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seizures
Arnaud Zalta, Jen-Cheng Hou, Monique Thonnat, Fabrice Bartolomei,
Benjamin Morillon, Aileen Mcgonigal
To cite this version:
Arnaud Zalta, Jen-Cheng Hou, Monique Thonnat, Fabrice Bartolomei, Benjamin Morillon, et al..
Neural correlates of rhythmic rocking in prefrontal seizures. Neurophysiologie Clinique/Clinical
Neu-rophysiology, Elsevier Masson, 2020, �10.1016/j.neucli.2020.07.003�. �hal-02937170�
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ORIGINAL
ARTICLE
Neural
correlates
of
rhythmic
rocking
in
prefrontal
seizures
Arnaud
Zalta
a,b,
Jen-Cheng
Hou
c,
Monique
Thonnat
c,
Fabrice
Bartolomei
a,d,
Benjamin
Morillon
a,1,
Aileen
McGonigal
a,d,1,∗aAixMarseilleUniversity,Inserm,INS,InstitutdeNeurosciencesdesSystèmes,Marseille,France
bAPHM,INSERM,InstNeurosciSyst,ServicedePharmacologieCliniqueetPharmacovigilance,AixMarseille University,13005Marseille,France
cINRIASophieAntipolis-Méditerranée,UniversitéNiceCôted’Azur,06902Valbonne,France dAP-HM,HôpitaldelaTimone,ServicedeNeurophysiologieClinique,13005Marseille,France
Received5June2020;accepted21July2020
KEYWORDS Seizure; Semiology; Oscillations; Rocking; Phaseamplitude coupling; Delta; gamma Abstract
Objectives.—Rhythmicbody rocking movementsmay occur inprefrontalepileptic seizures. Here,wecomparequantifiedtime-evolvingfrequencyofstereotypedrockingwithsignal anal-ysisofintracerebralelectroencephalographicdata.
Methods.—Inasinglepatient,prefrontalseizureswithrhythmicanteroposteriorbodyrocking recordedonstereoelectroencephalography(SEEG)wereanalyzedusingfastFouriertransform, time-frequencydecompositionandphaseamplitudecoupling,withregardstoquantifiedvideo data.Comparisonwasmadewithseizureswithoutrockinginthesamepatient,aswellasresting statedata.
Results.—Rockingmovementsinthedelta(∼1Hz)rangebeganafewsecondsafterSEEGonset oflowvoltagefastdischarge.Duringrockingmovements:(1)presenceofapeakofdeltaband activitywas visibleinbipolarmontage,withmaximalpower inepileptogenic zoneand cor-respondingtomeanrockingfrequency;(2)correlation, usingphaseamplitudecoupling,was shown betweenthephaseofthisdeltaactivityandhigh-gammapower intheepileptogenic zoneandtheanteriorcingulateregion.
Conclusions.—Here,deltarangerhythmicbodyrockingwasassociatedwithcorticaldelta oscil-latoryactivityandphase-coupledhigh-gammaenergy.Theseresultssuggestaneuralsignature during expressionofmotor semiology incorporatingbothtemporal featuresassociated with rhythmicmovementsandspatialfeaturesofseizuredischarge.
©2020ElsevierMassonSAS.Allrightsreserved.
∗Correspondingauthorat:ServicedeNeurophysiologieClinique,CHUTimone,AP-HM,Marseille,France.
E-mailaddress:aileen.mcgonigal@univ-amu.fr(A.McGonigal). 1 Theseauthorscontributedequallytothiswork.
https://doi.org/10.1016/j.neucli.2020.07.003
ARTICLE IN PRESS
2 A.Zaltaetal.
Introduction
Complex rhythmic movements seen in some epileptic seizuresinvolveautomatic motorbehaviorssuchas chew-ing or pedaling movements [26]. Such behaviors may be associated not only with epileptic seizures but also with sleepdisorders[15] or other neurologicalconditions[10], and have been conceptualized as being associated with centralpatterngenerators[26]likelyinvolvingsubcortical circuitry[3,18].Whenoccurringinthecontextofaseizure, these more complex patternsare generally not concomi-tantwithafocalseizuredischargeconfinedtoasinglebrain regionbutratheremergewhenseveralconnectedstructures withinassociativecortexareinvolvedbyearlypropagation of seizure discharge [2,5,8,18]. Not only anatomical con-straintsbutalsothetemporalcharacteristicsoftheseizure discharge(e.g.rhythmicity,frequency,time-lag,coherence betweenstructures)influenceclinicalexpression[5,8,18].
