Bridging the gap between striatal plasticity and learning

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Bridging the gap between striatal plasticity and learning

Elodie Perrin, Laurent Venance

To cite this version:

Elodie Perrin, Laurent Venance. Bridging the gap between striatal plasticity and learning. Current

Opinion in Neurobiology, Elsevier, 2019, 54, pp.104-112. �10.1016/j.conb.2018.09.007�. �hal-02055666�

Bridging

the

gap

between

striatal

plasticity

and

learning

Elodie

Perrin

and

Laurent

Venance

Thestriatum,themaininputnucleusofthebasalganglia, controlsgoal-directed behaviorandprocedurallearning. Striatalprojectionneuronsintegrateglutamatergicinputs fromcortexandthalamustogetherwithneuromodulatory systems,andaresubjectedtoplasticity.Striatalprojection neuronsexhibitbidirectionalplasticity(LTPandLTD)when exposedtoHebbianparadigms.Importantly,correlativeand evencausallinksbetweenprocedurallearningandstriatal plasticityhaverecentlybeenshown.Thisshortreview summarizesthecurrentviewonstriatalplasticity(witha focusonspike-timing-dependentplasticity),recentstudies aimingatbridginginvivoskill acquisitionandstriatal plasticity,thetemporalcredit-assignmentproblem,andthe gapsthatremaintobefilled.

Addresses

1_{CenterforInterdisciplinaryResearchinBiology,Colle`gedeFrance,} INSERMU1050,CNRSUMR7241,LabexMemolife,75005Paris,France 2

Universite´ PierreetMarieCurie,ED158,Paris,France Correspondingauthor:Venance,Laurent

(laurent.venance@college-de-france.fr)

CurrentOpinioninNeurobiology2019,54:104–112

ThisreviewcomesfromathemedissueonNeurobiologyoflearning andplasticity

EditedbyScottWaddellandJesperSjo¨stro¨m ForacompleteoverviewseetheIssueandtheEditorial Availableonline12thOctober2018

https://doi.org/10.1016/j.conb.2018.09.007

0959-4388/_ã2018TheAuthors.PublishedbyElsevierLtd.Thisisan openaccessarticleundertheCCBYlicense(http://creativecommons. org/licenses/by/4.0/).

Introduction

The striatum receives topographic glutamatergic

affer-entsfromallcorticalareasandfromsomethalamicnuclei [1](Figure1).Itisanimportantsitefor actionselection

andproceduralmemoryformation[2].Sincethe

demon-strationbyYinandcoll.[3]ofstriatalplasticityfollowing

acquisition of a procedural skill, several studies have

extendedthispioneeringworkbyassessingstriatal plas-ticityacross various learningtasks. This review aimsat givingthecurrentviewonexvivostriatalplasticityinthe

light of recent studies evidencing correlative or causal

linkbetweeninvivolearning andstriatalplasticity,ina physiologicalcontext.Here,‘exvivo’referstobrainslice

recordings from animals subjected to training or

treat-ment, as opposed to studies in which brain slices are

examined in naı¨ve animals to reveal plasticity

mechanisms. Striatal plasticityhas been a controversial

fieldforatleasttwodecadesbecauseofitsgreatvarietyof results(reviewedinRefs.[4–8])andtheriseof

back-and-forthinvestigations betweeninvivoand exvivo bringa

uniqueopportunityforabetterunderstandingofstriatal

plasticity, and most importantly for bridging the gap

betweenlearning andstriatalplasticity.

Striatal

complexity

Threemain reasons account for the diversityof results

concerning striatal plasticity: the induction protocols

(rate-coded versus time-coded and Hebbian versus

non-Hebbian),thestriatalheterogeneity,andsome

tech-nicalissues.Somecriticaltechnicalissuesaretheageof theanimals,thesliceorientation(coronalversussagittal versushorizontal), thelocation of thestimulation elec-trode(cortexversuscorpuscallosumversusstriatum)and therateoftheextracellularandintracellularcomponent

washout(LTPbeingoptimallyobservedundersufficient

ratesofsuperfusionandhighresistancewhole-cell

record-ings). Intermingled anatomo-functional compartments

and neuronal units constitute the basis of the striatal

heterogeneity: dorsolateral and dorsomedial striatum

(DLS and DMS), and direct and indirect trans-striatal

pathways,justtocitethemainoneswhichcanbeassessed

during recordings (Figure 1). DMS and DLS receive

inputs from associative and sensorimotor cortices and

encodefor goal-directed behavior and skill acquisition,

respectively[3,9].Inrodents,striatalprojectionneurons (SPNs)belongeithertothedirect(d-SPNs)orindirect

(i-SPNs)trans-striatalpathwaysandshowdistinct

dopami-nergicreceptorexpression,D1-class andD2-class

recep-tors,respectively[10].Recentstudiesshowthatd-SPNs

andi-SPNsareengagedinacomplementaryand

coordi-natedmannerforactioninitiationandexecution[11–13].

