Localization of deep brain activity with scalp and subdural EEG

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NeuroImage

journalhomepage:www.elsevier.com/locate/neuroimage

Localization of deep brain activity with scalp and subdural EEG

Mansoureh Fahimi Hnazaee

, Benjamin Wittevrongel

, Elvira Khachatryan

, Arno Libert

, Evelien Carrette

, Ine Dauwe

, Alfred Meurs

, Paul Boon

, Dirk Van Roost

, Marc M. Van Hulle

aLaboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven, Belgium

bFaculty of Medicine and Health Sciences, Ghent University Hospital, Ghent, Belgium

a r t i c le i n f o

Keywords:

Joint EEG ECoG Depth electrode Source localization Quiet wakefulness Deep brain activity

a b s t r a ct

Towhatextentelectrocorticography(ECoG)andelectroencephalography(scalpEEG)differintheircapability tolocatesourcesofdeepbrainactivityisfarfromevident.ComparedtoEEG,thespatialresolutionandsignal- to-noiseratioofECoGissuperiorbutitsspatialcoverageismorerestricted,asisarguablythevolumeoftissue activityeffectivelymeasuredfrom.Moreover,scalpEEGstudiesareprovidingevidenceoflocatingactivityfrom deepsourcessuchasthehippocampususinghigh-densitysetupsduringquietwakefulness.Toaddressthisques- tion,werecordedamultimodaldatasetfrom4patientswithrefractoryepilepsyduringquietwakefulness.This datacomprisessimultaneousscalp,subduralanddepthEEGelectroderecordings.Thelatterwaslocatedinthe hippocampusorinsulaandprovideduswithour“groundtruth” forsourcelocalizationofdeepactivity.Weap- pliedindependentcomponentanalysis(ICA)forthepurposeofseparatingtheindependentsourcesintheta,alpha andbetafrequencybandactivity.Inallpatientssubdural-andscalpEEGcomponentswereobservedwhichhad asignificantzero-lagcorrelationwithoneormorecontactsofthedepthelectrodes.Subsequentdipolemodeling ofthecorrelatingcomponentsrevealeddipolelocationsthatweresignificantlyclosertothedepthelectrodes comparedtothedipolelocationofnon-correlatingcomponents.Thesefindingssupporttheideathatcomponents foundinbothrecordingmodalitiesoriginatefromneuralactivityincloseproximitytothedepthelectrodes.

Sourceslocalizedwithsubduralelectrodeswere~70%closertothedepthelectrodethansourceslocalizedwith EEGwithanabsoluteimprovementofaround~2cm.Inouropinion,thisisnotaconsiderableimprovementin sourcelocalizationaccuracygiventhat,forclinicalpurposes,ECoGelectrodeswereimplantedincloseproximity tothedepthelectrodes.Furthermore,theECoGgridattenuatesthescalpEEG,duetotheelectricallyisolating silasticsheetsinwhichtheECoGelectrodesareembedded.Ourresultsondipolemodelingshowthatthedeep sourcelocalizationaccuracyofscalpEEGiscomparabletothatofECoG.

SignificanceStatement

Deepandsubcorticalregionsplayanimportantroleinbrainfunction.However,asjointrecordingsatmultiple spatialscalestostudybrainfunctioninhumansarestillscarce,itisstillunresolvedtowhatextentECoGandEEG differintheircapabilitytolocatesourcesofdeepbrainactivity.Tothebestofourknowledge,thisisthefirststudy presentingadatasetofsimultaneouslyrecordedEEG,ECoGanddepthelectrodesinthehippocampusorinsula, withafocusonnon-epileptiformactivity(quietwakefulness).Furthermore,wearethefirststudytoprovide experimentalfindingsonthecomparisonofsourcelocalizationofdeepcorticalstructuresbetweeninvasiveand non-invasivebrainactivitymeasuredfromthecorticalsurface.

2. Introduction

Howaccuratelysource signalsfromdeep andsubcorticalregions can be localized using electrophysiological recordings from the hu- mancorticalsurfaceisstillunderdebate.Theuncertaintypartlystems fromthefactthatthese structureshaveadistinct neuronalarchitec- turewhichmaycausethemtoproduceweakersignalsincomparison

∗Correspondingauthor.

E-mailaddress:mansoureh.fahimihnazaee@kuleuven.be(M.FahimiHnazaee).

tocerebralstructures(Andersenetal.,2020,AttalandSchwartz,2013; daSilvaandLopes,2011).Moreover,comparedtocorticalactivity,the largerdistancetodeepstructuresattenuatestherecordedelectrodeac- tivity(Krishnaswamyetal., 2017).Recordingsfrom thecorticalsur- face are predominantlydoneusing non-invasive electrophysiological toolssuchasmagneto-andelectroencephalography((M)EEG).Forcer- tainclinicalpurposes,invasivecorticalrecordingsarealsodonewith

https://doi.org/10.1016/j.neuroimage.2020.117344

Received19February2020;Receivedinrevisedform27July2020;Accepted31August2020 Availableonline6September2020

1053-8119/© 2020TheAuthor(s).PublishedbyElsevierInc.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/)

electrocorticography(ECoG).ECoGhasaconsiderableadvantageover (M)EEGinlocatingproximalactivity,astherecordingsarenotspatially filteredor“blurred” bythecranium.However,ECoGgridsorstripstyp- icallyonlycoverarestrictedregionofthecorticalsurfacecomparedto thewholescalpcoverageof(M)EEG,whichisexpectedtoaffectlocal- izationaccuracyofmoredistalsources.Therefore,todate,itisunclear whetherECoGhasanedgeover(M)EEGwhenitcomestolocalizing sourcesignalsfromdeepandsubcorticalregions.

In(M)EEGstudies,high-densitysettingshavesuccessfullylocalized activitydirectlyrecordedfromthehippocampus,amygdala,thalamus andnucleusaccumbens(Pizzoetal.,2019,Seeberetal.,2019).Theim- portanceofthesetwofindingshasbeenemphasizedrecently(daSilva (daSilvaandLopes,2019))asitchallengestheassumptionthatactiv- ityfromsmallanddeep/subcorticalstructuresdoesnothavesufficient signal-to-noiserationtobereliablydetectedwithouttheneedforexces- siveaveraging(PuceandS.Hämäläinen,2017).Whenthegroundtruth isavailable,asisthecasewiththesestudies,byvirtueofdepthelec- trodes,sourceseparationandlocalizationtechniquescanbecorrectly assessedintheir abilitytogauge theactivityofthementioned deep structures.ThestudiesbyPizzoetal.andSeeberetal.arenotthefirst onesadvocatingthedetectabilityofsubcorticalstructuresin(M)EEG.In fact,therehassincelongbeenasteadyflowofeithertheoreticalorex- perimentalstudiestosupportthisclaim(Cebollaetal.,2016;Cosandier- rimélé etal.,2012;Dalyetal.,2019;Dumasetal.,2013;Gharibetal., 1995; Ruzichet al.,2019; Samuelsson etal., 2019; Scherg andVon Cramon,1985; Schoffelenetal., 2008;Tzovara etal., 2019).Simul- taneous(M)EEGanddeepelectroderecordings haveshown toshare remarkablysimilarproperties(DalalSarangetal.,2009,Dubarryetal., 2014, Litvaketal., 2010, Tonoyan etal., 2017),though these find- ingshavebeenfairlylimitedtoclinicalsettings(Koessleretal.,2015; Ramantanietal.,2016).EspeciallyofinteresttothisstudyisEEGand EEGsourcemodeling,whichrequiresamuchmorecomplexmodelcon- siderably affectedbythe conductivityproperties of thedifferent tis- suesofthehead(PuceandS.Hämäläinen,2017).Advancesinthelast decadesonthedetectabilityandlocalizationofsubcorticalanddeep structureshavegonehandinhandwithimprovementsinspatialreso- lutionofEEG,nowdowntomillimeter-scalewhenusinghigh-density settingsandinEEGsourcereconstructiontechniques(Grechetal.,2008, Marinazzoetal.,2019;Pascual-Marqui,1999).