Body rockingoccurs fairlyrarely in prefrontal seizures
[6,14,24]andisobservedinvariousotherphysiologicaland pathologicalcontexts including autisticspectrum disorder (ASD) [16]. However, neural correlates of rhythmic body rockinginhumansareunknown.
We previously reported video quantification of antero-posteriorrhythmicrocking[12]asastereotypedexpression offrontalseizuresemiology[6,12,19].Here,weinvestigate neuralcorrelatesduringtheperiodofrocking,inapatient recordedonSEEG.Wewishedtoevaluatewhetherrhythmic neuralactivitycouldbeevidencedinrelationtothe rhyth-micbodymovements,andtodescribethetemporo-spatial relationbetweenseizure-andbodyrocking-basedactivities.
Methods
Clinicalcase
A 32-year-old right-handed woman presented pharma-coresistant frontal lobe epilepsy from the age of 18 years. Seizures consisted of abrupt onset of stereotyped hyperkinetic motor behavior characterized by rhythmic antero-posteriortruncalrockingmovements,duringwhich the patient was unresponsive. Neuroimaging wasnormal. Followingnon-invasivepresurgicalinvestigations,SEEGwas performed,duringwhichhabitualseizureswithrockingwere recorded.Thepatientalsopresentedsomeseizureswithout bodyrocking,characterizedbyhyperkineticbehaviormainly oflowerlimbswhilesheremainedlyingonthebed (consid-ered‘‘controlseizures’’forthepresentstudy).Allseizures hadsimilarpatternonseizureonsetonSEEG.Aspreviously reported,automated video analysisallowed characteriza-tionoftherhythmicbodymovements[12]andshowedmean rocking frequency that varied between 0.48 and 1.01Hz acrossallseizuresforthispatient
(Patient1,Seizures2and4inthepreviousstudy[12]). SEEG exploration in 2005 consisted of 7 orthogonally implantedelectrodes,with6exploringrightpremotorand prefrontal structures (see Fig. 1) and one contralateral electrodeinleftprefrontalcortex. AnalysisofSEEGdata, includingquantification of seizure onset with the Epilep-togenicityIndex[4]showedinitialorganizationofseizures (epileptogeniczone,EZ)predominantlyinvolvingright
dor-solateral prefrontal cortex (see Fig. 1); however, early involvementofcontralateraldorsolateralprefrontalcortex was also noted, as well as rapid spread of tonic dis-charge tomesial regions includinganterior cingulate and pre-supplementary motor area (pre-SMA). To complement visual analysis,the EpileptogenicityIndex[4]wasapplied toquantifyseizureonset.Thisisasemi-automaticmethod of quantifyingfastactivityat seizureonset,incorporating measures ofrapidityofdischargeandearlinessof appear-ance.ThisshowedmaximalvaluesinlateralcontactsofCR and FD (thus, predominantly right dorsolateral prefrontal cortex)(Fig.1A).Semiologyonsetoccurredaround2safter dischargeonset,atwhichtimeslowerrhythmicactivitywas visible.SubsequenttoSEEGexploration,cortectomy includ-ing right superior andmiddle frontal gyri wasperformed. Histopathologyshowednon-specificgliosis.Thepatienthad satisfactorysurgicaloutcomeat10years(ILAEclass2).