DMS/DLSand d-SPNs/i-SPNsaredistinguished inthe

majorityoftheplasticitystudies.Nevertheless,thethird

level of striatal structuration, the striosomes (patch)/

matrixcompartments[14],remainstobemore

documen-ted for striatal plasticity expression. Another

compart-ment has been recently added, the annular

compart-ments, surrounding the striosomes [15] (Figure 1).

Functionally, substance P increases dopamine release

within the striosomes but decreases it in the annular

compartment, and leaves dopamine unmodified in the

matrix [15,16] suggesting distinct neuromodulation of

striatalplasticityamongthesecompartments.

Here,insteadofrecapitulatingtheplasticityobservedin brainsliceswiththesignalingpathwaysatplay(reviewed inRefs.[4,6–8]),weoptforanotherangle:wefirstpresent recentinvivostudiesestablishingcorrelativeandcausal

links between learning and striatal plasticity, and then

from these studies we discuss the conditions of

emer-gence ofbidirectionalstriatalplasticity.

From

learning

to

striatal

plasticity

Striatalplasticityhasbeenassessedduringgoal-directed

behavior,and across theearlyand latephases of

proce-durallearning.Theanalysisofvariousparameters,usedas proxiesforsynapticplasticity,hasbeenachievedeitherin vivoduringbehavioraltasks(analysisofthefiringrateand activity coherence [9,13,17,18,19,20]; measurement of

opto-induced LFP [21]), or ex vivo after behavioral

training (NMDAR/AMPAR ratio [3,22,23];

spontane-ous-EPSCs: [24]; saturation/occlusion plasticity tests

[25,26]) (Figure 2). The link between theacquisition/ consolidationofprocedurallearningandstriatalplasticity wasfirstshownbythecombinedanalysisofinvivofiring

rate andexvivoNMDAR/AMPARratio frommice

sub-jected to an accelerating rotarod [3]. In vivo analysis

showsthatDMS,butnotDLS,displaysincreasedactivity

during the earlyphases of skillacquisition whereas the

reverse picture is obtained during the consolidation

phases,thatisDLSdisplaysincreasedfiringactivitywhile

DMS is back to naı¨ve levels. Interestingly, NMDAR/

AMPAR ratio variesonly in DLS for the consolidation

phase [3], pointing to the non-NMDAR natureof the

corticostriatalplasticityin DMSfortheearlyphases.Ex

vivo saturation/occlusion experiments after extended

trainingshowLTPati-SPNsbutnotatd-SPNs,

suggest-ingthatLTPisinducedatd-SPNsfortheconsolidation

phase [3]. Ex vivo AMPAR/NMDAR ratio analysis

revealed that during T-maze task, LTP is engaged

(but not LTD)in DMSin theearlyphase while LTD

(but notLTP)isinvolvedin thelatephase, whereasin

DLS,LTDisinvolvedonlyinthelatephase(butLTPin

DLS wasnotexplored)[25].After habitlearningusing

thelever-pressing task(correspondingtothelate phase

described in [3,25]), ex vivo spontaneous-EPSC are

specifically decreased in DLS i-SPNs (indicative of a

postsynaptic LTD)[24].In aserial order task, learning BridgingthegapbetweenstriatalplasticityandlearningPerrinandVenance 105

Figure1

Sensorimotor cortices

Associative

cortices _cortices Limbic

D2-SPN SNr SNc GPe D1-SPN Corpus callosum Late phase of skill acqquisition / habits Early phase of skill acquisition / goal directed STN EP Striatum Striosomes Dorsomedial striatum Dorsolateral striatum Direct pathway Indirect pathway

Current Opinion in Neurobiology

Schematicrepresentationofthestriatalheterogeneityandtheanatomo-functionalcompartmentsofthedorsalstriatum.