Invasive measures of electrophysiological activity such as ECoG, by contrast,are hailedfor their superior spatialresolution, spectral bandwidthandsignal-to-noiseratio(SNR)comparedtoscalpelectrode recordings(Balletal.,2009).ThespatialdistributionofECoGpoten- tials is complex (Whitmer et al., 2010) and the presence of highly localized components (e.g. high-gamma band during a visual task (Wittevrongeletal.,2018))hasledresearcherstoclaimthatECoGis alocalsignal(DubeyXandSupratimRay,2019).Thislocalityprin- ciplepredictsthatonlysourcesdirectlyunderneathandwell-covered bythesubduralgridcanbereconstructedsuccessfully.Anadvantage ofhavingamorerestrictedvolumeofsensitivityisthatitreducesthe amountofsurroundingbackgroundactivitycapturedbytheelectrodes (Cosandier-rimélé etal.,2012).Therefore,addingmoresubduralgrids forthepurposeofsourcelocalizationmightevendecreaseSNRiftheex- tracontactsarenotcloseenoughtothesource.Somestudiesshowthe sourcelocalizationaccuracyof activitywithECoGdecreaseslinearly withthedistancefromtheelectrodes(Todaroetal.,2019,Zhangetal., 2008).However,studieshaveappliedsignalseparationtechniquesand observedthatsignalsfromsubduralgridsorstripsmayalsodetectactiv- ityfrommoredistalsources(Whitmeretal.,2010).Itshouldbenoted that, incontrast to(M)EEG,theusedlocalizationmethodsfor ECoG aretypicallybased onactivityfromasingleor asmallgroupofad- jacentcorticalelectrodes(Huiskamp,2002).Moreadvancedmethods forsourcereconstruction,suchasthedipoleequivalentanddistributed sourcemodels,arenotsystematicallyappliednoroptimizedforECoG sourcelocalizationpurposes(Pascarellaetal.,2016),despiteevidence ofincreasedmodelaccuracy((Dümpelmannetal.,2009);Oostenveld

Fig.1.Schematicoverviewofthestudy.Deepandsuperficialarelocatedat locations(1)and(2),respectively.Thecolorbarsindicatethemeasurement strengthofthesourceactivitywhenmeasuredattheoriginofthesource(maxi- mumstrength)andwithECoGorEEGelectrodes.Lightblueanddarkbluerep- resentthemeasuredstrengthfordeepandsuperficialsources,respectively.The measurementofdeepandsuperficialsourcesareattenuatedatbothsubdural andscalplevelbuttoadifferentextent.Fromaperspectiveofthescalp(EEG), attenuationislikelysostrongthattheSNRfordeepandsuperficialsourcesdo notdifferasmuchastheydofromasubduralperspective(ECoG).Thiscould partiallyexplainwhysourcelocalizationaccuracyofdeepsourceswithECoG iscomparablewiththatofEEG(seediscussion).Notethatonlythelevelofat- tenuationisrelevant,nottheextentofthespreadorlocationoftheobserved activity.

and(OostenveldandF.Oostendorp,2002;Todaroetal.,2019))andsig- nificantimprovementsindeepsourceidentification(Choetal.,2011).

ToassesshowinpracticeEEGandECoGcompareintermsofdeep sourcelocalizationrequiressimultaneousrecordingsofinvasive,non- invasivecorticalanddeepactivity.Fig.1givesaschematicoverview of such a study. Simultaneous invasive and non-invasive recordings toisolate thecontributions of theunderlying neuralactivitytoEEG havebeenprimarilystudiedinnonhumanprimates(Musalletal.,2014; Snyderetal.,2018).Buttheseresultsdonotnecessarilygeneralizeto humandataasthepropertiesoftheskull,shapeandcancelationproper- tiesofthecorticalandsubcorticalstructuresmaydiffersubstantially.In humanstudies,simultaneousrecordingshavebeenperformedinclinical settingstodeterminetheamplitudeandextentofcorticalactivationthat determinesthepresenceofcorticalspikesinscalpEEG(Abrahamand AjmoneMarsan,1958.Cosandier-rimélé etal.,2012.Ramantanietal., 2016). Outside of theclinical context, humanstudies have founda highcorrelationbetween ECoGandEEGforagiventask(Balletal., 2008.Haufeetal.,2018),althoughthesestudiesdidnotconsidersi- multaneously recordedECoG andEEG asitis not without obstacles (Dubarryetal.,2014).Hence,astudycomparingsourcelocalizationof bothmodalitieswithinthesamesubjectwouldbeofgreatsignificance tothefield(NunezPauletal.,2019).

Tofill thisgap, we recordedelectrophysiological activityfrom 4 patientsduringquiescentwakefulnesssimultaneouslyfromdepthelec- trodesimplantedinthehippocampusorinsula,subduralgridscovering thecorticalsurfaceclosesttothesedepthelectrodesandscalpEEGelec- trodes.Werecordedthesepatientsduringquiescentwakefulnessasa focusonnon-epileptiformelectrophysiologicalactivityinhumanstud- iesoutsidethecontextoftask-relatedresponsesisstillrelativelyscarce (Frauscheretal.,2018).SourceseparationusingICA wasperformed separatelyonthescalp-andsubduralelectrodes.Severalstudiessup- portthenotionthatindependentcomponentsofEEGcorrespondtoan equivalentdipole,i.e.amaximallyindependentcomponentrepresents astationarysource(Delormeetal.,2012).Additionally,theuseofICA

Fig.2. Blockdiagramofthepipelineusedto investigatesourcelocalizationaccuracywithin andbetweenmodalities.

forintracranialdatahasbeenstudied,whereitwasalsoshownthatsev- eralICprojectionsareconsistentwithsourcesfromsinglebrainregions (Whitmeretal.,2010).Basedonthesestudies,weassumedthattheto- pographicmapofeachsubduralorscalpICcomponentcorrespondsto asingledipoleandperformeddipolemodelingtolocatethegenerator ofeachofthesecomponenttopographies.Thedistancebetweenthees- timatedgeneratorandthedepthelectrodeswascomputed.Inthisway, wewereabletoevaluateandcomparethesourcereconstructionofthe scalp-andsubduralelectrodes,giventhesamedeepsourceactivityas identifiedbythedepthelectrodes(seeFig.1).

3. Materialsandmethods

Fig.2showsanoverviewofthepipelineusedinourstudywhich consistsofseveralsteps.

3.1. Participants

Werecordedsimultaneousdepthelectrode,ECoGand(scalp)EEG from4patients(2females,averageage41.5ystd=20y,2left-handed) withdrug-resistantfocalepilepsyandundergoingpre-surgicalclinical assessment.Allpatientshadnormalvisionandnormallevelsofcon- sciousness.Thestudywasconductedaccordingtothecurrentversion ofthedeclarationofHelsinki,followingethicalapprovalfromGhent UniversityHospital’sEthicsCommittee.Allpatientsgavetheirwritten informedconsentbeforeparticipatinginthestudy.

3.2. Dataacquisition

EEGwasrecordedfrom27activeelectrodesattachedtothescalp accordingtothe10-20internationalsystem. Inadditiontothescalp

electrodes,patientshadbeenimplantedwithbothdepthandsubdural platinumelectrodesembeddedinsilastic(Ad-Tech,USA)forinvasive videoEEGmonitoringatGhentUniversityHospital.Forthesubdural grids,contactdiameterwas4mmwithanexposureof2.3mmdiame- terandacenter-to-centerdistanceof10mm;thedepthelectrodeshad 6or8contactsperelectrodewithcontactsizeof2.4/1.1mm (over- alllength/diameter)and4mmcenter-to-centerdistance.Allrecordings weredigitizedatasamplingrateof256Hz(exceptforpatientP3,where itwas1024Hz)usinganSDLTM64Express(Micromed,Italy)medi- callycertifieddevice.Thenumberandlocationofthesubduralgrids anddepthelectrodesforeachpatientarelistedintableS1andfigureS1 ofthesupplementarymaterialsection.Thetablealsoliststhepatients’

demographics.

