Network Organization Unfolds over Time during Periods of Anxious Anticipation

13 Pages·2014·4.91 MB·English

TheJournalofNeuroscience,August20,2014•34(34):11261–11273•11261
Behavioral/Cognitive
Network Organization Unfolds over Time during Periods of
Anxious Anticipation
BrentonW.McMenamin,SandraJ.E.Langeslag,MihaiSirbu,SrikanthPadmala,andXLuizPessoa
DepartmentofPsychology,UniversityofMaryland,CollegePark,Maryland20742
Enteringastateofanxiousanticipationtriggerswidespreadchangesacrosslarge-scalenetworksinthebrain.Thetemporalaspectsofthis
transitionintoananxiousstatearepoorlyunderstood.Toaddressthisquestion,aninstructedthreatofshockparadigmwasusedwhile
recording functional MRI in humans to measure how activation and functional connectivity change over time across the salience,
executive,andtask-negativenetworksandhowtheyinteractwithkeyregionsimplicatedinemotionalprocessing;theamygdalaandbed
nucleusofthestriaterminalis(BNST).Transitionsintothreatblockswereassociatedwithtransientresponsesinregionsofthesalience
networkandsustainedresponsesinaputativeBNSTsite,amongothers.Multivariatenetworkmeasuresofcommunicationwerecom-
puted,revealingchangestonetworkorganizationduringtransientandsustainedperiodsofthreat,too.Forexample,thesaliencenetwork
exhibitedatransientincreaseinnetworkefficiencyfollowedbyaperiodofsustaineddecreasedefficiency.Theamygdalabecamemore
centraltonetworkfunction(asassessedviabetweennesscentrality)duringthreatacrossallparticipants,andtheextenttowhichthe
BNSTbecamemorecentralduringthreatdependedonself-reportedanxiety.Together,ourstudyunraveledaprogressionofresponses
andnetwork-levelchangesduetosustainedthreat.Inparticular,ourresultsrevealhownetworkorganizationunfoldswithtimeduring
periodsofanxiousanticipation.
Keywords: amygdala;anxiety;BNST;executivenetwork;fMRI;saliencenetwork
Introduction sientandsustainedcomponents(Cribbenetal.,2012;Hermans
Anxious states induced by acute, unpredictable stressors have et al., 2014), which have not to date been described. Previous
widespreadeffectsonbrainfunctionduetochangesintheorga- studies of threat used short anticipation periods that limit the
nizationoflarge-scalebrainnetworks(Scottetal.,2006;Kienast abilitytostudysustainedprocesses(Kinnisonetal.,2012;Grupe
etal.,2008;Henckensetal.,2010;Hermansetal.,2011;Thoma- etal.,2013),oruseddynamicstimuli(Alvarezetal.,2011;Her-
sonetal.,2011).Atleastthreenetworksarealteredbyprocessing mans et al., 2011) that make it difficult to determine whether
threat(Pessoa,2013):asaliencenetworkthatincludestheante- effects are truly sustained or if they rely on repeatedly evoked
riorinsulaandthalamus,andrespondstomotivationallysalient transientresponses.Thepresentstudyaimedtounraveltransient
stimuli (Seeley et al., 2007; Menon and Uddin, 2010); a task- and sustained responses and functional connectivity in large-
negative(alsocalled“defaultmode”)networkthatincludesthe scale networks using an instructed threat of shock paradigm.
medialPFCandposteriorcingulatecortex,andisengagedwhen Critically, we tested whether network-level properties change
attentionisdirectedinternallyandduringsomeformsofemo- duringprolongedanxiousstates,incontrasttostaticdescriptions
tional processing (Gusnard et al., 2001; Greicius et al., 2003, ofnetworkorganization(Hermansetal.,2011;Kinnisonetal.,
2009);andanexecutivecontrolnetworkthatincludesfrontopar- 2012).
