Oscillations and Episodic Memory: Addressing the Synchronization/Desynchronization Conundrum

Opinion

Oscillations and Episodic

Memory: Addressing the

Synchronization/

Desynchronization Conundrum

Simon Hanslmayr,

* Bernhard P. Staresina,

and

Howard Bowman

Brain oscillations are one of the core mechanisms underlying episodic memory. However, while some studies highlight the role of synchronized oscillatory activity, others highlight the role of desynchronized activity. We here describe a framework to resolve this conundrum and integrate these two opposing

oscillatory behaviors. Specifically, we argue that the synchronization and

desynchronization reflect a division of labor between a hippocampal and a neocortical system, respectively. We describe a novel oscillatory framework that integrates synchronization and desynchronization mechanisms to explain how the two systems interact in the service of episodic memory.

The Synchronization, Desynchronization Conundrum

Brain oscillations (seeGlossary) provide temporal windows for neuralfiring and shape synaptic plasticity by synchronizing and desynchronizing neural assemblies. Oscillations therefore have a particularly high potential to shed light on the mechanisms underlying episodic memory [1,2]. However, over the past few years a conundrum has emerged regarding how brain oscillations relate to memory [3]. Whereas some studies highlight the role of synchronized activity, mainly in the theta (3–8 Hz) and gamma (40–80 Hz) frequencies[1], others highlight the role of desynchronized activity, mainly in the lower-frequency ranges (<20 Hz[4]). This conundrum exists at both an empirical and a theoretical level. Based on Hebb's seminal idea– neurons thatfire together, wire together – a strong case can be made that synchrony is required for memory formation[1,2]. However, mathematical information theory, alongside physiological studies in animals, postulates that high synchrony, especially in the lower-frequency ranges (<20 Hz), reduces information coding [4–6]. We here aim to integrate these two seemingly incompatible concepts and present a mechanistic framework to resolve this conundrum. Building on complementary learning systems [7], we assume a division of labor between a hippocampal system, which mainly binds information, and a neocortical system, which mainly represents the content of this information. Based on recentfindings, we argue that this division of labor is visible in the two opposing oscillatory behaviors, with the hippocampal system showing synchronization in the theta/gamma range[8–10], mediating binding [11], and the neocortex showing low-frequency desynchronization[4], mediating the representation of infor-mation[12,13].

Hippocampal Synchronization in the Service of Episodic Memory

The critical role of the hippocampus for intact episodic memory has beenfirmly established by neuropsychological studies, animal models, computational models, as well as human

Trends

Data from rodent as well as human studies suggest that theta/gamma syn-chronization in the hippocampus (i.e., theta phase to gamma power cross-frequency coupling) mediates the bind-ing of different elements in episodic memory.

In vivo and in vitro animal studies sug-gest that theta provides selective time windows for fast-acting synaptic mod-ifications and recent computational models have implemented these mechanisms to explain human mem-ory formation and retrieval.

Recent data from human experiments suggest that low-frequency power decreases in the neocortex, most evi-dent in the alpha/beta frequency range, mediate encoding and reinstatement of episodic memories.

The content of reinstated memories can be decoded from cortical low-frequency patterns.

1

University of Birmingham, School of Psychology, Birmingham, UK

2

University of Kent, School of Computing, Canterbury, UK

*Correspondence:

[email protected]

Glossary

ComplementaryLearning Systems(CLS):theCLSapproach wasconceivedasaresponsetothe plasticity–stabilitydilemma,a fundamentaltrade-offthatlearning systemshavetodealwith.CLS proposesameanstoobtaina relativelystablelearningsystem withoutforfeitingplasticityanddoes thisbypositingtwosubsystems,the neocortexandhippocampus,with complementaryrepresentational characteristics.Theneocortical systemslowlylearnshighly ‘overlapping’representations,with unitsbecomingbroadlytunedand therebycontributingtomanydifferent storedpatterns.Asaconsequence, thecorticalsystemishighly susceptibletocatastrophicforgetting. Thehippocampalsystem,by contrast,isnotlimitedinthisway. Thisisachievedbyitexhibitinga sparsecodeinwhichthe representationforeachnewpattern haslittleoverlapwithpriorlearned patterns.Thispattern-separated character,whichisparticularly evidentinthedentategyrusand CA3,ensuresthatitisnotsubjectto catastrophicforgettinginthesame wayastheneocortex.Furthermore, thislevelofoverlapofunits representingnewandolditems meansthatthissystemcanlearn quicklywithlittlecost.Thisenables theCLSsystemtoexhibit‘one-shot’ learning,aswehumansdo.See