3.3. Experimentalprocedure

Forthisstudy,werecordedeachpatient’sspontaneousactivitywith eyesopenfor3minuteswhiletheyfixatedacross-hairpresentedonan LCDscreenatadistanceofapproximately60cm.Patientsweresitting uprightintheirhospitalbeds.

3.4. Localizationofsubduralanddepthelectrodes

Thepre-implantationMRIscanofthepatientwasusedforcortical reconstructionandvolumetricsegmentationusingtheFreesurferimage analysissuite((DaleAndersetal.,1999)version6.0,seehttp://surfer.

nmr.mgh.harvard.edu/).TheFreesurferoutputandMRIscanwerethen loaded intoBrainstorm(Tadeletal.,2011),wheretheMRIwasthen co-registeredwiththepost-implantationCTscanusingtheSPM12ex- tension(https://www.fil.ion.ucl.ac.uk/spm/software/spm12/).Theco- ordinatesoftheimplantedsubduralanddepthelectrodeswereobtained

byvisualinspectionandmappedontothecorticalsurfacetoaccountfor possiblepost-implantationtissueshifting.Theresultsof theMRIseg- mentationwerefurtherusedtocreatetheheadmodelfordipolemod- eling(seethesectionondipolemodeling).

3.5. Pre-processing

TherawECoG,depthelectrodeandEEGrecordingswerefirstin- spectedforbadchannels.Inthecaseofsubduralanddepthrecording, badchannelswereidentifiedbyaspecializedepileptologist(co-author AM)whomarked,inadditiontotheelectrodes,alsothetimeintervals duringwhichtherecordingsexhibited frequentorcontinuousabnor- malactivity(interictalorictalactivityandabnormalslowing).These electrodesandtimeintervalswereexcludedfromourstudyaswellas thecorrespondingtimeintervalsfromtheEEGrecordings.Inprinciple, wecouldinvestigate sourcereconstructionaccuracyof theabnormal activitytoo,butwedecidedtoexcludeitaswewantedtheresultsto berelevantforhealthysubjectswithnormalbrainactivity.Addition- ally,depthelectrodeswerecheckedfortheiranatomicallocationusing Brainstormandwhenelectrodecontactswereoutsidethedeepstruc- tures(hippocampusfor3patients,hippocampus andinsulafor1pa- tient),theywerediscardedfromfurtheranalysis.Thenoisyelectrodes inEEG wereidentifiedusingthemanualrejectfunctionin FieldTrip (Oostenveldetal.,2011).Thedatawasinitiallyfilteredusingaband- passfilterbetween1-60Hzandre-referencedofflineusingacommon averagereference(CAR)peracquisitionmodality.Forthedepthelec- trodedata,weadditionallyre-referencedourrecordingstobipolarones toinvestigate theimpactofdepthelectrodeset-uponourresults,as bipolarrecordingsareassumedtobelesssensitivetovolumeconduc- tion,thus,allowingforamoreprecisespatiallocalizationoftransient events(Pizzoetal.,2019).Thebipolarsetupconsistsofsubtractingthe recordingofallpairsofnon-rejectedconsecutivecontactswithineach electrode(Dubarryetal.,2014).Afterthat,therecordingswerecutinto overlappingtimewindows(epochs),shiftedby2sec.Thisresultedinan averageof67,59,51and46(std=22.1,24.8,27.3and27.9)epochsfor windowlengthsof5,10,15and20seconds,respectively.Thewhole pipelineanalysisisrepeatedforeachwindowlength.

3.6. CAandcorrelation

Independentcomponentanalysis(ICA)wasperformedontheECoG andEEG data for each patient separately, using theIcasso package (Himbergetal.,2004)implementedinFieldTrip.Icassofindsmorere- liablecomponentsthanthoseof asinglerunofanICAalgorithmby rerunningtheFastICAalgorithmseveraltimes(“iterations”)butwith slightlydifferentinitialconditionsandvisualizingtheclusteringstruc- tureoftheobtainedcomponentsperiterationinsignalspace(usinga symmetricapproachandaccountingforGaussiannon-linearity).Inour case,weranthealgorithmfor100iterations. Ineachiteration,Fas- tICAwasperformedontheartifact-freeepochsinconcatenatedformat.

Wehadsufficientdatatoperformtheanalysissince,afterexclusionof badtimeintervals,weendedupwithanaverageof41,601datapoints, andthenumberofelectrodesrangedfrom15-52evenintheworstcase theratioofdatapointstoelectrodeswasstillatleast15(Delormeand Makeig,2004).AsthenumberofICsisequaltothenumberofinput channels,therefore,there weretypicallymoreICs forECoGthanfor EEG.

AfterICAanalysis,theresultingICsforbothECoGandEEG,inaddi- tiontothedatafromthedepthelectrodes,werebandpassfilteredusing atwo-passButterworthfilteroforder4inthreefrequencybands,theta (4-8Hz),alpha(8-12Hz),andbeta(12-28Hz).Thesewerechosenas theyhavebeenshowntocorrespondtothemostdominantfrequencies observedinresting-stateECoG(GroppeDavidetal.,2013).Foreachof thesefrequencybands,weobtainedthepowerenvelopeofthesignal usingtheHilbert transform.Thepower envelopefor thedepthelec- trodecontactswascalculatedinthesameway.Next,wecalculatedthe

Pearsoncorrelationbetweeneachoutputcomponentandalldepthelec- trodecontactsforallepochs,resultinginatotalofcomponents×depth electrodecontacts ×epochscorrelationvaluesforeachfrequencyband andpatient.Asidefromcorrelationanalysisbetweenthedepthelectrode contactsandindependentcomponentsoftheECoGandEEG,aprelim- inarycorrelationanalysiswasalsoperformedbetweendepthelectrode contactsandthepowerenvelopeoftheoriginaltimeseriesoftheECoG andEEGineachoftheabovementionedfrequencybands(withoutper- formingICA).

3.7. Dipolemodeling

Several studies support thenotion that independent components of EEG correspond to an equivalent dipole (Delorme et al., 2012).

Therefore we will assume that thetopographic map of subdural or scalpICcomponentcorresponds toasingledipole(providedthatthe goodness-of-fit is sufficiently high, see further) and perform dipole modelingonallcomponentsusingthedipolemodelingfunctionpro- vided by theBrainstormtoolbox. Inthisfunction, the forwardsolu- tionisestimatedusingarealisticthree-layerheadmodel(OpenMEEG BEM) werethesource spacewasconstrained tothewhole MRIvol- umewith15000verticesandrelativeconductivitiesof1,0.0125,1for thescalp,skull,andbrainlayers,respectively(Gramfortetal.,2010).

Even thoughtheBrainstormtoolboxallowsfor amixed headmodel whichincludesdeepandsubcorticalstructures,wedidnotoptforthis method asdipolemodelingis notavailablefor amixed headmodel of ECoGdata. SeparateheadmodelswerecreatedfortheECoG and EEGdata,usingtheindividualMRIanatomyofeachpatient(seesec- tiononlocalizationofsubduralanddepthelectrodes).Whenperform- ingdipolemodelingusingBrainstorm,adipolescanningmapis pro- ducedthatrepresentstheabilityof thedipoletoexplaintherecord- ings.Thenoisecovariancematrixwas setastheidentitymatrixand the medianeigenvalueused fornoisecovariance regularization.The subsequentdipolescanningroutine determinesthefinallocationand orientationofthebestfittingdipole(onedipoleperIC).Ofeach ob- taineddipole,agoodnessoffitisreturnedindicatingwhatpercentage ofthetotalvarianceisexplainedbythemodelvariance.Anotheroutput is“performance”,thesquarerootofthechi-squaresummingoverthe degreesoffreedom.Thisvalueissimilartoaz-scoring,therefore,any performancesubstantiallylarger than5maybe thoughtof assignif- icant (https://neuroimage.usc.edu/brainstorm/Tutorials/TutDipScan).

Inouranalysis,alldipoleswithaperformancebelow100werediscarded andourstatisticalanalysisperformedfordipoleswithagoodnessoffit of75%orabove,assourceswithlowergoodnessoffitwereconsidered asinconclusiveforsingledipolefit(Pizzoetal.,2019).Differentthresh- oldsofgoodness-of-fitforthedipoleswereevaluatedandreportedinthe supplementarytableS6.