tietalregions,andisengagedwhencognitivelydemandingtasks Nonhumanresearchindicatesthattheamygdalaplaysarole
requireattentiontotheexternalworld(Seeleyetal.,2007;Van- in transient “fear” responses but the bed nucleus of the stria
haudenhuyseetal.,2011). terminalis(BNST)isimplicatedinsustained“anxious”process-
Trial-by-trialmanipulationsof“anxiousstates”,suchasthe ing(ShiandDavis,1999;Walkeretal.,2003).Accordingly,hu-
anticipationofshock,alterinteractionswithinandbetweennet- manneuroimagingstudiesfoundtransientamygdalaresponses
works(Kinnisonetal.,2012).However,thepatternoffunctional followingcuesforimminentthreatandsustainedresponsesdur-
connectivity during threat anticipation may exhibit both tran- ing prolonged threat in locations consistent with the BNST
(Mobbsetal.,2010;Somervilleetal.,2010;Alvarezetal.,2011).
Critically,howtheamygdalaandBNSTinteractwithotherbrain
ReceivedApril17,2014;revisedJune5,2014;acceptedJuly11,2014.
networksduringtheprocessingofextendedthreatispoorlyun-
Authorcontributions:S.J.E.L.,M.S.,S.P.,andL.P.designedresearch;B.W.M.andM.S.performedresearch;
B.W.M.andS.P.analyzeddata;B.W.M.,S.E.J.L.,M.S.,S.P.,andL.P.wrotethepaper. derstood.Thus,animportantgoalofthisstudywastodetermine
ThisworkwassupportedinpartbytheNationalInstituteofMentalHealth(MH071589toL.P.). howbothstructuresalter“communication”(i.e.,functionalcon-
Theauthorsdeclarenocompetingfinancialinterests. nectivity)betweenbrainnetworksduringthreatprocessing.
CorrespondenceshouldbeaddressedtoDrBrentonW.McMenamin,DepartmentofPsychology,Universityof
Insummary,thepresentstudyusedfunctionalMRItoexplore
Maryland,1147BiologyPsychologyBuilding,CollegePark,MD20742.E-mail:[email protected].
temporalcharacteristicsoftransitioningintoanxiousstatesin-
DOI:10.1523/JNEUROSCI.1579-14.2014
Copyright©2014theauthors 0270-6474/14/3411261-13$15.00/0 ducedbythethreatofshock.Univariatewhole-brainactivation
11262•J.Neurosci.,August20,2014•34(34):11261–11273 McMenaminetal.•TemporalUnfoldingduringAnxiousStates
andnetworkanalyseswereusedtointerrogatetransientandsus-
tainedeffectsduringextendedthreatprocessing.
MaterialsandMethods
Participants
Twenty-fourright-handedparticipants(9male,age19–34years)with
normalorcorrected-to-normalvisionandnoreportedneurologicalor
psychiatricdiseasewererecruitedfromtheUniversityofMarylandcom-
munity.TheprojectwasapprovedbytheUniversityofMarylandCollege
ParkInstitutionalReviewBoardandallparticipantsprovidedwritten
informedconsentbeforeparticipation.
Procedureandstimuli
AninstructedthreatofshockparadigmwasusedduringfunctionalMRI
Figure1. Threatofshockparadigm.
tocreatesustainedanxiousstates.Participantscompletedthetraitpor-
tionoftheSpielbergerState-TraitAnxietyInventory(STAI;Spielberger
etal.,1970)(cid:2)1weekbeforescanning,andthen
completedthestateportionoftheSTAIimmedi-
atelybeforescanning.Experimentersinformed
participantsthatacolored(e.g.,yellow)circleon
thescreenindicatedthattheywereina“threat”
blockandmildelectricshockswouldbedelivered
randomlytotheirlefthand,whereasacircleof
anothercolor(e.g.,blue)indicatedthattheywere
ina“safe”blockandnoshockswouldbedeliv-
ered(Fig.1).Thecolorswerecounterbalanced
acrossparticipants.Eachblockhadtheaverage
durationof60s(range42.5–77.5s).Thewhole
experimentcontainedfourrunsresultinginato-
talof16threatand16safeblocks.Eachthreat
blockcontainedzerotofourelectricshocks,with
fiveof16threatblockscontainingzeroshocks.