SEEGsignalanalysis
Atotalof4seizureswereanalyzedfromthebeginningtothe endofthesemiologycorrespondingtoclinicalseizures(two withrocking,called‘‘seizures1and2;twowithoutrocking, called ‘‘control seizures (seizures 3 and 4)’’ ) as well as resting backgroundactivity without pathologicalneuralor clinicalactivity(baselineperiod),withinthesamepatient. Methodologyconsistedofseveralsteps:
(1) Preprocessing.Dataanalysiswasperformedwith Brain-storm [25] and Matlab (The Mathworks). SEEG data associatedwithfourseizures (two seizures associated with rhythmic body rocking, called seizure 1 and 2 here;also,twocontrolseizureswithoutrocking,called seizure 3 and 4), as determined by a clinician were selected.Fourbaselineepochs,ofsimilardurationsto thefourseizures,butcorrespondingtoadatasegment from the interictal period while the patient was at rest, each obtained the same day asthe correspond-ingseizure,werealsoselected.Channelsthatpresented significantartefactduringtheseizureswerediscarded aftervisualinspectionofthesignal.Weestimatedthe focalneuralactivitybetweentwochannelsbyapplying abipolarmontageontheremainingneighboring chan-nels. Of note, all the analyses were done on all the implantedelectrodestoinvestigatethedynamicofthe neuralnetworksuspectedtobeinvolvedintheseizure. (2) FastFourier transform(FFT).AfastFourier transform wasappliedtothecoordinatesoftheheadmovements extractedfromthequantifiedvideo[11]andtothe neu-raldatatoestimatetheirrespectivepowerspectrumin thedeltarange(0.5−4Hz).
(3) Estimation of high-gamma power. A time-frequency decomposition of the neural signal was performed between60and150Hzinlogarithmic scale,by apply-ingatime-frequencywavelettransform,usingafamily ofcomplexMorletwavelets[centralfrequencyof1Hz, time resolution (FWMH) of 3s; hence, three cycles]. Wethen estimatedhigh-gamma powerindecimal log-arithmic units (in dB), and applied a grand-average, acrossfrequenciesandtime,toobtainaglobalestimate
Fig.1 A.SEEGtraceofatypicalseizurecharacterizedbyrocking.Semiologicalonsetoccurred2safteronsetoflowvoltagefast activity(bluearrow).LowerrightinsetshowsschematicrepresentationofSEEGelectrodesintherighthemisphere.Sixorthogonal electrodesexploredrightfrontallobe,reachingmedialstructures.ThereisalsoonecontralateralelectrodeFD’,symmetricwithFD (notshowninfigure).Theredovalrepresentsthezonemaximallyinvolvedbyseizureonset(electrodesFP,CR,FD)andtheyellow ovalrepresentsthezoneofseizurepropagation(electrodesSA,PMandCC).ThetoprightinsetshowsamapoftheEpileptogenicity Index[4](seetextforexplanation)forthisseizure,whichshowsmaximalvaluesatseizureonsetintheexternalcontactsofFD andCR.B,C:Selectedclinicalsemiologyandneuraltimecoursesofseizures1(left)and2(right).B.Amplitudeofbodyrocking movementextractedfromvideo.C.Amplitudeofneuralsignalforbipolarmontagedata(Forinterpretationofthereferencesto colourinthisfigurelegend,thereaderisreferredtothewebversionofthisarticle).
of high-gamma activity for the seizure and baseline epochs.
(4) Phase-amplitudecoupling(Pac).Inordertoinvestigate theinter-dependence between delta andhigh-gamma oscillations, we estimated thephase-amplitude cross-frequency coupling between the phase of the neural signal corresponding to the body rocking movement (∼1Hz)andthehigh-gamma amplitude[1,22], follow-ingthemethoddescribedinÖzkurtandSchnitzler[22].
This estimates co-fluctuations between low and high frequency neuralsignals andquantifiestheamount of high-gammaactivitymodulatedinphasewiththebody rockingmovement.Thesameprocedurewasappliedto seizureandbaselineepochs.
(5) Combining the two rocking seizures. Finally, in order to obtain an overall estimate of the seizure-related activity,wefirstcontrastedneuralindexes(either,FFT, high-gammapower,orPac)duringseizureandbaseline
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4 A.Zaltaetal.