Schematicrepresentationofthedirectandindirecttrans-striatalpathwaysofthebasalganglia.Striosomesareshownwithblackdotsdistributed betweenthedorsolateralstriatum(blue)andthedorsomedialstriatum(orange).Groupedblackdotsrepresentstriosomessurroundedbythe annularcompartment(redline,[15]),whereasisolatedblackdotsillustratetheexo-patch[14].StriosomalSPNsmainlyprojecttoSNcwhereas SPNsfromthematrixbelongtothedirectorindirectpathway,identifiedrespectivelybytheexpressionofD1andD2receptors.Thedirectand indirectpathwaysarerepresented,respectively,ingreenandpurple.GPe,externalsegmentoftheglobuspallidus;EP,entopeduncularnucleus; STN:subthalamicnucleus;SNr,substantianigraparsreticulata;SNc,substantianigraparscompacta.

ofaprecisesequencedependsond-SPNsintheDLSand

inducesanincreaseoftheAMPAR/NMDARratioattheir

synapses(butnotati-SPNs)[23].Inagoal-directedtask,

exvivoAMPAR/NMDARratioanalysisrevealsopposing

plasticity in d-SPNs and i-SPNs in DMS, while no

modificationisobservedinDLS[22].Duringthe

learn-ingofasensorydiscriminationtask,LTPisdetectedin

vivoandexvivoin theauditorystriatum[21].

Learningabstractroutines,suchasneuroprostheticskills, requires corticostriatal plasticity as revealed by in vivo

firing coherence between motor cortex and DLS

[9,19,20].FiringrateinDLSandcoherenceinthetheta

bandbetweenmotor (M1)cortexandDLS increases in

the late phase of volitional modulation of M1 activity

[9,19];thesephenomenaareNMDAR-mediatedsince

nochangeoccursin NMDAR-knock-outmice[19].In

addition, firing activity patterns of neuronal ensembles

thattriggermaximaldopaminereleasealongtrialsofthe

neuroprosthetic task are selected and progressively

shapedforoptimizedreinforcementlearning[20].

It remains to get the full picture of the plasticities

successively engaged in d-SPNs and i-SPNs in DLS

andDMSfromgoal-directedto habitformation.

From

striatal

plasticity

to

learning

A reverse strategy consists in triggering LTP or LTD

duringabehavioraltasktoinvestigatecausalitybetween

synapticplasticityandbehavioralmodifications.

NMDAR-LTPandendocannabinoid-LTDwereinducedby

presyn-apticoptogenetic-stimulationassociatedwithoptogenetic

SPNdepolarizationinDMSinoperantalcohol

self-admin-istration[27].LTPandLTDinductionpromote respec-tivelyalong-lastingincreaseanddecreasein

alcohol-seek-ing behavior [27]. This demonstrates a causal link

betweenthepolarityofaninducedplasticityanditseffect

on behavior. Moreover, this strategy allows to test the

plasticitiesidentifiedinbrainslicesinSPNsor

interneur-ons, and to investigate theirin vivo impact onsynaptic

transmission[21]orbehavior[27].

Emergence

of

bidirectional

striatal

plasticity:

Hebbian

mode

is

the

key

TheobservationthatLTPcanbeinducedinvivousinga

Hebbian paradigm changed the view of a LTD

domi-nance in the striatum [28–30]. Since then, numerous

studieshavereportedLTP(aswellasLTD)depending

onthestimulationprotocol(forreviewsseeRefs.[4–8]).

Nevertheless,striatalLTPstill appearsmore capricious

to induce than LTD. Interestingly, following in vivo

learning tasks, LTP is systematically detected

[3,21,23,25,26].Obviously,theinductionphase

mat-tersandLTPappearsmorelikelyinduceduponHebbian

protocols. Hebbianplasticity relies on the

quasi-coinci-dent activity on either side of the synapse and

spike-timing dependent-plasticity (STDP) protocols aim at

mimickingsuchaHebbianmodebypairingpresynaptic

stimulations with postsynaptic back-propagating action

potentials [31,32]. Most of the striatal STDP studies

report bidirectional (LTP and LTD) plasticity [33–

39,40,41–44](Figure 3).Note thatinrate-coded

proto-cols,theremovalofexternalmagnesiumorpostsynaptic

depolarization for inducing LTP aims at mimicking a

Naive Goal-directed behavior Habit formation Extracellular recordings: - firing rate - coherence - opto-LFP Two-photon imaging: - neuronal maps - structural plasticity In vivo continuous recordings in behaving rodents Ex vivo discontinuous recordings in brain slices Patch-clamp:

- intrinsic membrane properties - AMPAR/NMDAR ratio - plasticity saturation / occlusion

Two-photon imaging: - structural plasticity

Patch-clamp GRIN lens imaging

Fiber photometry

Current Opinion in Neurobiology

Strategiesusedforevaluatingstriatalplasticityduringlearning.