Weperformeddipolemodelingandscanningforallresultingcompo- nentsofbothECoGandEEG.Wedividedallresultingdipolesintotwo groups;dipolesthatcorrespondtoanindependentcomponent,exhibit- ingasignificantcorrelationwithadepthelectrodecontactandthose thatdon’t. Wewillfurtherrefertothese asthecorrelatingandnon- correlatingdipoles.

3.8. Statisticalanalysis

Correlationswereassessedforsignificancewhichismaximalatzero lagusingasurrogatedataset.Thesurrogatedatasetwasproducedby keepingtheoriginalorderoftheepochsinthefirstgroup(theepochsof thedepthelectrodecontacts)andarandompermutationoftheorderof theepochsinthesecondgroup(theepochsoftheEEGorECoGcompo- nents,Matlab’srandpermfunction).Bydoingthisonetime,weobtained asurrogatedatasetwiththesamesizeastheoriginaldataset.Correla- tionvalueswerethencalculatedforboththesurrogateandtheoriginal dataset.Aone-sidednonparametricpermutationtestwith1000permu- tationsconfirmeda significantlylargervaluefortherealcorrelation

valuescomparedtothesurrogateones.Thecross-correlationbetween componentsanddepthelectrodecontactsthatshowedsignificantcorre- lationwasfurtherevaluatedbytestingwhethercross-correlationvalues weremaximumatzero-lag,asamaximumatalagdifferentfromzero wouldprobablyindicateaphase-delayedconnectionratherthanvol- umeconduction,therefore,thesesignificantvalueswerediscardedfrom furtheranalysis.Anexampleofthecross-correlationfunctionbetween depthelectrodecontactandECoG/EEGcomponentsforonepatientcan befoundinsupplementaryfigureS2.Finally,p-valueswerecorrected formultiplecomparisonsusingthefalsediscoveryrate(FDR)correction forthenumberofcomponents.

Toassesstheaccuracyofsourcelocalization,weestimatedthedis- tance betweentheindependentcomponentsandthe depthelectrode contactswithwhichtheywerecorrelated.Thisistermedinthestudy

“sourcelocalizationaccuracy,” asourhypothesis isthatindependent componentscorrelatingwithacertaindepthelectrodecontactareas- sociatedwithadipolelocatedincloseproximitytothatcontact.Asa control,wealsoestimatedtheaverageEuclideandistancebetweenthe non-correlatingcomponentsandalldepthelectrodecontactsofagiven patient.Giventhatweassumethesenon-correlatingcomponentstobe associatedwithdipoles,locatedinvariousplacesinthebrainthatare notlikelytobeclosertothedepthelectrodecontactsthanthecorre- latingcomponents,asignificantdifferenceinlocalizationaccuracyfor correlatingandnon-correlatingdipoleswouldconfirmourhypothesis.

Forthestatisticalanalysisinthiscase,weusedMATLABtoperforma linearmixedeffectanalysisofsourcelocalizationaccuracy(Gelmanand Hill,2006).WedidthisforECoGdataandEEGdataseparately.Asa fixedeffect, weusedcorrelationandasrandomeffects,wetook fre- quencyband,patients,modality,epochlengthanddepthelectroderef- erencingmontage:

𝑠𝑜𝑢𝑟𝑐𝑒𝑙𝑜𝑐𝑎𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛𝑎𝑐𝑐𝑢𝑟𝑎𝑐𝑦∼𝑐𝑜𝑟𝑟𝑒𝑙𝑎𝑡𝑖𝑜𝑛+(1𝑝𝑎𝑡𝑖𝑒𝑛𝑡)

+(1𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦𝑏𝑎𝑛𝑑)+(1|𝑒𝑝𝑜𝑐ℎ𝑙𝑒𝑛𝑔𝑡ℎ)+ (1𝑚𝑜𝑛𝑡𝑎𝑔𝑒) (1)

Finally,tocomparethesourcelocalizationaccuraciesofEEGand ECoGweusedanotherlinearmixedeffectmodeltocompareaccuracy onlybetweencorrelatingdipolesofeachmodality.Inthismodel,we took as fixed effect modality(EEG or ECoG)and asrandom effects frequencyband,patient,epochlengthanddepthelectrodereferencing montage:

𝑠𝑜𝑢𝑟𝑐𝑒𝑙𝑜𝑐𝑎𝑙𝑖𝑧𝑎𝑡𝑖𝑜𝑛𝑎𝑐𝑐𝑢𝑟𝑎𝑐𝑦∼𝑚𝑜𝑑𝑎𝑙𝑖𝑡𝑦+(1𝑝𝑎𝑡𝑖𝑒𝑛𝑡)

+(1𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦𝑏𝑎𝑛𝑑)+(1𝑒𝑝𝑜𝑐ℎ𝑙𝑒𝑛𝑔𝑡ℎ)+(1𝑚𝑜𝑛𝑡𝑎𝑔𝑒) (2)

Furthermore,asimilarpipelineanalysiswasperformedsimilarlyto theonedescribedabove,wherebandpassfilteringintothedifferentfre- quencybandswasomittedanddatawasfilteredbetween1-40Hz.This pipelineandcorrespondingresultscanbefoundinthesupplementary material,tableS7andtheaccompanyingtext(eq.S1andeqS2).

4. Results

4.1. ActivityfromdeepsourcescontributetoECoGandEEGsignals

Ourfirstgoalwastoverifywhetheractivityfromdeepsourcesspread tothecorticalsurfaceandscalp.Correlationanalysisrevealsaweakbut significant(rho_average=0.13(std=0.085),p_average=0.017forallsubjects andfrequencybands, bothECoG andEEG)dependencebetween the depthelectrodesandseveralsubduralandscalpcontacts.Thecorrela- tionissignificantandpeaksatzero-lag,indicatingthattherelationship isnotduetoactivetransmissioninneuralpathways.Fig.3showsthe zero-lagcorrelationsforasinglepatient(patientP2)inthethetarange, for15secondlongepochs(rho=0.18,p=0.0039adjustedformultiple comparisonsusingFDRcorrection)whenusingacommonaverageref- erence.Correlationvaluesinthethetaandalphabandareonaverage twiceaslargeasinthebetaband,forbothECoGandEEG.Table1shows

Fig.3. Zero-lagcorrelationforeachofthedepthelectrodecontactsofpatient P2inthetabandwithECoG(leftcolumn,left),andEEG(rightcolumn,right) sensors.Electrodeswithsignificantcorrelation(FDRcorrected)aremarkedin green.

Table1.

AveragecorrelationvalueofEEG/ECoGtimeserieswithdepthelectrodecon- tactsacrosssubjectsperfrequencyband,forECoGandEEG.P-valuesaread- justedformultiplecomparisonsusingFDRcorrection.

Rho (p, FDR corrected) theta alpha beta ECoG 0.27 (p = 0.011) 0.16 (p = 0.015) 0.09 (p = 0.02) EEG 0.16 (p = 0.010) 0.12 (p = 0.020) 0.08 (p = 0.023)

theaveragecorrelationacrosssubjects.Additionally,TableS2insup- plementarymaterialshowsthecorrelationforeachpatientseparately.

ThistableshowsahighercorrelationvalueforP4comparedtoother patients,whichmayhavetodowiththefactthatP4istheonlypatient whereECoGcontactscoverbothhemispheres.

AseachEEGandECoGelectrodecapturesamixtureofsignalsorigi- natingfromdifferentsources,weappliedICAinanefforttosinglethem

Fig.4.CorrelationvaluesforECoGandEEGindifferentfrequencybandsforpatient2.Significantvaluesaremarkedby“+” (p-valuesareFDRcorrectedformultiple comparisons).

out(individualsourcecontributionsarefurthertermed‘components’).