Fig.2 Powerspectra(involtsforneuralsignal;arbitraryunitsforbodyrockingmovement)of(A)bodyrockingmovementsand (B)ofneuralactivityfrombipolarmontagedataforeachcontact,forseizures1(left)and2(right).C.Delta(∼1Hz)powerduring seizuresrelativetobaseline,extractedfromthebipolarmontagedata;pairedttestsagainstzero(Bonferronicorrectedwitha factor4):t(80)=5.83andt(80)=7.96forseizures1and2respectively;allp<0.01.D.Spatialdistributionofdeltapowercombined acrossthetwoseizures(involt2).Contactsareplottedforeachelectrodefollowingamedio-lateralgradient(frommedialtolateral: 1-14).Eachlineorpointcorrespondstoonecontact.
periods.Wethencombinedthetwoseizuresofsimilar nature (i.e.associated withrhythmic bodyrocking or not)bymultiplyingtheirrespectiveindexes,per chan-nel(i.e.,percontact).Thisallowedustohighlightthe channels forwhichneuralactivitywashighrelativeto baseline duringSeizures 1and 2.We alsoappliedthe samemethodtothetwocontrol(non-rocking)Seizures 3and4.
(6) Statistical procedure. Paired t tests, Bonferroni cor-rected with a factor 4, were performed at the level of individual electrode contacts (bipolar montage) betweenseizureandbaselineepochs.
Results
Bodyrockingmovement andtheneural signal forthe two seizurespresent a strong similarity(Fig.1 B,C)supported bythecomputationofpowerspectrumwhichrevealedthe modalfrequencyofthebodyrockingmovement (Fig.2A) andneural activity in the delta range(Fig. 2B) -1Hz for seizure1and0.9Hz forseizure2.Using bipolarmontage, weextractedtheneuralpowerat thepeakfrequencyand contrasted it from baseline periods (Fig. 2C). Across the
twoseizures(Fig.2D),externalcontactsofFP,CRandFD’ electrodes(exploringrightandleftdorsolateralprefrontal cortex)emerged.Thefirsttwocapturedneuralactivity situ-atedintheEZ,whileFD’issituatedintheearlypropagation zone.
We next investigated the relationship between body rhythmic movements and high-gamma neural activity (60−150Hz), which best approximates multi-unit activity
[23]. We computed the phase-amplitude coupling (PAC) between the phase of the delta (∼1Hz) activity and the amplitudeofthehigh-gammaactivity onthebipolar mon-tagedatacontrastedtobaselineperiods(Fig.3A).Weshow anoverallincreaseofdelta-gammacouplingduringseizures (paired t tests againstzero: t (80)=7.99 andt (80)=15.9 for seizures 1 and 2 respectively;all p<0.01). Combining thecouplingstrengthofthetwoseizures(relativeto base-line;seeMethods;Fig.3B)weobservedamaximalcoupling ininthedorsolateralprefrontalcortexcorrespondingtoEZ (wherealargedeltaactivitywasobserved)andinthemotor cingulateregion(BA24;CCelectrode).
Finally, we computed the overall high-gamma power relative to baseline to investigate whether the previous resultwasspecifictoahigh-gammaactivitylockedtobody rhythmicmovements.We observedan overall larger
high-Fig.3 A.Phase-amplitudecoupling(PAC),computedbetweenthephaseofdelta(∼1Hz)activityandhigh-gamma(60-150Hz) amplitude,extractedfrombipolarmontagedataandnormalizedtobaseline,forseizures1(left)and2(right).B.Spatialdistribution ofPACcombinedacrossthetwoseizures.SameconventionasFig.2C.Powerofhighgammaactivity(60-150Hz),indecibel(dB), extractedfromthebipolarmontagedataandnormalizedtobaseline,forseizures1(left)and2(right).D.Spatialdistributionof high-gammapowercombinedacrossthetwoseizures(indB2).SameconventionasFig.2.Eachlineorpointcorrespondstoone contact.
gammaactivityduringseizures(pairedttestsagainstzero:t (80)=26.4andt(80)=25.3forseizures1and2respectively; allp<0.01;Fig.3C).Combining theprofileofresponseof thetwoseizures(Fig.3D)weobservedamaximalresponse inthemostmedialcontactsofelectrodeCR,alsosituated in the early propagation zone, but in anterior cingulate gyrus (BA32), a regionnot reported in the previous anal-yses. These results indicate selective coupling between delta and high gamma activity that is notmerely related tonon-specific globalincrease in gammaactivity in these locations.