[7,66]forarecentreview. Desynchronization:adecreasein theneuralbehaviorcausing synchronization(seeSynchronization). Information:averybroadtermwith numerousdifferentdefinitions.Rather thangivingafurthertheoretical definitionofinformation,wehererefer toinformationinanoperationalway. Thatis,informationis,forus,the degreetowhichwecanmake inferencesabouttheidentityofa particularperceivedorretrieved memoryfromaparticularobserved temporalorspatialneuralpattern. Noisecorrelations:aplethoraof single-unitrecordingsinmonkeyshas shownthatevenunderthemost controlledconditionsfiringratevaries significantlyfromtrialtotrialwhen identicalstimuliarepresented. Synchronizedlow-frequency fluctuations(<20Hz)infiringrate, whichareindependentofthe stimulus,areassumedtobethemain

neuroimaging[14].Notably,hippocampalengagementseemsparticularlyimportantforthekey characteristicofepisodicmemories;thatis,bindingdiscontiguous(i.e.,separate)eventdetails intorichassociativememorytraces[15].Howisthisfeataccomplishedmechanistically?Gamma oscillations,operatingattimescalesbelow30ms,haverecentlybeenproposedastheprime candidatetofacilitatelearning-relatedsynapticchangessuchasspike-timing-dependent plas-ticity (STDP)/long-term potentiation (LTP) [1]. Does the hippocampus recruit such gamma oscillationsintheserviceofepisodicmemoryformationandretrieval?

Directhippocampalrecordingsfromhumanepilepsypatientshavefoundthatgammapower increasescorrelatewithbothsuccessfulmemoryencoding[16]andretrieval[17].Onecaveat relatedtotheseresultsisthat,oncloserexamination,thegammaeffectswerefoundtobepartof more broadband power increases, ranging from 30Hz to 100Hz [18,19]. The functional significanceofsuchbroadband powerincreasesremainsunderdebate,butconsensushas emergedthattheyreflectmulti-unitspikingactivityratherthantrueoscillatoryactivity([20,21], butsee[22]).However,recentrecordingsfromtheprimatehippocampushavesucceededin showingnarrow-bandgammapowerincreasesaswellasspike-fieldcoherencebetweensingle unitsandgamma-bandLFPsduringsuccessfullearning[23].

Perhaps even more compelling evidence for hippocampal gamma oscillations supporting episodicmemoryprocessescomesfromstudiesexaminingshort-rangeinter-regional synchro-nization, particularly between the hippocampus and the adjacententorhinal cortex (EC). In humanepilepsypatients,gamma-bandcoherencehasbeenfoundtoincreasebetweenthese regionsasafunctionofsuccessfulepisodicencoding[24]aswellasretrieval[25](Figure1B). Recordings from rodent models have gone further to identify a frequency-specific ‘routing function’ofgammaoscillations,suchthattheCA1subregionisfunctionallycoupledwithCA3 versustheECindifferentgammasub-bands[26].Establishingtherelevanceofthiscouplingfor learningprocesses,arecentstudyhaslinkedthegamma-bandcoherencebetweenCA1and theECtotheencodingandretrievalofodor/spaceassociations[27].

Insummary,convergingevidencehasaccumulatedacrossdifferentspeciesandacrossdifferent experimentalparadigmsforacriticalroleofsynchronizedhippocampalgammaoscillationsinthe serviceofepisodicmemory.Thepressingquestionisthenhowtheseoscillationsarethemselves regulated.Ignitedbythehallmarkobservationofthetaphaseprecessionofhippocampalplace cells[28],muchresearchhasbeendedicatedtounderstandingtheroleofthethetarhythmin orchestratingmemory-relatedneuralsignals[29].Astrikingexampleisthefinding–observedvia directrecordingsfromthehumanhippocampus–thatsuccessfulepisodicencodingmaynot necessarilyrelyonthenetincreaseinhippocampalfiringratesbutonthetemporalprecisionof single-unitfiringwithrespecttotheconcurrentthetaphase[8].

Importantly,recentresearchhasbeguntoinvestigatenotonlyhowthethetarhythmmayclock single-unitfiringbutalsohowoscillatorypatternsinthegammarangemayberelatedtothe ongoingthetaphase[9].Forinstance,theabovementionedcouplingbetweenCA1andCA3 versustheEC was notonly expressed indifferent gammasub-bands butalsooccurred at differentphases ofthethetacycle[26].Moreover(andnotwithstandingtheabovementioned questionofwhethergammapowerincreasesreflecttrueoscillatorychangesversusmulti-unit spiking),evidencehasaccumulatedinbothrodentmodelsandhumanintracranialrecordings thathippocampaltheta–gammacouplingislinkedtosuccessfulepisodicmemoryprocesses [30].Ofparticularimportanceisarecentmagnetoencephalography(MEG)studythatshowed thatitem–contextbinding,ahallmarkofepisodicmemory,criticallydependsontheta–gamma couplinginthemedialtemporallobe(MTL),andspecificallyonwhethergammaoscillationsare coupledtothepeakorthetroughofathetacycle(Figure1A)[11,30,31].Notably,thefrequency rangeshowingthestrongestmodulatoryeffectsisslightlylowerinhumans(3–4Hz)thanin

rodents (8Hz), in line with the notion that functionally homologous oscillations occur at increasinglyslowerfrequenciesasbrainsizeincreasesacrossspecies[32,33].