Illustrationoftheanalyticalmethodsandparametersusedtoassesssynapticandstructuralstriatalplasticityduringprocedurallearning.Invivo electrophysiologicalextracellularrecordings,two-photonimaging,GRINlensimagingandfiberphotometryallowcollectingdataallalongthe learningphasesofbehavioraltasks(continuousrecordingsschematizedbythehorizontalpinkarrow).Attimepointsofinterestduringthe behavioraltasks(discontinuousrecordingsschematizedbythebluedots),exvivopatch-clampandtwo-photonimagingonacutebrainslicescan beusedtotestwhethervariousformsofstriatalplasticitywereinducedinvivo.Examplesofinvivoandexvivorecordingsforstriatalplasticity assessmentduringprocedurallearningcanbefoundin[9,13,17,18,19,20,21,68]and[3,22,23,24,25,26],respectively.

back-propagatingactionpotential[4,5].Similarly, manip-ulating dopamine levels(or activityof D1/D2Rs) allows

adjusting the cellular excitability, which brings striatal

neurons more prone to displayHebbianplasticity. The

importanceoftheHebbianmodeforinducingLTPhas

beenfurtherdemonstratedinDMSsinceHebbian

high-frequencystimulation(i.e.stimulationcoupledwith

opto-genetic postsynaptic depolarization) induces

NMDAR-LTP, whereasnon-Hebbianhigh-frequencystimulation

inducesendocannabinoid-LTD[3,9].

Therefore, we focus here on striatal STDP [33–

39,40,41–46], which is a typical Hebbian paradigm.

Bidirectional plasticity has been observed following

STDP,thatisLTDandLTPwereobserveddepending

ontheorderofpairings[33–36,38,39,41,43,47].

Interest-ingly,byvaryingthenumberand/orfrequencyofSTDP

pairingsacomplexplasticitylandscapeisobtained:from

the‘classical’bidirectionalNMDAR-LTPand

endocan-nabinoid-LTDfor 100pairings[34,36],to

endocanna-binoid-LTP for a lower number (10–15) of pairings

[39,40,44,47] (Figure 3). It remains to determine the

role of endocannabinoid-LTP in vivo and how it

com-bineswith NMDAR-LTP.

Itshouldbenotedthattheplasticities observedinvitro (brainslices)andinvivorelatetodistinctphases.Studies

using brain slices investigate plasticity up to one hour

post-protocol, thus referring to the early plasticity,

whereas AMPA/NMDAR ratio and occlusion/saturation

analysis are performed 1–3days after thelearning task,

corresponding to the long-lasting phase of plasticity.

Therefore, conclusions drawn from in vitro and ex vivo

/invivoplasticityarenotstraightforward,anditremains

to determine whether similar signaling pathways are

engagedduringearlyandlateplasticityphases.

InHebbianplasticity,theassociationoftwofactors

con-trols the synaptic strength, that is two inputs (and/or

activity patterns) on the presynaptic and postsynaptic

elements,withtheadditionofathirdfactormodulating

plasticity [48]. Here, recent studies concerning GABA

and dopamine acting as third factors for striatal STDP

helpto clarifytheplasticity debate.

The conflictingobservationsofHebbian[34,35]or anti-HebbianstriatalSTDP(inbrainslices[33,36,39,41,45]or invivo[37])areexplained bytheuse(or lackof use)of

GABA antagonists [38,43]. The appearance of tonic

GABAergic signaling during development gates STDP

polarity, promoting anti-Hebbian STDP in the adult

striatum [43]. It remains to investigate pathological

effects of tonicGABAergic transmissionin striatal

plas-ticityandprocedurallearning.

BridgingthegapbetweenstriatalplasticityandlearningPerrinandVenance 107

Figure3 LTP LTD STDP experiments Model 0 25 50 75 100 30 15 0 -15 -30 100 200 50 100 250 100 200 0 100 Number of pairings (#) Δ tSTDP (ms) 50 0 50 100 Wtotal (%) Wtotal (%) W total (%) NMDAR-LTP eCB-LTD eCB-LTP 1 2 3 1 3 2 Number of pairings (#)

Current Opinion in Neurobiology

Endocannabinoid-mediatedandNMDAR-mediatedLTPandLTDareinduceddependingonthenumberofpairingsinaHebbianparadigm (STDP).

