouareanengineer,physicist,ormathematicianinterestedinapplying
your expertise to life sciences, or whether you are a biologist, psychologist,
neuroscientist,orphysician:Youwillbenefitfromreadingthisbook.
Director,DepartmentofNeurology,MaxPlanck ArnoVillringer
InstituteforHumanCognitiveandBrainSciences
Leipzig,Germany
Director,DepartmentofCognitiveNeurology
LeipzigUniversityHospital,Leipzig,Germany
ProfessorofCognitiveNeurology
LeipzigUniversity,Leipzig,Germany
Spokesperson,(national)MaxPlanckSchoolofCognition
Leipzig,Germany
Director,MindBrainInstitute,BerlinSchoolofMind
andBrain,Berlin,Germany
Preface
Would you assess the performance of a soccer player by looking at them playing
inthefieldcompletelyalone?Surelyyouwouldgetoverallinformationabouttheir
playing skills and state of health, but this can be far from the actual performance
evaluation that should be undertaken in a comprehensive manner, i.e. looking
at multiple players interacting together throughout the play time. This is what
many years ago we realized was going on in the majority of research and clinical
activities across multidisciplinary fields involving central and autonomic nervous
systems, which innervate all body organs. Biological systems like brain and heart
are “complex”, meaning that, due to the interaction of many sub-components, the
system as a whole demonstrates properties that the individual components acting
alonecannot.
Indeed,whileclinicalevidence pointstothefunctionalinterplaybetweenbrain
and body, a solid comprehensive data modelling/processing framework linking
the very different physiological dynamics, but bound to the very same systemic
biological responses despite time-scale differences, was difficult to find till a few
yearsago.
Throughthisbook,weaimtoprovidereadersinterestedinthequiteholisticand
timely research field of functional brain-heart interplay an overview on systemic
brain-heartphysiology,whichdrivesnewad-hocmathematics,mergingknowledge
fromcardiologyandneurologytouncovernewcomplexphysiologicaldynamicsin
amultivariate,continuous-in-timefashion.Whilethemethodologydescriptionhas
indeedatechnicalcut,thescientificbackground,results,anddiscussionatabrain-
heartlevelismeanttobedirectedtoanon-technicalaudience,too.
It goes without saying that brain and heart may interact in a wide range of
ways, including biochemical and electrical pathways that may be anatomically
or functionally connected. For example, we are aware that brain cells other than
neurons,suchasglialcells,arealsoinvolvedinthemaintenanceofcardiovascular
andrespiratoryhomeostasis.
Inthisbook,wealwaysreferto“functional”brain-heartinterplaytoincorporate
themacroscopicchangesthatmayconcurrentlybeobservedincomputationalbrain
and heartbeat series, regardless of their particular and specific anatomical origins.
vii
viii Preface
In the next chapters, the brain activity will mainly refer to the cortical electrical
activity of pyramidal neurons, as measured through electroencephalography, and
hemodynamicresponsesmeasuredthroughfunctionalmagneticresonanceimaging.
From the heart side, the focus will be on the autonomic control on heartbeat
dynamics, neglecting the many other cardiovascular functions that may not be
directlyrelatedtothesynergisticsympathetic-parasympatheticactivity.
Whileanexhaustivedescriptionofeachbrain-heart-relatedtopicwouldrequire
morethanabookperse,wearesurethatthisbookmayconstitutethebasisthrough
whichmanyinterestedscientistsandreaderswillgettoknowmoreaboutCNS-ANS
measurementsandformulatearenewedviewonneuro-/psycho-cardiologyandthe
extraordinarycomplexaetiologytherein.
Pisa,Italy VincenzoCatrambone
Pisa,Italy GaetanoValenza
March2021
Contents
PartI FundamentalsonFunctionalBrain–HeartInterplay(BHI)
1 BHIPhysiologyataGlance................................................. 3
1 AnatomicalandPhysiologicalBases.................................. 5
2 ExemplaryBHI-RelatedElicitations .................................. 11
3 BHI-RelatedPathologies............................................... 16
2 BHIEstimationMethodology .............................................. 21
1 GeneralAnalysisFramework.......................................... 22
1.1 SynchronizationLikelihood ..................................... 23
1.2 Coherence ........................................................ 24
1.3 MaximalInformationCoefficient ............................... 24
1.4 JointSymbolicAnalysis ......................................... 25
1.5 TimeDelayStability............................................. 26
1.6 ConvergentCrossMapping...................................... 28
1.7 InformationTransferandTransferEntropy..................... 29
1.8 GrangerCausality................................................ 32
1.9 NormalizedShort-TimePartialDirectedCoherence ........... 33
2 AdhocFunctionalBHIAnalysisFramework......................... 34
2.1 Heartbeat-EvokedPotentials..................................... 35
2.2 BHISyntheticDataGenerationModeling...................... 37
2.3 BivariatePoint-ProcessModeling............................... 41
2.4 BeyondTime–FrequencyDomain:ABHI-Tailored
MultifractalApproach ........................................... 44
2.5 NetworkPhysiology ............................................. 47
3 TaxonomyforaFunctionalBHIEstimation .......................... 48
PartII Applications
3 SympathovagalChanges .................................................... 53
1 ExperimentalDataset .................................................. 54
2 SignalPreprocessing ................................................... 54
ix
x Contents
3 Results .................................................................. 55
3.1 AMaximalInformationCoefficientAnalysis .................. 55
3.2 SyntheticDataGenerationModelAnalysis..................... 56
3.3 BivariatePoint-ProcessModelAnalysis........................ 63
3.4 MultifractalAnalysis............................................. 72
4 Emotion ....................................................................... 79
1 EmotionalImages ...................................................... 81
1.1 MaximalInformationCoefficientAnalysis..................... 82
1.2 GrangerCausalityAnalysis...................................... 89
2 EmotionalVideos....................................................... 106
5 PsychiatricandNeurologicalDisorders................................... 117
1 MildDepression........................................................ 117
2 Epilepsy................................................................. 126
3 Schizophrenia........................................................... 129
3.1 ANormalizedShort-TimePartialDirectedCoherence
Analysis........................................................... 133
3.2 AMultivariateTransferEntropyAnalysis...................... 135
6 Sleep........................................................................... 143
1 AnInformationTransferAnalysis..................................... 145
2 ATimeDelayStabilityAnalysis ...................................... 150
7 MotorControl................................................................ 155
1 ASyntheticDataGenerationModelAnalysis........................ 163
2 AMachineLearningApproach........................................ 166
AppendixA ....................................................................... 175
A.1 SmoothedPseudoWigner–VilleDistribution......................... 175
A.2 MultifractalsandNon-GaussianMultiscaleAnalysis ................ 176
A.3 Point-ProcessModelofHeartbeatDynamics......................... 177
A.4 EEGChannelMap ..................................................... 185
AppendixB ....................................................................... 189
B.1 QuantitativeResultsofBHIEstimations
intheMultifractalDomain............................................. 189
References......................................................................... 201
Index............................................................................... 229