Takingthese findings together, the mnemonicfunctions ofthe hippocampus appear to be intimatelylinkedtoneuronalsynchronizationinthegammafrequencyband,witharegulatory influenceofthephaseofongoingthetaoscillations(Figure1A,B).

CorticalDesynchronizationintheServiceofEpisodicMemory

Oscillatory powerdecreases during the formation ofmemories (i.e., encoding) are typically observedinthelower-frequencyranges(<20Hz),especiallyduringencodingofitemsthatare laterrememberedcomparedwith laternotremembered [34,16,35–37].Forinstance,during encodingofverbalmaterial,alpha/betapowerdecreases(12–18Hz)aremostevidentinthe leftinferiorprefrontalcortex[16,37,38].Importantly,suchleftfrontalbetapowerdecreasesare notasimple(incidental)byproductofmemoryformationbutarecausallyrelevant,as demon-stratedinarecent combinedelectroencephalography (EEG)–rhythmictranscranial magnetic stimulation(rTMS)study[39](Figure1C).Giventhattheleftinferiorprefrontalcortexisstrongly involvedinsemanticprocessingingeneral,theseresultsfitwithseveralfindingsinthelanguage domainshowingthatleftprefrontalbetapowerdecreasesduringsemanticprocessing[40,41]. Memoryformationfornonverbalmaterial(i.e.,images)isalsoaccompaniedbypowerdecreases;

drivingforceofthisvariability,termed noisecorrelations[49].Onewayin whichattentionenhancestheneural signal-to-noiseratioisbyreducing (i.e.,desynchronizing)these low-frequencyfluctuations[6]. Oscillations:brainoscillationsare typicallydividedintodifferent frequencybandsandreferredtoby lettersoftheGreekalphabet, includingbutnotlimitedtodelta (1–4Hz),theta(4–8Hz),alpha (8–12Hz),beta(15–25Hz),and gamma(40–80Hz).Theexact boundariesbetweenfrequenciesare difficulttodefineandvary considerablybetweenexperiments andspecies.

Synchronization:therearemany waystodefineneuralsynchronization andevenmoremethodstomeasure it.Inthisopinionarticle,wereview studiesthatfocusedoneitherofthe followingthreetypesof

synchronization:(i)thelevelof synchronizationwithinalocalcell assembly,whichcanbemeasured viathepowerofanoscillatorysignal onEEGorMEG[67];(ii)interareal synchronization,whichisthe synchronizationbetweentwobrain regions(e.g.,thehippocampusand therhinalcortex)[24];and(iii)phase amplitudecross-frequencycoupling, whichreferstothesynchronization betweentwofrequencieswhereby thephaseofalowerfrequency modulatesthepowerofahigher frequency(e.g.,thecouplingbetween thephaseofthetaandthepowerof gamma[11,30,31]).

(A) (B)

(C) _(D)

Item-context binding No item-context binding

Phase (rad.) Phase (rad.)

Theta/Gamma synchrony during EM encoding Gamma synchrony during EM retrieval

Beta desynchronisaon during EM encoding Alpha/beta desynchronisaon during EM retrieval

0 0.5 1.0 1.5 2.0 0.0 –0.4 0.4 0.8 1.2 Time (sec)

coh. change from baseline

iEEG coherence (35-40 Hz) between hippocampus and Rhinal cortex (source memory vs. item recognion)

Source Item

Power change (%) from baseline 0.0

10 20

Alpha/Beta power (10-25 Hz, 100-200 ms) Item encoded in the le VF –

Item encoded in the right VF

Le electrodes Right electrodes Le VF Right VF – pi 0 pi – pi 0 pi

Gamma power Gamma power

3.9 4.1 4.2 4.0 3.9 4.1 4.2 4.0 x 10 x 10 1 0 –1 1 0 –1 ∗ ∗ 10-25 Hz 100-200 ms Memory performance 18.7 Hz 10.7 Hz 6.8 Hz Sham 50 45 40 35 0 % Recalled Key: Key:

Figure1.StudiesShowingHippocampalTheta/GammaSynchronizationandAlpha/BetaDesynchronization