Changesofthesynapticweight(Wtotal)whenthenumberofpairingsandtherelativetimingbetweenpresynapticandpostsynaptictiming(DtSTDP) werevaried.Thecolor-mapdepictsthesynapticplasticitypredictedbyamathematicalmodel(from[36]andconfirmedbyexperiments(illustrated bythecolor-codedpoints)(adaptedfrom[35and36]).Asmallnumberofpost-prepairings(10–15)producesendocannabinoid-LTP(eCB-LTP), whereasalargernumberofpairings(_>75)inducedNMDAR-LTP;forpre-postpairings,endocannabinoid-LTD(eCB-LTD)isinducedfrom 50pairings.Thecolorbarindicatesthecolorcode.Intherightpanels,theblacklinesrepresentthesimulationresultsandtheblackcircles illustrateexperimentalresults.

learning [49]. StriatalHebbian plasticityrequires dopa-mine(brainslices[34,35,50];invivo[37,42]).Adendritic

spineenlargementandanincreaseofcalciumoccurwhen

dopamineisreleasedconcomitantlyorafter(1s)

gluta-mate [51] allowing in vivo STDP [37,42]. There are

conflicting results concerning the involvement of D1R

versusD2RinSTDP(post-preLTDandpre-postLTP

requires D1R-activation but not D2R-activation [35];

LTPin d-SPNs is D1R-mediated and LTD in i-SPNs

is D2R-mediated [34];reviewed in Refs. [6–8]). In the

absenceofdopamine(andwithGABAantagonists),

D1-SPNsshowLTDinsteadofLTPwithpre-postpairings,

whereasD2-SPNsdisplayLTPforbothpost-preand

pre-postpairings[34].Methodologicaldifferencessuchasthe locationofthestimulationelectrode(leadingtodifferent dopaminerelease[52])orthenumberandfrequencyof pairedstimulationscouldaccountfor differential activa-tionofD1RandD2Randspecific-regulationofthe

back-propagatingactionpotential[5].Thisisparticularly

illus-trated by the fact that LTP induced by theta burst

optogenetic stimulation is dependent on presynaptic

NMDARandBDNF[53]butnotondopamine,whereas

LTPinducedwithelectricalhigh-frequencystimulation

isgenerallydopamine-dependent(reviewedinRefs.[4–

8]).

In future studies it will be crucial to investigate in

behavinganimalstheactionofthirdfactors[48]in

Heb-bian learning, like for the eligibility traces (see next

chapter).

Solving

the

temporal

credit-assignment

problem

with

eligibility

traces

and

striatal

plasticity

The temporalcredit-assignment problem questions the

temporal link between the reward and the preceding

action to allow reinforcement learning [49]. The

exis-tenceofeligibilitytraces,originallybroughtby computa-tionalmodels[54–56],helpstosolvethetemporal

credit-assignment problem. Eligibility tracesare synaptic tags

induced by Hebbian learning and are transformed into

synapticplasticitybytheretroactiveeffectof neuromo-dulators.Theoretically,eligibilitytracesallow tokeepa

synaptic trace from the learning sequence, but not to

promoteplasticityperse,unlesstherewardsignaloccurs beforeextinctionof eligibilitytraces(Figure 4).

There-fore, eligibility traces temporally link the learning

sequence with the reward allowing the induction of

reinforcement learning via striatal plasticity. Structural plasticity,used as aproxyfor synaptic plasticity,occurs

exclusivelywhendopaminereleasehappens0.3–2safter

anSTDPparadigm[51](Figure4).D1Randdendritic

PKAactivationallowtobridgetheaction(glutamatergic

inputs) and the subsequent reward (dopamine); PKA

activationisshort-lived becauseofthehigh

phosphodi-esterase-10Aactivityindistaldendrites[51].Dopamine

exerts also retroactive effects of on existing plasticity sincedopaminedelivered2saftercell-conditioning

pro-tocol (and importantly not before or during protocol)

convertsLTDinLTP[42,52].

Therefore, the expression of eligibility traces and the

delivering of a distal reward allow the expression of

plasticity [51] or even the conversion of a form of

plasticityintoanother[42,52].