VisualstimuliwerepresentedusingPresen-
tation software (Neurobehavioral Systems)
and viewed on a projection screen using a
mirrormountedtotheheadcoil.TheMP-150
system(BIOPACSystems)recordedskincon-
ductance levels (SCL) via MRI-compatible
electrodesaffixedtotheindexandmiddlefin-
gersofthelefthandandoperatingatasam-
plingrateof250Hzwithhardwarehigh-pass
filterat0.05Hz.Anelectricstimulator(Coul-
bournInstruments)delivered500msstimula-
tiontothefourthandfifthfingersoftheleft
handviaMRI-compatibleelectrodes.Tocali-
bratetheintensityoftheshock,eachpartici-
pant was asked to choose his/her own
stimulation level immediately before func-
tionalimaging,suchthatthestimuluswouldbe
“highlyunpleasantbutnotpainful”.Aftereach
run, participants were asked about the un-
pleasantnessofthestimulusandwereaskedto,
ifneeded,recalibrateitsothattheshockwould
stillbehighlyunpleasantbutnotpainful.
MRIdataacquisition
MRI data collection used a 3 tesla Siemens
TRIOscanner(SiemensMedicalSystems)with
Figure2. MethodforperformingtemporalfactoranalysisonfunctionalMRIresponses.
a32-channelheadcoil.Eachsessionbeganwith
the acquisition of a high-resolution MPRAGE
anatomicalscan(0.45(cid:3)0.45(cid:3)0.9mmvoxels).Eachofthesubsequent
functionalrunscollected201volumesofEPIdatawithTR(cid:4)2.5s,TE(cid:4)25 smoothing to reduce scanner-induced noise with a median filter (50
ms,andFOV(cid:4)192mm.Eachvolumecontained44obliqueslicesoriented sampleswithina200mswindow),resamplingto1Hz,andnormalizing
signalmagnitudeacrossparticipants(settingthemeanto50andSDto
30°clockwiserelativetotheAC–PCaxis(todecreasesusceptibilityartifacts
10).TransformedSCLsignalswereanalyzedusingalinearmodelinthe
inregionssuchastheamygdalaandorbitofrontalcortex)withthickness3
mmandvoxelsmeasuring3(cid:3)3mminplane. AFNIsoftwarepackage(http://afni.nimh.nih.gov/)toestimatethere-
sponsetothetwoblocktypes.Eventsofphysicalshockweremodeledas
Dataanalysis additionalregressorsofnointerest.TheSCLresponsetoeachstimuli
SCL. The SCL data for each participant were preprocessed using type (physical shock, onset of safe block, onset of threat block) was
MATLAB (MathWorks) and included the following steps: temporal estimatedusingcubicsplinebasisfunctionsfordeconvolutioninaman-
McMenaminetal.•TemporalUnfoldingduringAnxiousStates J.Neurosci.,August20,2014•34(34):11261–11273•11263
Table1. sitionslice.Asix-parameterrigidbodytransformationcorrectedhead
Talairachcoordinates motionwithinandbetweenrunsbyspatiallyregisteringeachvolumeto
thefirstvolume.Noneoftheparticipantsexhibitedexcessiveheadmo-
Region Hemisphere x y z tion((cid:5)3mmtotalmovement).TheSPMpackagewasusedtoskullstrip