DuringEncodingandRetrievalofEpisodicMemories(EMs).(A)Gammapowercoupledtodifferentphasesoftheta

predictswhetheritem–contextbindingoccursordoesnotoccur,astestedinasubsequentmemoryparadigmwherethe contextualoverlapbetweenencodingandretrievalwasdirectlymanipulated[11].(B)Resultsfromanintracranial electro-encephalography(EEG)studyshowinggammaphasesynchronizationbetweenthehippocampusandrhinalcortexduring successfulassociativerecognition(i.e.,sourcememory)comparedwithsimpleitemrecognition.(C)Preventingbeta desynchronization(i.e.,18.7-Hzstimulation)attheleftinferiorfrontalcortexviarhythmictranscranialmagneticstimulation (rTMS)selectivelyimpairsmemoryencoding.(D)Alpha/betapowerdecreasesduringretrievalindicatethevisualfield(VF) where a stimuluswasinitially encoded (i.e., alpha/beta power decreasesindicate memory reactivation). (A,B,C,D) reproducedandmodifiedwithpermissionfrom[11,25,39,47],respectively.

however,thesedecreasesapparentlyoccurmoreinthealpharangeatparieto-occipitalregions [34]. Clearly, more studies are needed to investigate alpha/beta power decreases during memoryformationofdifferentmaterials(includingwords,images,andsounds),butthepattern ofresultssofarsuggeststhatalpha/betadesynchronizationindexesinformationprocessingin specializedcorticalmodulesduringtheperceptionofanevent[42,43]andthereforepredictits likelihood of being later remembered. Of note, this negative relationship between power decreasesandmemoryformationmightalsoextendtothethetafrequencyrange,asindexed byseveralrecentstudiesshowingthatthetapowerdecreasescorrelatewithmemoryformation [16,44].

Asimilarpicturearisesforpowerdecreasesduringmemoryretrieval.Forinstance,the topog-raphyofalpha/betapowerdecreasesvarieswiththetypeofretrievedmaterial(i.e.,wordsversus faces[45]orlocationsversusobjects[46]),suggestingthatpowerdecreasesindicate material-specificmemoryreactivation.Directsupportforthiscomesfromstudiesthatpresentedobjects duringencodingtoeithertheleftorrightvisualhemifieldandshowedthatmemoryretrievalof centrallypresentedobjectsisindeedreflectedbyalpha/betapowerdecreasescontralateralto thesiteatwhichtheitemwasencoded[13,47](Figure1D).Usingmultivariatepatternanalysisof time–frequency data, two MEG/intracranial EEG (iEEG) studies went one step further and demonstratedthatthecontentofreactivatedmaterialcanbereliablydecodedfromalpha/beta frequencies[12,48].Forinstance,applyingatemporal-pattern-analysisapproach,Staudigletal. [12]demonstratedthatthereactivationofindividualdynamiccontexts(i.e.,movieclips)canbe decoded from the temporal pattern of beta phase in material-specific cortical areas (i.e., parahippocampalarea,visualcortex;[12]).Together,theseresultsofferaninterestingpossibility forthemechanistic roleoflow-frequency powerdecreases:decreases inoscillatory activity enableaneuralassemblytoexpressastimulus-specificcodebyallowingamorecomplex(i.e., information-rich)temporalphasetrajectory.Arguably,suchacodingmechanismwouldnotwork veryefficientlyinsituationsofhighsynchrony(i.e.,astationarysignal),wherelargepopulationsof neuronsareentrainedtothesamerhythm[4].

Takingthesefindingstogether,wepostulatethatlow-frequencypowerdecreasesreflecttheactive engagementofcorticalmodulesduringencodingandretrievalofmemories.Anopenquestionis whatalow-frequencypowerdecreasemeansmechanistically(i.e.,attheneurallevel)andhowit relatestothetheta/gamma dynamicsinthehippocampalsystem.Althoughmoreresearchis neededtoanswerthiscomplexquestion,aconvergentpicturecanbederivedfromthreedifferent recentframeworks.(i)Followingthealphainhibitionframework,low-frequencypowerdecreases couldactasagatingmechanismwherebydecreasingalphapowerincreasesfiringrates[42,43]. Notably,thisnegativerelationshipbetweenoscillatoryactivityandneuralfiringmightalsoextendto higher (beta) and lower (theta) frequencies [9]. (ii) A second line of research suggests that synchronizedfiringinlowfrequenciesisamaincontributortothetrial-by-trialvarianceinneural firing(termed‘noisecorrelations’),therebyreducingthereliabilitywithwhichaneuralcodeis expressedinapopulationofneurons[6,49].Decreasingtheamplitudeoftheselow-frequency oscillationswouldreducesuchneuralnoisecorrelationsandthusincreasethereliabilityofaneural codethatis conveyedto downstreamneurons (i.e.,inthe hippocampus). (iii)Finally, power decreasesthemselvescouldbeamechanismtode-correlateneuralactivitytoenhancetheneural codingcapacityperse.Powerdecreasesmighttherebyallowflexiblephaseadjustmentsina neuralpopulationtoformatemporalcoderepresentingtheidentityofaspecificstimulus[4,12,50]. The common notion between all of these different frameworks, however, is that power decreasesenableaneuralassemblytoexpressaneuralcodeinsomeform;thatis, viaan increasein firing rate, a reductionin noise, or phase encoding. Anysuch code would be meaninglessifit werenot interpretedbya ‘reader’[2].Here weassumethatthis readeris thehippocampus(Figure2).