Future

directions

Amongthestriatalcompartments,thestriosomeandthe

matrix remain the less documented in terms of

Eligibility trace 3 1 2 4 Pyramidal cell Plasticity Striatal projection neuron Learning sequence Temporal credit- assignment Reinforcement learning Eligibility trace

Teaching signal (reward)

Dopamine Synaptic weight Dopa-minergic neuron Hebbian paradigm Dopamine Eligibility trace Synaptic weight

Current Opinion in Neurobiology

Eligibilitytracesbridgethegapbetweenlearningsequenceand subsequentrewardtopromotereinforcementlearning. Illustrationofreinforcementlearningallowedbyshort-livedeligibility tracesatcorticostriatalsynapses.Eligibilitytracesaretriggered followingHebbiansequence,whichpersedoesnotinduceplasticity (illustratedherebytheflatgreylinecodingforthesynapticweight). Theseeligibilitytraces(constitutedbyPKAactivitycontrolledby phosphodiesterase-10Aind-SPNs,asreportedby[45])canbe transformedbeforetheirextinctionintoplasticity,iftheteachingsignal (dopamineinstriatum)isdeliveredduringthemaintenancephase(3) oftheeligibilitytraces;Noplasticityisinducedifdopamineisreleased eitherbefore(1),duringthebuild-up(2)orafter(4)eligibilitytraces (verticalbarsillustratetheneuronalfiring).

physiological role in striatal function. Thanks to new

markers[14],invivotwo-photonmonitoringduringtask

performance showed overlapping responses of neurons

belongingtothestriosomeandthematrix,with

differen-tial firing activity for reward coding [57]. Because of

striosome/matrix differential inputs and outputs [14],

dopaminergic [15,16] and endocannabinoid [58] regula-tion,specific-plasticitieswithdifferentialmodulationare

expected tooccur.

AlthoughdifferentialpolarityofSTDPinGABAergicand

cholinergic interneurons has been shown [59], the full

pictureoftheinterplayofplasticitiesatstriatalcircuitsis

just beginning to be understood. It remains to further

investigatetheunderlyingmechanismsoftheplasticities

occurring at the lateral connections [60,61] such as

interneuron–interneuron,interneurons–SPNsandSPN–

SPNs. Forexample,astudyshowinganLTDat

inhibi-tory synapses between SPN–SPNs and fast-spiking

interneuron–SPNsdemonstratesthatdistinct

endocanna-binoid signaling pathways are engaged depending on

membranepotentials(upversusdownstates)[62].

Addi-tionally,withthediscoveryoflong-rangeprojecting

cor-ticostriatalGABAergicneuronsmodulatingmotoractivity

viadifferentialactionond-SPNsandi-SPNs[63],itwill

be important to take into account the fact that cortical

activationleadstothedirectreleasenotonlyofglutamate

but also of GABA into the striatum. This changes our

view on the striatal excitation-inhibition balance, and

begs the question of whether plasticity, if any, occurs

betweentheselong-rangeGABAergicneuronsandthe

d-SPNsandi-SPNs.

Determining the conditions of emergence of plasticity

helps to better understand the striatal capability for

storage and recallofinformation. Noisy STDPpairings

showsthatplasticityrobustnessdependsonthesignaling

pathways:NMDAR-LTP is more fragilethan

endocan-nabinoid-plasticity [44]. Interestingly, resistance of

NMDAR-tLTPtonoisypatternsisincreasedwithhigher

frequency or numberof pairings.Invivo Hebbian

plas-ticity appears as a multivariate function of the number

and frequencyof pairings,but alsothevariability ofthe spiketiming.In-vivo-likeconditionsforstriatalplasticity, usingnaturalisticfiringpatternsof

cortical/thalamic/stria-tal neurons recorded in learning tasks still need to be

explored. Although STDPaims at mimicking Hebbian

learning,reservationswereexpressedaboutits physiolog-icalvalidity[64].Input-timing-dependentplasticity

con-stitutesaHebbianupgradeofSTDP.Itconsistsinpaired

activation of presynaptic inputs (distinct cortical areas

and/or thalamic nuclei, for example), leading to

sub-threshold or suprathreshold activity in the postsynaptic

neuron,asperformedrecentlyinavianbasalganglia[65].