WeperformedtheICAanalysisasdescribedinMaterialsandMethods andFig.2.Inordertoinvestigatetheeffectofdifferentreferencesfor thedepthelectrodes,weanalyzedourdatausingboththecommonav- erageandbipolarre-referencing(seethesectiononpre-processingfora discussion).Whenusinganaveragereference,acorrelationanalysisof theobtainedcomponentswithrespecttothe(non-decomposed)depth electrodesignalsreveals,forallpatients,componentsthatsignificantly correlatewithanaverageof1.8and2.8depthelectrodecontactsforthe decomposedscalp-andsubduralEEG,respectively(forabipolarrefer- encemontage,thesevaluescorrespondto1.3and1.9,respectively).By contrast,asingledepthelectrodecontactusuallycorrelatedwithanav- erageof2.2and6independentcomponentsforscalpandsubduralEEG, respectively(bipolar:2.2and5.8).Ahighnumberofsubduralindepen- dentcomponentsareassociatedwiththesamedepthelectrodecontact.

Thisissimilartowhatwasobservedinpreviousstudies(Whitmeretal., 2010).There,ICAanalysisofECoGdatarevealedmultiplecomponents thatcouldbeclinicallyidentifiedasexhibitingfrontalintermittentdelta activity,therefore,thepathologicalbrainsignalcouldberepresentedby multipleindependentcomponents.Inourcase,itcouldbeexplainedby thefactthatdepthelectrodecontactsrecordsignalsthatareacombina- tionofsurroundingactivity.Furthermore,inourstudyonaverage24%

ofthescalp-and39%ofsubduralcomponentshadasignificantcorre- lationwithagivendepthelectrodecontact(bipolar:25%and37.6%).

Likewise,48%and76%ofthetotalnumberofdepthelectrodecontacts weresignificantlycorrelatedwithagivencomponent(bipolar:46.9%

and62.5%).Adetailedlistspecificforeachfrequencybandandepoch lengthisgiveninsupplementary tableS4(andforthesameanalysis whenusingbipolarreferencemontageintableS5).Interestingtonote hereisthat,therewasnoobservedrelationshipbetweenthenumber ofdepthelectrodecontactscorrelatingwithasingleICandthemedian distancebetweendepthelectrodecontactsandsubduralelectrodesin thepatients(seealsoTable3).Theabove-mentionedresultsarepre- sentedonasinglesubjectlevelasfollows:Fig.4showsforpatientP2 significantcorrelationsbetweenindependentcomponentsofECoGand

EEGanddepthelectrodecontactactivityinthethetabandwhentaking epoch lengthsof15seconds.Thefiguresfortheotherpatientsalong withthoseforthebipolarreferencecanbefoundinsupplementaryma- terialfigureS3.Anaverageofthesignificantcorrelationvaluesandtheir varianceforeachpatientcanalsobefoundinsupplementarytableS3.

4.2. Sourcesaremoreaccuratelylocalizedfromsubduralthanfromscalp electrodes

Each ICA component is believed tooriginate from anindividual sourceinthebrain(Delormeetal.,2012),seematerialsandmethods section dipolemodelingforadiscussion).Toidentifythelocationof thissource,eachICAcomponentwassubjectedtoasourcelocalization analysis.Afterdipolefitting,dipoleswithagoodnessoffitabove75%

werefurtheranalyzedintermsofsourcelocalizationaccuracy(asde- finedinmaterialsandmethods).Forasinglesubject,werepresentthe resultsasfollows:Fig.5showstheposition,topographyandtimecourse oftheindependentcomponentanalysisforP2inthethetaband,forthe threeofthedipolesthathadthebestgoodnessoffit.Furtherinforma- tiononthecorrelationvaluesandaccuracyofsourcelocalizationfor thesespecificdipolescanbefoundinTable2.Itshouldbenotedthat wealsolookedintothequalityoftheICmapfortheECoGgrid.Accord- ingtoWhitmeretal.(2010),IC mapscanbeclassifiedas“focal”,or

“diffuse” basedonhowtheICprojectstotheelectrodes.Aprojectionto twoelectrodesorlessisconsideredtobe“focal”,whereasaprojectionto morethantwocontiguouselectrodesisclassifiedas“diffuse”.Basedon thisdefinition,dipole1and2fortheECoGcorrespondtodiffusemaps, astheybothprojecttothreecontiguouselectrodes,whereasdipole3 projectsto2electrodesandis,therefore,afocalmap.Inadditiontothe ECoGandEEGdata,thelocationofthedepthelectrodesandtheirtime courseinthethetabandforthesamepatientisshowninFig.6.Asimi- laranalysisforthetheta,alphaandbetafrequencybandsofallsubjects canbefoundinfigureS4ofthesupplementarymaterial.

Thesourcelocalizationaccuracyonpopulation-level,forallepoch lengths,frequencybandsandtypesofreferencewasstatisticalanalyzed

Fig.5.Locationofthethreedipoleswiththe bestgoodnessoffitinthethetabandforpa- tient2, ford) ECoG andEEG in a)sagittal view,b)axialview,c)coronalview.d)topog- raphyofindependentcomponents,ande,f,g) 1secondtimecourseofindependentcompo- nents 1,2 and3forrespectively ECoG and scalpEEG (shownin blue),withcorrelating timecourses ofthe depthelectrodecontacts (shownindashedred).Unitsforamplitudeand timeaxisareshownine)ontheleft.

usingalinearmixed-effectmodelasdescribedinEqs.1and2.Visualin- spectionofresidualplotsofallstatisticalmodelsdidnotrevealanyobvi- ousdeviationfromnormality.ForwithinmodalityanalysisofbothECoG andEEG,correlationaffectedsourcelocalizationaccuracysignificantly withP=2.898 × 10⁻⁷ (estimate0.0354, CI=[0.0219 0.0489], coeffi- cientofdeterminationR²=0.14)forECoGandP=4.89×10⁻⁴(estimate 0.0273,CI=[0.0120.0426],coefficientofdeterminationR²=0.19)for EEG,whichindicatesanimprovementinsourcelocalizationofaround 3.54and2.73cmforeachmodality.Fortherandomeffects,thelinear mixedeffectmodelreturnsanestimatedcovarianceandits95%confi- denceinterval.Thevariationbetweenrandomfactorswhoseconfidence intervaldidnotincludezerowasnotsignificant(seematerialsandmeth-

ods,sectiononstatisticalanalysis).Thiswasthecaseforallrandomfac- torsexceptforpatients(estimate0.0066,0.0095,CI=[0.0034,0.0127], [0.0091, 0.00099]forECoG andEEG,respectively).Sourcelocaliza- tion analysisbetween modalities for significantlycorrelatingdipoles showed ahighlysignificant effectofreference typeonmodality(es- timate0.022,P<10⁻¹²,CI=[0.025681,0.0184],coefficientofdetermi- nationR²=0.29).Thisindicatesanaveragesourcelocalizationaccuracy forEEGof7.1cmandforECoGasignificantlyloweroneof4.9cm.The variationbetweenrandomeffectswasnotsignificant. Fig.7showsa comparisonofthesourcelocalizationaccuracyofECoGandEEG.Resid- ualplotsfortheseresultsaregiveninsupplementaryfigureS5.Results ofthesamestatisticalmodelfordifferentvaluesofdipolegoodnessof

Table2.

Informationcomplementarytofigure5.Listedare,foreachICcorrelatingwithadepthelectrode contactandpermodality:a)cross-correlationatzero-lagandb)sourcelocalizationaccuracy(cm).

ECoG EEG

IC1: Contact 7: a) 0.4198 b) 6.08

Contact 8: a) 0.4974 b) 6.42

Contact 4: a) 0.3995 b) 7.13

Contact 7: a) 0.4379 b) 7.58

Contact 8: a) 0.4391 b) 7.88

IC2: Contact 6: a) 0.4201 b) 4.10

Contact 7: a) 0.456 b) 4.19 Contact 8: a) 0.471 b) 4.46

Contact 6: a) 0.4191 b) 6.97

Contact 7: a) 0.4198 b) 6.65

Contact 8: a) 0.4274 b) 6.32

IC3: Contact 6: a) 0.4912 b) 4.17 Contact 2: a) 0.3763 b) 4.7

Contact 3: a) 0.4015 b) 4.6

Contact 4: a) 0.3946 b) 4.04

Contact 5: a) 0.3819 b) 3.87

Contact 6: a) 0.4188 b) 3.54

Contact 7: a) 0.4525 b) 3.32

Contact 8: a) 0.4517 b) 3.1

Fig.6. Locationandtimeseriesofdepthelectrodecontactsforpatient2.Cor- respondingdipolescorrelatingwiththesetimesseriescanbefoundinfig.5.

fitarelistedinsupplementarytableS6(fortheresultsofthebroadband analysis,seesupplementarytableS7).