Reconciliation:ASynchronized Hippocampusanda DesynchronizedCortex

TheComplementaryLearningSystems(CLS)theoryhaschampionedthepositionthatthe neocortexand hippocampus provide differentbut complementary representational formats, withtheneocortexsupportingarichintegratedrepresentationlearnedovermanyexperiences andthehippocampusprovidingasparserepresentationlearnedin‘oneshot’(oratleastfew shots).Thetheoryalsoproposesthatthehippocampus,sittingattheendoftheprocessing pathway,providesonlinelearning ofconjunctive representations,whichbindtheconstituent elementsofanepisodicmemory.Thisisimplementedbystrengtheningthesynapsesbetween contributingneuronsthroughLTP.

WearguethattheCLStheoryprovidesaframeworkwithinwhichthedisparityinsynchronyof oscillationsbetweencortexandhippocampuscanbereconciled.Statedexplicitly,wepropose thatthecomplementarityofcomponentsubsystemsisreflectedinthedisparityofoscillatory dynamicsthatthesesubsystemsexhibit.Ourproposalismostclearlyunderstoodby consider-ingthesequenceofstepsthatweenvisagerealizeencodingofepisodicmemories(illustratedin Figure2).(i)Sensorystimulation(e.g.,seeingapersoninaparticularplace)inducesareductionin alpha/betaoscillationstoallowneocorticalunitstoencodethecontentofthatstimulation[42,43] bypushing their firing rates upsignificantly.Whether alpha/betapower reductions drivean increaseinneuralfiringorwhetheranincreaseinneuralfiringdrivesareductioninalpha/beta powerisanopenquestion;however,thenetresultisinbothcasesanobservabledecreaseof alpha/betapowertogetherwithincreasedanddesynchronizedfiringofbroadlytunedneurons. (ii)This stimulation-specificfiringrateincreaseintheneocortexinturn drivescorresponding stimulation-specifichippocampal unitsto move their firing forwardinthe phaseoftheta. In thecasewherehippocampal unitsarenot receivingstimulus-specificdrive fromneocortical units,theywouldfireintheexcitatoryphaseoftheta;thatis,inthetroughofthetaasrecordedin

No Input Hipp. NC Alpha (10 Hz) Theta (4 Hz) LTP LTD LTD LTP Input Hipp. NC Alpha (10 Hz) Theta (4 Hz) LTP LTD LTD LTP No memory formaon Memory formaon (A) (B) + - + - LFP LFP + LFP +

Figure2.ASchematicoftheCurrentFramework.(A)Intheabsenceofexternalinput,highalphapowerisevidentin

theneocortex(NC),withNCneuronsfiringatalowrate.Inthisstate,theNCneuronshavelittleimpactontheirdownstream neuronsinthehippocampus.long-termpotentiation(LTP)/long-termdepression(LTD)isregulatedbythethetaphase, whereby,intheabsenceofinput,thesynapticconnectionsbecomeweakened(LTD).(B)Inputreducesthe(effective)firing thresholdforstimulation-specificpopulationsintheNC,which,inthiscase,respondtotwostimuli.Onthepopulationlevel, neuronalfiringincreases,whichleadstoadecreaseinsynchronyandalphapower.TheincreasedfiringinthetwoNC populationsof neuronswouldinturnreducethe(effective)firingthreshold oftheirhippocampalstimulation-specific downstreamneurons,causingphaseprecession(indicatedbyarrows)andhenceLTP,whichthenformsanassociation betweenthetwostimuli.Notethatthephaseofthetachangesdependingonwhichhippocampalsubregionitisrecorded from[29],being180o

phaseshiftedbetweenthehippocampalfissureandCA1/CA3.Wehereplotthetaaswouldbe recordedinCA1(andCA3),inkeepingwithstudiesthatshowedLTPtooccuratthepeak(+)andLTDtooccuratthetrough ( )oftheta[53,55].Moreover,aspresentedhere,thepeakofthetaisinfactthefunctionallyinhibitoryphase,whileitstrough isthefunctionallyexcitatoryphase.