We appliedthe same analysis pipelineused for rhyth-micbodyrockingseizuresontwocontrolseizuresfromthe samepatient(Seizures 3and4).They werecharacterized by hyperkinetic motor behavior but did not present the body rocking movement semiology of the other seizures. As expected, we did not find a selective pattern of low-frequency activity in the neural time-course (Fig. 4A) or in the power spectrum(Fig. 4B). In particular, thepower spectrum ofbipolar montage data at 1Hz wasnot differ-entinthesecontrolseizuresthanbaselineactivity(paired t testsagainstzero : t(82) =-3.4, p<0.01and t (82)= -0.99,p>0.05forseizures3and4respectively;Fig.4C-D). Nosignificantdelta-high gammaphase-amplitudecoupling wasobservedneither(paired ttestsagainstzero:t (82)= -1.21andt(82)=0.62forseizures3and4respectively;all p>0.05;Fig. 5A-B),confirming the selectivityof the neu-ralactivity lockedtotherhythmicbodyrockingdescribed previously.Finally,weobservedthepresenceofsignificant high-gammaactivity inthetwocontrolseizurescompared tobaseline(paired ttestsagainstzero:t (82)=-11.2and
t(82)=14.5forseizures 3and4 respectively;allp<0.01;
Fig.5C)inBA32regionaspreviouslyobserved(Fig.5D).
Discussion
To our knowledge, this is the first study analyzing neu-ral correlates of rhythmic body rocking during epileptic seizures,associatingquantifiedvideoandintracerebralEEG data.Here,wedescribetwomaincharacteristicsofcortical activity associatedwith rhythmicbody rockingsemiology, compared toseizures without rocking movements and to interictal rest periods. First, using fast Fourier transform analysis(FFT),apeakofdeltabandactivity,maximalinEZ andearlypropagationzones,wasobservedduringrhythmic bodyictalrocking,correspondingtoquantifiedrocking fre-quency.Secondly, usingphase-amplitudecoupling[1],the phase of the clear delta peak was correlated with high-gamma(60−150Hz) activity, in EZand propagationzones includingmotorcingulateregions.Thus,aswellasbringing additionalevidence of the tightrelation between seizure onsetandpropagationzonesin both temporalandspatial aspects[11], ourdata highlight a clear temporal relation betweencorticalactivityandrhythmicityofmotorclinical expression.
Alimitationhere, apartfromthesmallnumberofdata (duetorarityofSEEGrecordingofthisclinicalpattern),is thepossibilityofan artefactualcausefor thedelta activ-ity,notablymovement artefactfromthe rhythmicrocking being transmitted via the SEEG cable, suggested by the similarityofamplitudeacrosselectrodecontacts.However,
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6 A.Zaltaetal.
Fig.4 A.Neural time coursesof thetwo controlseizures3(left)and 4(right),withoutbody rocking movementsemiology. Amplitudeofneuralsignalsforbipolarmontagedata.B.Powerspectraofneuralactivityfrombipolarmontagedataforthetwo controlseizures.C.Delta(∼1Hz)powerduringcontrolseizuresrelativetobaseline,extractedfromthebipolarmontagedata.D. Spatialdistributionofdeltapowercombinedacrossthetwocontrolseizures(involt2).SameconventionasinFig.2.Eachlineor pointcorrespondstoonecontact.
weinvestigatedthispossibilitybyusingabipolarmontage, consideredtoproducespatialfiltering,thusminimizing arte-factfromacommonsource[7];thesamedeltabandpeak persistedintheseconditions.Whileheadmovementwould be more likelyto introduce artefact in contacts close to theskull[13,20]andinawidespreaddistribution,maximal deltaactivitywasobservedinseizureonsetandpropagation zones, which included deeper cerebral contacts far from electrodeskullentrypoints;thetopographicaldistribution ofthiseffectthus alsotends toargueagainstan artefac-tualcause.Non-rockingseizuresin thesamepatientwere characterizedbyhyperkinetic, non-rhythmic bodyandleg movements;theseshowedsimilarseizureonsetpatternbut werenotassociatedwithvisible 1HZactivity ontheSEEG traceduringsemiologicalexpression.