Saliencenetworknodes thehigh-resolutionanatomicalimagesandsegmentthebraintocreate
Fronto-insula R 34 18 4 gray- and white-matter masks for each participant. Probability maps
L (cid:7)34 22 4 wereextractedforgraymatter,whitematter,andCSF.Binarizedwhite
Dorsalanteriorcingulatecortex — (cid:7)2 10 40 matter and CSF masks were created by thresholding the images at a
Temporo-parietaljunction R 62 (cid:7)26 36 probability(cid:5)0.90.Toreducethelikelihoodthatthesemaskscontained
L (cid:7)62 (cid:7)26 36 voxelsfromadjacentgray-matterregions,theywere“eroded”usingAF-
Inferotemporalcortex R 54 (cid:7)62 (cid:7)4 NI’s 3dmask_tool to remove voxels that had edges or faces that con-
L (cid:7)54 (cid:7)54 (cid:7)8 nected with voxels outside of the mask. A 12-parameter affine
Precentral R 26 (cid:7)6 64 transformation registered each participant’s anatomical scan with the
L (cid:7)26 (cid:7)2 64 TT_N27template(AFNIpackage)fornormalizationtoTalairachspace
Dorsolateralprefrontalcortex R 38 42 24 (TalairachandTournoux,1988).Thesametransformationwasapplied
L (cid:7)34 46 28 to the functional data. A 6 mm full-width half-maximum (FWHM)
Inferiorfrontalgyrus R 54 6 20
Gaussianfilterwasusedtospatiallysmoothallvolumes,andtheaverage
L (cid:7)54 10 12
intensityateachvoxel(foreachrun)wasscaledto100.
Posteriorthalamus R 6 (cid:7)18 4
Analysis of functional MRI signals. Theactivationateveryvoxelwas
L (cid:7)6 (cid:7)18 0
analyzedforeachparticipantusingamultipleregressionmodelinAFNI.The
Midbrain R 7 (cid:7)24 (cid:7)3
L (cid:7)7 (cid:7)23 (cid:7)4 responsetosafe-blockonset,threat-blockonset,andphysicalshockdelivery
Hypothalamus R 10 2 (cid:7)8 weremodeledusingcubicsplinebasisfunctionsthatmadenoassumptions
L (cid:7)10 2 (cid:7)8 about the shape of the hemodynamic response. Responses to safe- and
Executivenetworknodes threat-blockonsetsweremodeledforthefirst40softheblockbecausethat
wastheminimumdurationofanythreatorsafeblock.Responsetophysical
Orbitalfrontoinsula L (cid:7)36 24 (cid:7)10
shockdeliverywasmodeledfor20s.Constant,linear,andquadraticterms
Dorsolateralprefrontalcortex R 46 46 14
L (cid:7)34 46 6 wereincludedascovariatesofnointerestforeachruntoaccommodate
Ventrolateralprefrontalcortex R 34 56 (cid:7)6 slow-varyingdriftsintheMRsignal.Additionalcovariatesofnointerest
L (cid:7)32 54 (cid:7)4 comprisedtheaveragesignalfromwhitemattervoxels,theaveragesignal
Frontaloperculum R 56 14 14 fromventriclevoxels,andsixrigid-bodyheadmotionparameters.Thewhite
Frontaleyefield R 30 12 60 matterandventriclesignalsweredefinedusingtheerodedmapsofwhite
L (cid:7)32 18 50 matterandCSFregionsfromeachparticipant’shigher-resolutionanatom-
Dorsomedialprefrontalcortex — 0 36 46 icalscan.