CA1/CA3[51](Figure2A).Inthecaseofstimulation(i.e.,encoding),thoseunitsthatrespondto thepresentedstimuliwouldadvancetheirspikingwithrespecttotheongoingthetaoscillation, showingapatternthatissimilartothewell-documentedphenomenonofphaseprecession[28]. Thatis,theincreasedexternaldrivingexcitationenablesthestimulation-specifichippocampal unitstohittheirfiringthresholdearlierinthethetaphase;thatis,closertotheinhibitoryphaseof theta(i.e.,thepeakinCA1/CA3)–atimepointwheremosthippocampalunitsaresilent[51,52]. (iii)Thisadvancementinitiatesatemporalsegregationinwhichprecessedunitscometofireinan earlierandseparategammacycleepisode.Thisagaintakesinspirationfromphaseprecession, wherebyprecessionspecificallyadvancesthegammacycleofavolleyofspikesinthephaseof theta.Importantly,weproposethatthesegregationofstimulation-sensitivefromnon-sensitive unitsenablesLTPtobeselectivelyapplied.Thereby,theearlierphaseofthetathat stimulation-specifichippocampalunitsaredriventofireinisspecificallyoneinwhichLTPoccurs.SeeBox1 forpossiblemechanismsthatcouldunderliethisincreaseinLTP.(iv)Thisincreasedsegregation intogammacycleswouldexplainhowthecouplingofthetaphaseandgammapowerwould correlatewithmemoryformationanditem–contextbindinginthehippocampus[11,30,31].(v)As aresultofthisselectiveLTP,stimulation-specificunitswouldbecomestronglyinterconnectedin thehippocampus,layingdownamemoryoftheepisode.FollowingCLStheory,these asso-ciativeconnectionswouldfacilitateretrievalthroughcompletionofapartialstimulationpattern. Importantly,thesparse,pattern-separatednatureofthehippocampalrepresentationsensures thatonlyasmallproportionoftheentirepopulationofunitswouldprecessforwardinthetheta oscillation,whichinturnensuresthatlearningisselective.

Theobservationcentraltotheconundrumweseektoresolve,thatgammasynchronizestothetain the hippocampus during episodic memoryencoding, is critical to the phase advancement argumentjustmade.Thatis,thespecificpresenceofstronggamma-to-thetasynchronyprovides themechanismbywhichfiringofdrivenunitsstepsoutandforwardinthethetacycle,enabling relevantsynapsestobeselectivelysubjecttoLTP.Inthissense,onecouldarguethat gamma-to-thetasynchronizationiskeytothedistinctivelearningcapacityofthehippocampuswhilealpha/ betadesychronizationiskeytotheneocortex'scapacitytorepresentinformation.

Box1.MechanismsforTheta-Phase-DependentSynapticModifications

WeenvisagethreepossiblewaysinwhichadvancementoffiringinthephaseofthetacouldinduceincreasedLTP. ThereisconsiderableevidencethatthestrengthofLTPinthehippocampus(orindeedwhetherthereisLTPorLTD) varieswiththephaseoftheta[53–55].Invivo[55]aswellasinvitro[53]studiesshowedthatstimulationduringthe positivepeakofthetafavorsLTP.Notably,thispositivethetapeakinCA1iseffectivelythehyperpolarizingphase(i.e., inhibitoryformosthippocampalpyramidalcells[29,51]).Together,theseresultsfitwithourmodel,wherecorticallydriven neuronswouldbepushedtofireclosertotheinhibitorythetaphase(Figure2).Accordingly,advancingthefiringofa subsetofunitscouldsimplyplacethoseunitsinaphaseofthetawithstrongLTP.

TheoriesofSTDP[68]holdthattheorderofspikingdeterminesthedirectionofsynapticchange.Inparticular,asynapse increasesinstrengthifthepresynapticunitspikesbeforethepostsynapticunit.Thisprovidescausalitytolearning;thatis, earlierspikefiringsuggeststhatthepresynapticunitiscontributingtodrivingthepostsynapticunittofire,indicatingthat thesynapseshouldincrease.However,forsuchlearningtocausesustainedLTPofasynapse,aconsistentpre–post orderoffiringneedstoobtain.Thus,itcouldbethatadvancingthefiringofstimulation-specificunitsinthehippocampus introducesasystematicordertothatfiringonwhichSTDPcanact.

