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 ©TheEditor(s)(ifapplicable)andTheAuthor(s),underexclusivelicensetoSpringerNatureSwitzerland AG2021 Thisworkissubjecttocopyright.AllrightsaresolelyandexclusivelylicensedbythePublisher,whether thewholeorpartofthematerialisconcerned,specificallytherightsoftranslation,reprinting,reuse ofillustrations,recitation,broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,and transmissionorinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilar ordissimilarmethodologynowknownorhereafterdeveloped. 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ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland 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