Sincetheeffectofdepthelectrodereferencewasnotsignificant,re- sultsshownfromnowonwillbediscussedbasedonaveragereference only(forbothaverageandbipolarreferencemontageresults,seesup- plementarymaterial).

AnoverviewofthedistancesbetweendepthelectrodesandECoG andEEGelectrodes,ashortsummarycanbefoundinTable3.Ascanbe seen,thedistancefromdepthelectrodestoscalpelectrodesisapproxi- matelytwicethedistancefromdepthelectrodestosubduralgrids.

Fig.7. Sourcelocalizationaccuracy(inmeters)ofECoGandEEG,shownsep- aratelyperfrequencyband.Colorsofdatapointsrefertopatients.

5. Discussion

5.1. Simultaneousdepth-ECoG-EEGrecordingallowsfordirectcomparison ofsourcelocalizationaccuracies

Our studyaimedtoquantitativelycomparethelocalizationaccu- racyofsubcorticalanddeepsourcesfromcorticalECoGandscalpEEG recordings.Aninitialanalysisshowedasmallbutsignificantcorrelation betweendepthelectrodesandbothECoGandEEG.Thefactthatneu- ralactivityfromdepthelectrodecontactscouldalreadybeobservedon bothscalpandsubduralelectrodesbeforeapplyingsourceseparation techniquesisaninterestingfindingasitsupportsafaircomparisonof EEGandECoGrecordingsinthedetectabilityandlocalizationaccuracy ofsourcesofneuralactivity.

Table3.

Mediandistancesbetweenelectrodesofthethreemodalities,foreachpatient.

Patient Distance between Depth and EEG electrode (cm) Distance between Depth and ECoG electrode (cm) Patient 1 Median = 10.5, sd = 2.18 Median = 5.2 sd = 1.4

Patient 2 Median = 10.3, sd = 1.9 Median 4.2, sd = 2 Patient 3 Median = 10, sd = 2 Median = 5, sd = 2.2 Patient 4 Median = 10.8, sd = 2.8 Median = 3.4, sd = 0.7

TheECoGandEEGsignalsweretheneachdecomposedusingICAto isolatespatiallydistinctsourcesthatcontributedtotherecordedsignal.

OurresultsshowedthatforbothEEGandECoGseveralindependent componentscorrelatedwiththe(non-decomposed)signalsatindivid- ualdepthelectrodecontactsinthehippocampusorinsula.Therecon- structedsourcesbasedonthesecorrelatedcomponentswerelocatedsig- nificantlyclosertothedepthcontactsthantheirnon-correlatedcoun- terparts.

Furthermore,ourcomparisonbetweenmodalitiesconfirmedasig- nificantdifferenceinsourcelocalizationaccuracy.Whendeepneural activityisdetectablebyEEGorECoGwecouldlocatethisactivitywith anaccuracyof7.1cminEEGand4.9cminECoG.Thepoorperfor- mance of EEGsource localizationwas tobe expectedgiven that,in additiontothelimitationsofthesourcelocalizationmodelmentioned above,aminimumof100electrodesisrequiredforasufficientlyaccu- ratesourcelocalization(Liuetal.,2017)whileinourcasewehad27 activeelectrodes.OurresultsshowedthatforthesameconditionECoG gridslocatedincloseproximitytothedepthelectrodesyieldedanim- provedaccuracyintherangeof ~2cm.Itisinterestingtonotethat whileECoG sourcelocalizationperformedindeedsignificantly better thanEEGsourcelocalizationonapopulation-levelthiswasnotsignif- icantonthescaleofasinglepatient.Additionally,webelievethatthe improvementinsourcelocalizationfromEEGtoECoGofdeepsources isnot largeenoughtojustifyapreferenceforinvasive measurement ofECoGovernoninvasiveEEG.Especiallygiventhatinsimultaneous EEG/ECoGrecording,thereareseveralproblemswithsourcelocaliza- tioninscalpEEG,suchas:

Duetothedisruptive effectof thesubduralgrid on volumecon- duction,scalpactivitywasattenuated.Therefore,theminimumcorti- calextentneededtoproducevisiblescalpactivitycanbeoverestimated (Ellenriederetal.,2014,Lanferetal.,2013).Forexample,a4×8grid canproduceattenuationof2to3times,whichmeansthattheminimum corticalamplitudenecessarytoproducevisiblescalpactivityishigher thanwhenthesubduralgridisabsent(Ellenriederetal.,2014).

1.Theplacementofthesubduralgridanddepthelectrodewascho- sentoprovideoptimalvisibilityoftheepilepticsource.Therefore,even thoughthespatialcoveragewaslimited,thesubduralelectrodeswere placedquiteclosetothedepthelectrode.ThisisincontrasttotheEEG electrodes,whichwereplacedinastandard10-20internationalsystem wherebytheirpositionwasnotaffectedbythepositionofthedepth electrode.

2.Aspreviouslystated,scalpelectrodeswererecordedfromonly27 electrodes.Studieshaveshownforsourcelocalizationaccuraciesinthe rangeof10~20mm,aminimumof100electrodesisrequired(Liuetal., 2017).Thisaccuracyislikelyevenlessfordeepandsubcorticalsources.

3.Consideringtheunfavorableconditionsofscalpelectrodesmen- tionedabove,wefoundan accuracyof4.9cmfor subduralgridsvs.

7.1cmforEEGtobesomewhatsurprising.However,previousstudies havealreadyshownusingcomputersimulationsthatEEG-basedsource localizationinidealconditionsoutperformsECoGin caseswherethe stripandgridelectrodesarenotsufficientlyclosetothesourceofinter- est(Dümpelmannetal.,2009,Zhangetal.,2008).Ourstudyshowed thatindeepstructures,thedistancebetweenthedeepsourceofneural activityandtheECoGgriddoesnotallowforaveryhighsourcelocal- izationaccuracy.Itstillremainstobeseenhowhigh-densityEEGwould performinsuchasetting,butarecentstudyusingsimultaneousdepth andhigh-densityscalpEEG,duringaverysimilarexperimentalcondi-

tion,reportedanaccuracyof~2cm(Seeberetal.,2019),emphasizing theimpactofhavingmorescalpelectrodes,somethingmuchlessex- pensiveandriskythanincreasingthenumberofsubduralelectrodes.To thebestofourknowledge,thiswasthefirsttimetheseabovementioned claimsweretestedandinvestigatedusingrealexperimentaldatafrom humansubjectswhenincludingagroundtruthfromthedeepstructures bymeansofdepthelectrodes.

Wealsoinvestigatedthevariancecausedbythetwodifferenttypes ofreferencingmontageforthedepthelectrodesbyincludingreference montageasarandomfactorinourstatisticalmodel.Wefoundnoeffect ofthechoiceofreferencing(the95%confidenceintervalofthisvari- ance didnotexclude zero).Independentcomponentanalysisshowed verysimilarresults forbothmontages,ascanbeobservedinsupple- mentarytablesS4andS5(forasummary,seeResultssection).Bipolar montagesarepresumedtobeadvantageouswhenattemptingtopickup localactivityastheyhelptocancelthemorewidespreadactivity.Inour case,thiscancellationeffectdidnotdifferfromacommonaveragemon- tageofalldepthelectrodemeasuringsites.Thereasonforthiscouldbe explainedasfollows.Bothtypesofreferencearepredominantlyrecord- ingactivityintheproximityofthedepthelectrodecontactandtheeffect ofafarsourcethatpropagatesinasimilarwaytoalldepthelectrodes willbecanceledbybothreferencetypes(seesupplementarymaterial figureS6forasimulationexample).OneshouldnotethatbipolarEEG alsoremovesallsignalscommontotheelectrodepairsandthatnotall signalscommontotheelectrodepairscomefromthesamereference.