ThereareformsofHebbian learningthatincorporateanormalizationfortheamountofweightchangeforeach postsynapticunit(e.g.,[56],seepp.289,290,and291).Asaresult,aboundedformofHebbianlearningisobtained, accordingtowhichweightscannotbecomearbitrarilylarge.Aconsequenceofthenormalization,however,isthat competitionisgeneratedbetweenweightchangesonlinksenteringapostsynapticunit,withchangesbeingbiggerif feweroftheseweightsaresubjecttochange.Thiswouldoccurwhenfewerpresynapticunitsareactiveandwould generategreaterLTPforsynapsesthatchangewhenfiringisselective(i.e.,duringaninhibitoryphase).Thisisexactly whattheadvancementofspikingforstimulation-sensitiveunitstowardtheinhibitorythetaphase,asweareproposing, woulddo:itwouldrestrictthesetofpresynapticunitsthatarefiring,ensuringgreaterLTPontheirspecificsynapses. Similarly,theamountofLTDforstimulation-unspecificunitswouldberathersmall,evennegligible.

CaveatsandLinks toOtherMemoryModels/Theories

Oneseeminglycounterintuitiveconsequenceofourframework,andoftheanimalworkitbuilds on[53–55],isthatbothLTPandlong-termdepression(LTD)(i.e.,learningandforgetting)occur sequentiallyinanalternatingmannerdependingonthetaphase.Thiswouldbeaproblemforour frameworkiftheamountofthepositiveweightchangeatanysinglesynapseduringLTPwere equaltotheamountofthenegativeweightchangeatasynapseduringLTD.However,thisis unlikelytobethecase.Inourframework,LTDoccursforsynapsesof‘irrelevant’units;thatis, unitsthatdonotcurrentlyreceiveinputfromtheircorticalcounterpartsandthereforefireduring thethetatrough(asrecordedinCA1/CA3).Notably, mosthippocampal pyramidalcellsare activeduringthattime[51];consequently,theactualweightchangethatisappliedtotheseunits canbeassumedtobefairlysmall(Box1)[56].Thus,ourframeworkpredictsaweakamountof forgettingovertime,especiallyforunitsthatarenotreactivated,whichresonateswellwiththe factthatmemoriesfadeovertime.Moreover,thisassumptionisalsoinlinewithaplethoraof findingsshowingthatreactivationofmemoriesduringwakefulness[57]andsleep[58] counter-acts this forgetting. This aspect of our framework also resonates well with recent ideas highlightingtheroleofforgettingasahighlyorganizedprocessthatkeepsourmemorysystem flexible,goaloriented,andorganized[59,60].

Inthepresentedframework,wefocusedontheinteractionbetweentwoofthemostubiquitous oscillatorydynamicsinthebrain,thetaoscillationsinthehippocampusandalpha/beta oscil-lationsin the neocortex. Therefore we did not include a detaileddescription of how theta oscillationsregulateencodingandretrievaldynamicswithinthedifferenthippocampalsubfields.

Box2.PredictionsoftheSynchronization/DesynchronizationFramework(SDF)

Thehere-presentedSDFmakesseveralpredictions,whicharelistedbelow.

Thelevelof corticaldesynchronization should correlatepositively withcorticalinformation coding; thatis,more desynchronizationshouldleadtostrongerfidelityofneuralrepresentationsasdetectedwithmultivariatepattern-analysis methods.

Duringencoding,phaseprecessioninthehippocampusshouldcorrelatewithmemoryformation;thatis,itemsthatare laterrememberedshouldshowstrongerphaseprecessionthanitemsthatarelaternotremembered.Thethetaphase shouldalsodiscriminatebetween stimulus-selectiveandstimulus-unselective neuronsduringboth encoding and retrieval.

Desynchronizationinthecortexhasadownstreameffectonthestimulus-selectiveneuronsinthehippocampusthat shouldexpressitselfin:(i)phaseprecessionofneuronsinthehippocampus;(ii)highertheta/gammacross-frequency coupling;and(iii)highermetabolicdemands[blood-oxygen-leveldependent(BOLD)]signalinthehippocampus. Arelativelysmallproportionofhippocampalneuronsshouldprecessforwardduringencoding,reflectingtherelatively sparsenatureofhippocampalrepresentations.