Calciumimagingofi-SPNsandd-SPNsrecordedexvivo

just after different phases of an operant lever-pressing

taskrevealedthati-SPNsfiredbefored-SPNsinthe

goal-directed phase, whereas thereversepictureisobserved

during thehabitual phase[13].GABAergic fast-spiking

interneuronsbecomemoreexcitableinhabitualbehavior

[66,67]andcouldaccountforthereversetemporalorder

of firing between d-SPNs and i-SPNs. It remains to

examineplasticityinDLSacrossgoal-directedtohabitual

behavioratd-SPNsandi-SPNs,andalso inGABAergic

interneurons. Also, most of the studies focused on the

involvementofNMDAR-LTPinlearning.Basedonthe

diversityofplasticitiesrevealedbystudiesinbrainslices (Figure 3),one needs to evaluate therole of the endo-cannabinoid-LTDand-LTP[39,40,47]acrosslearning.

Supporting thisview,arecent studyshowedthat

endo-cannabinoidssetthetransitionbetweengoal-directedand habit formationvia the control of cortico(orbital frontal cortex)-striatal synaptic weight [68]; the nature of the

endocannabinoid plasticity at play at these synapses

allowing the shift between goal-directed behavior to

habitsremainsto bedetermined.

Attempts are made to link the complexity of striatal

STDPandgoal-directedbehaviorbyelaborating

compu-tational models (for recent examples see [42,69]). In

futurestudies,itwillbenecessarytoupgradethemodels withrecentexperimentalfindings,suchas,tonameafew, thelateral connections[60,61],thenew facesof striatal STDP[39,40,44,47],thekeyroleofstriatalGABAergic interneuronsinprocedurallearning[66,67]aswellasthe eligibilitytracesfeatures[42,51,52].

Awaytoapproachinvivostriatalplasticityduringlearning istoanalyzethecortico-striatalsynchronousoscillations.

However,becauseoftheabsenceofalaminar

organiza-tion of the striatum, these oscillations can be

contami-natedbyvolume-conductedsignals[70]leadingto

inac-curate interpretation. To overcome this, an elegant

strategy consists in the specific-expression of

channel-rhodopsin incorticostriatal pyramidalcells andthus the

uniquepossibilitytoestimatestriatalopto-LFPchanges

invivoduringskilllearning[21].Anotherstrategyisthe

use of fiberphotometry tomonitor upstreamactivityin

cortical inputs arising from distinct cortices [71] (

Fig-ure 2). In vivo patch-clamp recordings in awake and

behaving(head-fixed)rodentsallowsasingle-cell

resolu-tion and the datacollection of subthreshold and

supra-thresholdevents [72]. Thisapproach hasbeen usedfor

theanalysisofthemembranepotentialdynamicsduring

goal-directed behaviorin d-SPNsandi-SPNs[73].

Although cortico-striatal and thalamo-striatal afferents

equallycontactSPNs[1,74],thethalamo-striatal

plastic-ity has been the focus of a limited number of studies

[1,75–78],despitetheexistenceofabrainslice prepara-tion preserving both cortico-striataland thalamo-striatal

connections [79]. Cortical and thalamic (parafascicular

nucleus) inputs target evenly d-SPNs and i-SPNs

observed in d-SPNs and i-SPNs [75–77]. Major differ-encesbetweencortico-striatal and thalamo-striatal plas-ticityare expectedbecauseofdifferentorganizations of

glutamatergic and dopaminergic synapses on

cortico-striatalandthalamo-striatalpathways[74].Thus, charac-terizing thethalamo-striatal plasticityrepertoire and its putative interactions with cortico-striatal plasticity is of

crucial importance to fully understand the role of the

striatumin goal-directedandprocedurallearning.

Thefield of striatalplasticityhascometo anew agein which theinvestigation of intrinsic, synaptic and struc-tural plasticity at play across procedural learning (from goal-directed behavior to habits) and across the striatal

anatomo-functional complexity has become possible in

behavingrodents.Anewperiodof(constructive)debates

isexpectedsince variousformsofplasticityshouldarise dependingnotonlyonthestriatalcomplexitybutalsoon thebehavioraltaskandtherelatedlearningphase(early versuslate).

Conflict

of

interest

statement

Nothingdeclared.

Acknowledgements

WethankSe´bastienValverdeforcommentsonthemanuscript.Thiswork wassupportedbythe,theAgenceNationalepourlaRecherche (ANR-CRCNSDopaciumcityandANRMopla),Inserm,CNRSandtheColle`ge deFrance.

References

and

recommended

reading

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