Lateralparietal R 38 (cid:7)56 44 Weusedadata-drivenapproachtocharacterizehowtransientand
L (cid:7)48 (cid:7)48 48 sustained responses unfolded over time (Fig. 2). The functional time
Inferiortemporalcortex R 58 (cid:7)54 (cid:7)16 coursewasestimatedateverygraymattervoxelfor40sfollowingblock
Dorsalcaudate R 12 14 4 onset.Subsequently,factoranalysiswasusedtodescribetheresponsesat
L (cid:7)16 (cid:7)14 20 eachvoxelasacombinationoftemporalfactors.Factoranalysisguide-
Anteriorthalamus R 10 2 8 lineswereadaptedfromtheevent-relatedpotential(KayserandTenke,
L (cid:7)8 (cid:7)2 8 2003) and EEG literature (Shackman et al., 2010). Initially, for every
Task-negativenetworknodes
voxel,anaverageresponsewasdetermined,whichpooledacrosstrials,
Posteriorcingulatecortex — (cid:7)2 (cid:7)36 37 conditions,andparticipants.Thisallowedustocomputea“temporal
Retrosplenial — 3 (cid:7)51 8 correlationmatrix”;specifically,anumber-of-timepoints(cid:3)number-of-
Lateralparietal L (cid:7)47 (cid:7)67 36 timepointsmatrix,whereeachentrywasthecorrelationoftheresponses
R 53 (cid:7)67 36 foraspecificpairoftimepoints.Thecorrelationmatrixdescribedthe
Medialprefrontalcortex L (cid:7)3 39 (cid:7)2
similarity(acrossvoxels)oftheevokedresponsesforeachpairoftime
R 1 54 21
points.Principalcomponentswereextractedfromthecorrelationmatrix
Superiorfrontal L (cid:7)14 38 52
andascreetest(Cattell,1966)wasusedtodeterminethenumberof
R 17 37 52
componentstoberetained.Notethatthenumberofcomponentsre-
Inferotemporalcortex L (cid:7)61 (cid:7)33 (cid:7)15
R 65 (cid:7)17 (cid:7)15 tained(i.e.,three)agreeswiththatofKaisercriterion(e.g.,acomponent
Parahippocampal L (cid:7)22 (cid:7)26 (cid:7)16 isretainedonlyifitexplainsatleast1/number-of-timepoints(cid:4)1/17(cid:4)
R 25 (cid:7)26 (cid:7)14 5.89%ofthetotalvariancebyitself).Varimaxrotationwasappliedtothe
retainedcomponents.Thevarimaxrotationmaximizesthevarianceof
loadings within each factor (i.e., across time points) while preserving
neranalogoustoprocessingoffunctionalMRIdata(Bachetal.,2009; orthogonality(Kaiser,1958;Abdi,2003).Thisrotationmethodencour-
Choietal.,2012).Theresponsetophysicalshockwasmodeledfor20s ageseachfactortoloadheavilyonasmallnumberoftimepointsand
followingstimulusdelivery,andtheresponsestoblockonsetsweremod- haveloadingsnearzeroelsewheretofacilitatethefactor’sinterpretation.
eledfor40sfollowingstimulusonset.Responseslockedtoblockonset Notethattherotatedfactorsremainorthogonal(i.e.,uncorrelatedwith
weremodeledfor40sbecausethatwastheminimumdurationofany oneanother)butatimepointmaycontributetomultiplefactors,sothe
threatorsafeblock,thusensuringthatestimatedresponsesdidnotin- factoranalysiscanidentifytemporallyoverlappingprocesses.
cludethebeginningofasubsequentblock.TheSCLresponsewasin- Univariaterandomeffectsanalyseswereperformedvoxelwisedur-
dexedasthemeanresponseacrossthe40speriod,andapairedttestwas ingeachtemporalfactor.Correctionformultiplecomparisonswas
usedtotestdifferencesbetweenthreatandsafeacrossparticipants. performedbyestimatingtheFWHMsmoothnessofspatialnoiseus-
FunctionalMRIpreprocessing.Preprocessingofthefunctionalandan- ingAFNI’s3dFWHMxprogram(9.07(cid:3)8.89(cid:3)8.33mm)andthen
atomicalMRIdatausedtheAFNI(Cox,1996;http://afni.nimh.nih.gov/) usingAFNI’s3dClustSimprogramtoperformMonteCarlosimula-
and SPM software packages (http://www.fil.ion.ucl.ac.uk/spm/). The tionsanddeterminetheclusterextentthresholdnecessarytoachieve
first three volumes of each functional run were discarded to account a whole-brain corrected (cid:2)(cid:3) 0.05. Based on these simulations, all
forequilibrationeffects.Slice-timingcorrectionusedFourierinterpola- statisticalmapswerethresholdedatp(cid:6)0.005(uncorrected)witha
tiontoaligntheonsettimesofeverysliceinavolumetothefirstacqui- clusterextent(cid:4)46voxels.