Wealsoinvestigatedthedynamicsofhigh-gamma activ-ity,typicallythepredominantfrequencyrangeinneocortical seizures[5,27]. Highgammaband activity closely approx-imates multi-unit activity [23] and cannot be induced by cablemovements.Inallseizures(with(Fig.3)andwithout (Fig. 5C-D) body rocking semiology), high-gamma activ-itywas maximallypresent in the anteriorcingulate gyrus (BA32),possiblyrelatedtoitsimportantrolehereinseizure propagation.
Wenextevidenceda correlationbetween thephaseof deltabandpeakandtheamplitudeofhigh-gamma oscilla-tionsselectivelyduringtheperiodsofrhythmicrocking.This effectwasparticularlymarkedwithinelectrodecontactsin theEZ.Additionally,strongdelta-highgammacouplingwas observedintheelectrodeexploringtheBA24sectionofthe cingulategyrus. This portionofthe cingulatehasamajor role within the motor system, notably in terms of motor coordinationandselection[9,21].
Onepossibleexplanationof thetopographical distribu-tionofourresultscouldreflecttheusualevolution ofthe seizuredischargeasitspreads tocingulatemotorregions. Thiscouldhavearoleindrivingrockingbehaviorforexample byinductionofmulti-unitactivitybydeltaactivity,leading toactivation ordisinhibition ofan intrinsicneural oscilla-tor[17], perhaps involving thestriatal connectionsof the anteriorcingulate[9].
Established modelsof epilepsynetworks based on sig-nalanalysisfromintracerebralEEGdatahaveshown that, duringseizures,connectionsbetweenneuralgroups in dif-ferentanatomical structuresareabnormally selected and facilitated[5,29].Instudyingtheserelationsbetween neu-ralactivities, mostworktodateonepilepsynetworkshas focusedontheperiodofseizureonset[28];relativelyfew
Fig.5 A.Phase-amplitudecoupling(PAC),computedbetweenthephaseofdelta(∼1Hz)activityandhigh-gamma(60-150Hz) amplitude,extractedfrombipolarmontagedataandnormalizedtobaseline,forthetwocontrolseizures.B.Spatialdistribution ofPACcombinedacrossthetwoseizures.SameconventionasFig.2C.Powerofhighgammaactivity(60-150Hz),indecibel(dB), extractedfromthebipolarmontagedataandnormalizedtobaseline,forthetwocontrolseizures.D.Spatialdistributionof high-gammapowercombinedacrossthetwocontrolseizures(indB2).SameconventionasFig.2.Eachlineorpointcorrespondstoone contact.
works have investigated links to putative mechanisms of semiological production [18]. While firm conclusions can-notbedrawnfromthepresent workduetosmallnumber ofdata,ourresultssuggestthatcorrelatingquantifiedictal movement patternswithquantified cerebraldatais feasi-ble.Studyofa largerdatasetcouldhelptoshedlighton underlyingpathophysiologyofcomplexictalbehaviors.
Conflicts
of
interest
None.
Acknowledgements
This paper has been carried out within the Federation Hospitalo-Universitaire(FHU)EPINEXTthankstothesupport oftheA*MIDEXproject(ANR-11-IDEX-0001-02)fundedbythe ¨Investissementsd’Avenir¨FrenchGovernmentprogram man-agedby the French National Research Agency(ANR). The authors wishtothankChristian Bénar, Jean-MichelBadier andothermembersoftheDynamapteam,INS,Aix-Marseille University,forhelpfuldiscussion.
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