Hence,agivenbipolarreferencewillcompletelymissdipoleswithcer- tainlocationsandtangentialorientations(Huetal.,2010).Geselowitz showedthatifthemodeltakesintoaccountthepositions ofthesen- sors,thechoiceofaparticularreferenceelectrodedoesnotinanyway changetherelationbetweensourceandpotential,exceptforanaddi- tiveconstantofnophysicalsignificance(GeselowitzDavid,1998).In conclusion,wedonotbelievethetypeofreferenceofthedepthelec- trodestohaveasubstantialeffectontheoutcomeofsimilarstudieswith simultaneousrecordingsofdifferentmodalities.

5.2. Controversyondetectingdeepandsubcorticalactivityfromscalpand subduralEEG

Severalstudieshavestatedthatatleast6cm²ofsynchronouscortical activityisneededtogenerateasignalwithastrongenoughsignal-to- noiseratiotobeobservedonthescalpwithoutaveraging(NunezPaul andSrinivasan,2006,Taoetal.,2005),althoughthishasbeencalled intoquestion(Ramantanietal.,2016).Whilethisstatementsuggests thatunaveragedactivityfromsmallersubcorticalstructuresisnotdis- tinguishablefromcorticalactivity,thesestructuresstillcontributecon- siderablytoscalpEEGandcanbereliablylocalizedundercertaincon- ditions.Forexample,inthecaseofbrainstemevokedpotentials,prior knowledgeofthelocationandbehaviorofdeepbrainactivityisavail- ablewhichcausessubcorticalactivityoflessthanamicrovolttobede- tected(PictonandTerrence,2010)andlocalizedwithinthebrainstem (SchergandVonCramon,1985).Additionally,thesuggestedminimum areadoesnottakeintoaccountthathigherneuraldensitiescouldpro- ducethesameamplitudewithinasmallerpatchoftissue.Itremainsto beseenhowtheneuraldensityofthehumanhippocampuscompares tothatoftheneocortex.Inrodentscertainhippocampalstructureswith neuraldensitiesseveraltimesthatofneocorticalstructureshavebeenre- ported(Kelleretal.,2018).Anotherconcernmightbethatthedistance

betweenthedeepstructuresandtheelectrodesisweakeningdipolecon- tributionbeyondobservabilityastheamplitudeoftheelectricaldipole decaysasa functionofdistance,althoughthis rateisvery smallfor distancesup to10cm(Arnulfoetal., 2015,Scherg,1990).Although thehippocampusisconsideredadeepstructure,itisrelativelysuperfi- cialcomparedtosubcorticalstructures.Indeed,themediandistancebe- tweenourdepthelectrodecontactslocatedinthehippocampuswasonly 4.6cmforsubduralgridsand11.9cmforscalpelectrodes.Simulation studiessuggestthatsourcelocalizationaccuracydeterioratesbeyond6- 8cmdistanceinECoG(Pascarellaetal.,2016)andforEEGitdeteriorates gradually,ataconstantrate(Whittingstalletal.,2003).Ofcourse,while EEGisacomplexsignal,sensitivetobothradialandtangentialsources, andcanmorereadilygaugepotentialsfromdeepsourcesincompari- sontoMEG,thesignal-to-noiseratiooftheactivityattributedtothese sourcescouldstillbepotentially verylow (PuceandS.Hämäläinen, 2017).Specifically,inrecordingsofspontaneousactivity,thesignal-to- noiseratiomaybeevenpoorerbecauseoftheoverwhelmingamountof simultaneouslyoccurringactivity.Indeed,ourresultsshowedthatwhen independentcomponentanalysiswasnotusedtoincreasethesignal-to- noiseratio,correlationswereverysmall(seeFig.2)thoughstillsignif- icant.Insummary,morestudiesarepresentingexperimentalandthe- oreticalevidencesuggestingthepossibilitytouniquelyrecoveractiv- ityfrombothcorticalandsubcorticalsources(Andersenetal.,2020, Attaletal.,2009,AttalandSchwartz,2013,Krishnaswamyetal.,2017, Seeberetal.,2019).

5.3. Hippocampusatrest

Thehippocampusplaysaprominentroleincentralnervoussystem functioning.Itcanevokelarge-scaleinfluencesoncorticalactivity,as itisahighlyinterconnectedregion,connectedanatomicallytoawide rangeof corticalregions(Coleetal.,2010).Thecontributionofhip- pocampalstructurestoscalpEEGandalsoMEGhasrecentlybecome moreaccepted,asevidencedbydeepstructuressuchasthehippocam- pusfornotbeingso“closedfield” aspreviouslythought,andthereforea cancellationofoppositelyorienteddipolegeneratorsmightnotbeasex- tensive(Attaletal.,2009,AttalandSchwartz,2013,Meyeretal.,2017, QuraanMaheretal.,2011,Ruzichetal.,2019).Furthermore,exper- imentsinmammalsrevealedsubcorticalstructuressuchastheamyg- dalaandthalamustohavearelativelyhighsourcedensitycompared totheneocortexwhichis whyintheory asmalleractivated volume wouldbeneededtoproduceadetectablesignalonthescalp.This is alsotrueforsomepartsofthehippocampussuchasthedentategyrus, althoughothershavealowercurrentdensity(Kelleretal.,2018).During rest,brain-wideslowoscillationsareacharacteristicfeatureofboththe mammalianneocortexandthehippocampusoccurringspontaneously andphase-lockedtoeachotherwithashortdelay(Chanetal.,2017, Wolanskyetal.,2006).Thissuggeststhat,inlow-frequencyranges,deep brainregionssuchasthehippocampuscouldinitiatebrain-widecortical activity.Whetherthehippocampalneuralactivityispickedupbysubdu- ralandscalpelectrodeswithsufficientsignal-to-noiseratiotobevisible isaquestionwehaveaddressedinthisstudy.Inordertodistinguishbe- tweenthetwolikelytypesofactivitypropagation−physiologicalprop- agationofactionpotentialsthroughcausalinteractions(activespread) andelectrical volumeconductionthroughcorticalstructures(passive spread)−timingis key.Therefore,forourinvestigation,itiscrucial toeliminatecorrelationsthatweremaximumatanon-zerolag.Future studiescouldlookdeeperintothephaserelationsbetweenthesetypes ofactivitypropagationbyusingtheimaginarypartofphase-basedcon- nectivitytechniques.However,evenwhencontrollingforzero-lag,we cannotfullyruleoutthepossibilitythatactivityfrombrainregionslo- catedoutsidethehippocampusisvolumeconductedatzero-lagtoboth depthelectrodesandECoGorEEGelectrodes(BénarandBadier,2019).

Thisisaddressedfurtherdownunderthelimitationsofthestudy,point III.

5.4. Detectabilityismoreprominentforthetaoscillations

Theta-alphaoscillationsareprominentlyobservedinthehippocam- pusofallmammalsstudiedtodate(Buzsáki,2002).Duringquietwake- fulness,evidenceexistsforactivityinthetheta-deltarangeinthehuman hippocampus(Frauscheretal.,2018).Furthermore,ithasrecentlybeen suggestedthatlow-frequencyhippocampalactivityplaysasignificant roleindefiningtheinterhemisphericcorticalresting-stateconnectivity andmediatesvisualprocessing.Ourresultsshowcomponentscorrelat- ingwithadepthcontactinthethetarangetwiceasstrongascorrelating componentsinthealphaorbetarange.Thissuggeststheimportanceof slow-hippocampalactivityintheformationoftheelectrophysiological signatureofresting-stateactivityinthehumanbrain(Chanetal.,2017).

5.5. Limitationsofthestudyandsuggestionsforfutureresearch

Onafinalnote,wewanttopointoutthefollowingpracticaland technicallimitationsofthecurrentstudyaswellassuggestionsforfuture improvement:

Whilethetopographyofthescalpelectrodesisinaccordancewith thestandard10-20internationalsystemandcommontoallpatients, theexactlocationandnumberofdepthandsubduralelectrodesvaries amongpatients(seesupplementarymaterialTableS1andfigureS1).