11264•J.Neurosci.,August20,2014•34(34):11261–11273 McMenaminetal.•TemporalUnfoldingduringAnxiousStates
ROIs for the BNST and amygdala. Given a
priori interest in the role of the BNST and
amygdala during anxious anticipation, we
measured their responses using anatomically
definedregionsofinterest(ROIs).TheROIs
forBNSTweredefinedusingtheatlasofMaiet
al. (1997) with Talairach x-coordinates re-
strictedtothevaluesbetween3and8mm((cid:7)3
and (cid:7)8 mm for the opposite hemisphere),
y-coordinates restricted between (cid:7)1 and 3
mm,andz-coordinatesrestrictedbetween(cid:7)1
and6mm.BilateralamygdalaROIswerede-
finedusingtheDesaiatlas(Desikanetal.,2006;
Destrieuxetal.,2010)providedwiththeAFNI
softwarepackage.Tominimizesignalcontri-
butionsfromoutsidetheseROIs,theresponse
toblockonsetswereestimatedusingnonspa-
tiallysmootheddataandaveragedacrossthe
voxels within the ROIs. Threat and safe re-
sponsesweremeasuredforeachtemporalfac-
tor and differences between threat and safe
conditionsweretestedwithapairedttest.
Functional connectivity and network defini-
tion.Wedefinedthreenetworksusingcoordi-
nates from previous studies: the salience
network, except the amygdala (19 regions;
Figure3. Methodforcalculatingfunctionalconnectivityduringeachtemporalfactor.
Hermans et al., 2011), the executive control
network(16regions;Seeleyetal.,2007),and
thetask-negativenetwork(12regions;Foxet
al., 2005). The bilateral BNST and bilateral
amygdalaregionswereeachincludedtoform
two additional networks that each had two
ROIs.Thefinalsetcontained51regionsinfive
different networks (Table 1). Every region,
excepttheBNSTandamygdalaregions,was
defined as 6 mm radius spheres. Responses
weremeasuredineachregionforeachtem-
poralfactoroneveryexperimentalblockby
averagingnonspatiallysmootheddataacross
thevoxelsineachregion.
Network analysis was performed based on
adjacencymatrices(whichwerefertoas“con-
nectivitymatrices”)forsafeandthreatcondi-
tions,ateachtemporalfactor(Fig.3).Todoso,
theestimatedresponseforeveryblockwasex-
pressedintermsofthreecoefficientsthatde-
termined the magnitude of the contribution
(“factor loading”) of each of the temporal
factors.Inthismanner,eachtrial(i.e.,block)
was represented as a vector of coefficients:
((cid:5) , (cid:5) , (cid:5) ).
temporal_factor1 temporal_factor2 temporal_factor3
Eachconnectivitymatrixwasthendefinedviathe
PearsoncorrelationbetweenpairsofROIsofthe
coefficientsacrosstrials.Inthismanner,theconnec-
tivitymatricescanbeviewedas“trial-by-trial”(here,
block-by-block) functional connectivity matrices
duringeachtemporalfactor.
Network measures. Network analysis in-
groupstudiescanbeperformedbydetermin-
ing connectivity matrices at the participant
level, computing network metrics of interest
(e.g., efficiency), and performing statistical
testsonthemetrics.Thisapproachisappropri- Figure4. Permutation-basedmethodsforstatisticalinferenceonnetworkmeasures.