Thesepredictionscanbetestedinmultiplewaysusingvariousapproachesandrecordingtechniques.Onatheoretical level,thepredictionscanbetestedincomputationalmodelsthatcombinebasicideasofCLStheorywithoscillationsand neuralfiringintheneocortexandhippocampus(see,forexample,[52]).Implementingtheproposedsynchronization/ desynchronizationmechanismsinsuchmodelswillshowwhattypeofbehaviorcanbemodeledand,moreimportantly, whattypeofbehaviorcannotbemodeled.Thereby,computationalmodelingwouldrevealthelimitsofourframework.On anempiricalbasis,thesepredictionscanbetestedusinginvasiverecordingmethodscombininglocalfieldpotential(LFP) withsingle-unitrecordingsinanimalmodels(i.e.,rodentsandmacaques)andhumans(i.e.,epilepsypatientsundergoing presurgicalmonitoring).Asthecoreideaofourframeworkreliesonaninteractionbetweenthehippocampusand neocortex,itiskeytonotonlyrecordinthehippocampusortheneocortexbuttorecordhippocampalandneocortical activitysimultaneously.Finally,someofthepredictionscanalsobetestedusingnoninvasiverecordingmethodssuchas EEG/MEGorEEG–fMRI.Recentdevelopmentsinsourcelocalizationhavemadeitpossibletorecord electrophysio-logicalsignalsfromtheMTL[11].AlthoughitmightbedifficultforEEG/MEGstudiestodisentanglehippocampalfrom otheractivitywithintheMTL(e.g.,parahippocampalgyrus,EC),oscillatoryinteractionsbetweentheMTLandthe neocortexinprinciplecanbestudied.Additionally,multivariateanalysisapproachesusingtemporalandspatialpattern analysis can be utilized to test for the representation of information, which can then be linked to cortical desynchronization.

Thesemechanismsaredescribedingreatdetailinothertheoreticalpapers(e.g.,[29])andhave beenimplementedinrecentcomputationalmodels[52].Notably,althoughtheexact mecha-nismsofhowLTP/LTDandthetaphaseprecessionareimplementeddifferslightly,thebasic characteristicsofourframeworkandthesepreviousstudiesareverywellinlinewitheachother. Ingeneral, itwouldbehelpfulifmorecomputationalmemorymodelstake intoaccountthe intrinsicoscillatorybehaviorofthebraintorelatetheelectrophysiologicalpatternstomemory processes.Similarly,ourunderstandingofthemechanismsthatneurallydrivedesynchronization inthecortexduringmemoryformationisratherlimitedtodate.Previousanimalstudiesinthe attention[61]andmotor[62]domainsuggestpossiblecandidatemechanisms(i.e., thalamo-corticalinteractions),butwhetherthesecanbeextendedtomemoryremainstobeinvestigated.

Asforanytheoreticalframework,therearepotentiallimitationsandchallengesthatneedtobe considered.Forinstance,nohumandatacurrentlyexistthatsupportsthathippocampaltheta oscillationsregulateLTP/LTDinasimilarwayastheydoinrodents[53–55].Similarly,although placecells[63]andgridcells[64]havebeendiscoveredrecentlyinhumans,nostudyhasyet shownthephenomenonofphaseprecession inthehumanhippocampus. Anymechanistic frameworkthataimstoexplainepisodicmemoryneedstoaddresshowsynapticmodifications occur ata rapidtimescale. The theta-mediated LTP/LTDmechanisms observed inanimals provide amechanism thatfulfilsthese criteria. However, STDP (Box1),which, it has been argued,operatesonlongertimescales,mightbeamorequestionablemechanismforepisodic memoryformation. Interestingly, animal studiessuggest thatfor STDP protocolsto reliably induce LTP within a few seconds the stimulation has to occur in the theta rhythm [65], suggestinganinteractionbetween STDPandthetaoscillations,which wouldthenbeinline withtheframeworkproposedhere.

ConcludingRemarks

Theaimofthisopinionarticlewastoprovideamechanisticframeworkwithinwhichwecan understandthedifferentrolesofneuralsynchronizationanddesynchronizationintheserviceof episodicmemories.Linkingfindingsfromtherecentelectrophysiological literatureand inves-tigationsofoscillatorycorrelatesofepisodicmemoryformationandretrievalwiththewell-known CLSframework, weargue thathippocampal theta/gamma synchronizationisnecessaryfor bindingepisodeswhereascorticallow-frequencydesynchronizationisnecessarytorepresent thecontentoftheseepisodes. Thisframeworkmakesseveralclear predictions(Box2) and raisesimportantopenquestions(seeOutstandingQuestions)thatshouldbetestedinthefuture.

Acknowledgments

S.H.thankshiscollaboratorsfromtheCognitionandOscillationsLab,inparticular(inalphabeticalorder)Marie-Christin Fellner,TobiasStaudigl,andGerdWaldhauser,whoprovidedmostoftheempiricalgroundworkthatledtothisopinion article.ThisworkwassupportedbygrantsfromtheDeutscheForschungsgemeinschaft(HA5622/1-1),theEuropean ResearchCouncil(GrantAgreementno647954),andaSirHenryDaleFellowshipjointlyfundedbytheWellcomeTrustand theRoyalSociety(107672/Z/15/Z).

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