Thisundeniablyexplainspartoftheobservedvariability.

The forwardmodelcurrently providedin theBrainstormtoolbox doesnotaccountforsurgery-inducedeffects,suchassuturesoftheskull andtheimpactofthenon-conductinggrid.Holesintheskullcanhave alargeimpactonthescalppotentialdistributionandneglectingthem can leadtoasystematicerrorinfittedsourcelocationsuptoseveral centimeters (Oostenveldand(OostenveldandF.Oostendorp,2002)).

Volumeconductionmodelsignoresucheffects(Pascarellaetal.,2016) althoughrecentlyforwardmodelshavebeendevelopedforECoGsource localizationinprimatesthattakeintoaccounttheimplantationofvery lowconductivityECoGsiliconestrips(Wangetal.,2019).However,in thisstudy,ourobjectivewasnottoachievethebestsourcelocalization accuracy,butrathertocomparesourcelocalizationbetweenECoGand EEGgiventhecurrentlyavailablemodels.Inthisrespect,futurestudies arenecessarytodeterminehowmuchsourcelocalizationwithECoGor EEGisaffectedbyaccountingfortheabove-mentionedissues.Further- more,itwouldbeofinteresttoinvestigatetheneuralactivityofresting- statebymeansofmethodsthatcancombineEEGandECoGwithinga singleheadmodel.Itstillremainstobeseen howsuchamodelcan improvethelocalizationofdeepbrainstructures,sinceprevioussimu- lationshaveshownlittleimprovementinlocalizationaccuracyinareas beneaththenon-conductinggrid(Todaroetal.,2018).

Inthisstudy,wepresumedindependentcomponentstohaveasig- nificantzero-lagcorrelationwithneuralgeneratorsincloseproximity tothedepthelectrode,thoughintheory,zero-lagcorrelationcouldbe aresultofdistantcoupledoscillators(Petkoskietal.,2018).Webased ourassertionontheobservationthatourindependentcomponentsdo not correlatewithall depthcontacts.Ifaneuralgeneratorwouldbe locatedfurtherawayfromthedepthelectrodes,mostprobablyacorre- lationwiththemajorityofthedepthelectrodeswouldbeobserveddue tovolumeconduction.AsfaraswecanseefromtablesS4andS5,in mostcasesthisdoesnothappen,bothforaverageandbipolarreferenc- ingofthedepthelectrode.TableS4showsthat,eveninthesubdural grids, thenumberof depthelectrodecontacts thatcorrelateon aver- agewithaspecificindependentcomponentisaround3contacts(2.1 forbipolarreference)andrarelyexceeds5contacts.OnlyinpatientP2 (bipolarandaveragereference)andP4(onlyaveragereference)didwe findcomponentsthathadasignificantcorrelationwithalldepthelec- trodecontacts inahemisphere(seeFigs. 4andS3insupplementary material).ForpatientP2,thiswasseenforonecomponentinthetheta band(sameforbipolar)inbothECoGandEEG.ForpatientP4,2out of16subduralcomponentsinthethetaandbetabandwerecorrelated withalldepthelectrodecontacts(bothhemispheresforthethetaband,

onlytherighthemisphereforthebetaband)and4outof21scalpcom- ponentsinthethetabandshowedsignificantcorrelationwithalldepth electrodecontacts(2ofwhichwerecorrelatingwithbothhemispheres, onewithleftandonewiththerighthemisphere).PatientP4alsohadthe smallestdistancebetweensubduralanddepthelectrodes,whichcould explainthehighnumberofcorrelateddepthelectrodecontacts.Inany case,thefactthatthisisnotacommonobservationandthatthereis indeedasignificantdecreaseindistancebetweentheestimateddipoles andtheircorrelateddepthelectrodecontacts,comparedtotheaverage distancebetweenthenon-correlatingdipolesandtheaveragelocation ofalldepthelectrodecontacts,convincedusthatcorrelatingcompo- nentsarecomingfromneuralgeneratorsincloseproximitytothedepth electrodecontact.Thispresumptionshouldbeconfirmedbystudiesfor whichthereispriorknowledgeofaneuralgeneratorlocatedindeepor subcorticalstructures.

Inthisstudy,ourmethodforsourcelocalizationwasrestrictedto dipolemodeling.Futureresearchisnecessarytodeterminetowhatex- tentourresultswillbeinfluencedwhenchoosingalternativemethods suchassourcedistributedmodeling(JatoiMunsifetal.,2014).

Furthermore,recentstudieshavesuggestedtheuseoftheLaplacian re-referencemontagefordepthelectrodesasopposedtothebipolarand averagemontagesusedinthisstudy(Lietal.,2019).

6. Conclusion

Theassertionthatdeepstructuressuchasthehippocampusdonot produceactivityvisibleonthescalp,duetotheirassumed“closedfield” nature,isincreasinglybeingchallenged.Usingagroundtruthinthehip- pocampusandinsulaof4patientsweshowedthatduringquietwakeful- ness,theactivitypickedupbydepthelectrodesindeedcorrelateswith scalpEEGactivitydecomposedusingICAanalysis.Wespeculatethat thesecorrelationsstemfromneuralgeneratorsincloseproximitytothe depthelectrodesfortworeasons:I)anindependentcomponentwasnot observedbyalldepthelectrodesandtypicallycorrelatedwithonlya fewofthedepthelectrodecontacts,whichhintsatlocalactivityandII) theresultofdipolefittingforthecorrelatedcomponentsshowedasig- nificantdecreaseinthedistancebetweenthedipoleanddepthelectrode contact,comparedtonon-correlatingcomponents.

Furthermore,bysimultaneouslyrecordingnotonlyECoGandscalp EEGbutalsodepthelectrodes,wewereinauniquepositiontocom- paresourcelocalizationaccuracyofdeepsourcesusing invasiveand non-invasiveEEG.Tothebestofourknowledge,thisisthefirststudy presenting experimental findings on thecomparison of invasive and non-invasiveEEGsource localizationaccuracyofdeepcorticalstruc- tures. Ourresults showed that,while source localizationusinginva- siveEEGturnedouttobeindeedsignificantlymoreaccuratethanusing non-invasiveEEG,webelievethisimprovedaccuracyisnotsatisfactory giventhat:I)scalpEEGisrecordedwithalownumberofelectrodesand partiallyshieldedbythenon-conductingECoGgrid,andII)thelocation ofbothECoGelectrodesanddepthelectrodeswerechosenforoptimal visibilityandproximitytotheepilepticsourceandwerethereforein closeproximitytoeachother.

7. Dataavailability

Thedatasetsforthismanuscriptarenotpubliclyavailableasitcon- tainssensitiveinformationaboutthepatientsandthereforecannotbe transferredusingonlinerepositories.

Acknowledgments

TheauthorswouldliketothankRobertOostenveldforhisvaluable inputon thedesignof thestudyandthe writingof themanuscript.

MFHissupportedbytheHermes Fundof theNationalFundforSci- entific Research Flanders (SB/151022). BW is supported by a post- doctoralmandate(PDM/19/176)fromKULeuven.EKissupportedby

thespecialresearchfundoftheKULeuven(C24/18/098).ALissup- ported by theResearch Foundation Flanders (FWO 1SC3419N).EC, ID,AMandPBaresupportedbytheBelgian FundforScientificRe- search– Flanders(G0A4118N).MMVHissupportedbyresearchgrants receivedfromtheEuropeanUnion’sHorizon2020researchandinno- vationprogrammeundergrantagreementNo.857375,theFinancing Program(PFV/10/008)andthespecialresearchfund oftheKULeu- ven (C24/18/098), theBelgian Fund for Scientific Research – Flan- ders(G088314N,G0A0914N,G0A4118N),theInteruniversityAttrac- tionPolesProgramme– BelgianSciencePolicy(IUAPP7/11),andthe HerculesFoundation(AKUL043).

Supplementarymaterials

Supplementarymaterialassociatedwiththisarticlecanbefound,in theonlineversion,atdoi:10.1016/j.neuroimage.2020.117344.

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