ate when sufficient observations per partici-
pant(percondition)areavailabletocomputea
“stable,”representativeconnectivitymatrixattheindividuallevel.Be- Then, network metrics can be computed and statistical analyses per-
causethelongblocksusedherelimitthenumberoftrialsforeachpar- formedbycomparingtheobservedmetricstowhatisobservedina“null
ticipant, a preferable approach is to average all individual-level model” estimated via Monte Carlo methods. Here, correlations were
connectivity matrices into a single group matrix for each condition. averagedacrossparticipantstogenerategroup-levelsafeandthreatcon
McMenaminetal.•TemporalUnfoldingduringAnxiousStates J.Neurosci.,August20,2014•34(34):11261–11273•11265
Thesethreemeasureswerecalculatedonthe
group-average connectivity matrices for each
ofthefivenetworksforthethreatandsafecon-
ditionsduringeachtemporalfactor.Current-
flowalgorithmsdonotpermitnegativevalues
intheconnectivitymatrix,sonegativecorrela-
tions(only3%ofconnections)weresettozero
as done in previous research (Rubinov and
Sporns,2010;Kinnisonetal.,2012).Statistical
inferencesaboutthreatversussafedifferences
were made by using permutation testing
(Good, 2005) to estimate the distribution of
the expected threat-safe difference under the
nullhypothesis(Fig.4).Specifically,foreachof
5000 permutations, randomly assign threat
andsafelabelsforeachparticipant’sconnectiv-
ity matrices; determine new group-average
connectivitymatricesforthreatandsafe(per
timeperiod);andrecalculatenetworkproper-
ties.Thenulldistributionofthethreatversus
safedifferenceduringeachtemporalfactorwas
usedtocalculatethepercentileoftheobserved
threatversussafedifferencetodeterminehow
extreme(ornot)theobservedeffectwas.For
convenienceinreportingtheresults,wecon-
vertedpercentilesinto“equivalent”z-valuesof
the standard normal distribution. To correct
formultiplecomparisonsacrossthefivenet-
works, we calculated a maximum-z distribu-
tionduringthepermutationtest.Specifically,
we determined the distribution of the maxi-
mum z-statistic expected across the five net-
worksunderthenull-hypothesis,thustaking
intoaccountallthetestssimultaneously.Sta-
tistical inferences were made using this
maximum-zdistributionratherthanthenull
distributions calculated for each individual
network to calculate p values corrected for
multiple comparisons (Westfall and Young,
1993; Nichols and Holmes, 2002; Maris and
Oostenveld,2007).
Individualdifferences
Figure5. Meanactivationduringthefirsttemporalfactor.Brainmapsdepicttheresultofunivariatetestsduringthefirst
Becausenetworkanalysiswasbasedonaver-
temporalcomponentcollapsedacrossThreatandSafe(voxel-levelthresholdatp(cid:6)0.005andcluster-levelthresholdatp(cid:6)0.05).
ageconnectivitymatrices,weassessedapo-
Inset,thetimecourseassociatedwiththefirsttemporalfactor.Insetsshowaverageestimatedresponsesforthreatandsafe
tentialroleofindividualdifferencesbasedon
conditionsforrepresentativeregions(Talairachcoordinatesshown).
a median split of the data (instead of com-
puting network measures on individuals).
nectivitymatricesforeachtemporalfactor.Fisher-transformationswere
Participantsweredividedintohigh-(N(cid:4)11)andlow-anxiety(N(cid:4)
appliedbeforeaveragingthecorrelationstoreducebiasinducedbythe
boundsoncorrelationsat(cid:7)1and1(SilverandDunlap,1987). 13)groupsusingamediansplitontheSTAIstateanxietyscores(but
becausetraitanxietyscoreswerecorrelatedwithstateanxietyscores,
Weusedtwonetworkmeasures,namely,efficiencyandbetweenness.
theircontributionscannotbedissociated;seeDiscussion).Theaver-
Weusedthe“informationflow”frameworkdevelopedbyMissiuroetal.
(2009).Comparedwithstandardmeasuresofdegreeandbetweenness,it ageconnectivitymatriceswerecalculatedforthreatandsafecondi-
has the advantage that it considers all possible paths of information tionsineachgroup,andathreat-by-anxietyinteractionwasevaluated
transferbetweennodes.Theapproachmodelsanetworkasalatticeof bycalculatingthedifferenceofthreatversussafescoresacrosshigh-
resistorsbytransformingedgeweights(heredefinedbyfunctionalcon- andlow-anxietygroups.Statisticalsignificanceagainwasassessedby
nectivity)intoelectricalconductances(i.e.,1/resistance).Thecommu- determininganulldistribution.Thenulldistributionoftheinterac-
nication efficiency between nodes A and B is defined as the net tion score was estimated by randomly assigning participants to the
conductanceobservedwhenafixedcurrentsourceisappliedtoAanda highandlowanxietygroupsandrecalculatingtheinteractionscore
groundissettoB.Theamountofcurrentthatpassesthroughathird (5000times).
nodeCmeasurestheextenttowhichnodeCisbetweenAandB.The
current-flowmeasuresofefficiencyandbetweennesswereusedtocalcu-
latethefollowingpropertiesforeachofthefivenetworks:(1)within- Results
network efficiency, defined as the average current-flow efficiency SCL
betweenallpairsofnodeswithinanetwork,(2)between-networkeffi-
Threat blocks had greater average skin conductance level than
ciency,definedasanetwork’saverageefficiencywitheachoftheother
safeblocks(t (cid:4)5.55,p(cid:6)0.001),indicatingthatthethreatof
networks,and(3)network-betweenness,definedastheaveragebetween- (23)
nessforallnodesinanetworkwithrespecttocommunicationbetween shockmanipulationwassuccessfulandproducedanincreasein
othernetworks. arousal.
11266•J.Neurosci.,August20,2014•34(34):11261–11273 McMenaminetal.•TemporalUnfoldingduringAnxiousStates
Table2. Table3.
Talairachcoordinatesof Talairachcoordinates
peak ofpeak
Cluster Peakstatistic, Cluster Peakstatistic,
Region extent x y z t(23) Region extent x y z t(23)
Earlytemporalfactor:threat(cid:8)safe(cid:5)0 Intermediatetemporalfactor:threat(cid:8)safe(cid:5)0
Cuneus 6163 5 (cid:7)71 12 15.29 None
Posteriorcingulate 8 (cid:7)40 40 9.23 Intermediatetemporalfactor:threat(cid:8)safe(cid:6)0
RightsupramarginalGyrus 56 (cid:7)42 31 8.73 Rightpostcentral 4201 41 (cid:7)26 57 (cid:7)8.31
Rightinferiorparietal 56 (cid:7)53 11 6.37 Leftpostcentral (cid:7)34 (cid:7)32 56 (cid:7)5.65
Leftlingual,fusiform (cid:7)23 (cid:7)55 (cid:7)6 11.33 Paracentral 0 (cid:7)25 48 (cid:7)3.77
Rightlingual,fusiform 23 (cid:7)66 (cid:7)6 6.90 Rightprecentral 40 (cid:7)23 43 (cid:7)7.05
Thalamus (cid:7)1 (cid:7)16 (cid:7)7 8.07 Leftprecentral (cid:7)52 4 41 (cid:7)4.23
Leftputamn (cid:7)20 7 1 6.67 Rightposteriorinsula 40 (cid:7)25 17 (cid:7)5.99
Rightputamen 21 4 1 7.82 Leftposteriorinsula (cid:7)31 (cid:7)28 20 (cid:7)5.53
Leftcaudate (cid:7)10 8 2 7.85 Leftthalamus 399 (cid:7)10 (cid:7)28 2 (cid:7)5.74
Rightcaudate 14 10 9 5.54 Rightthalamus 13 (cid:7)22 2 (cid:7)4.82
LeftanteriorInsula (cid:7)37 14 2 11.20 Precuneus (cid:7)6 (cid:7)56 16 (cid:7)5.27
(cid:7)28 17 (cid:7)7 10.34 Frontalpole 397 (cid:7)4 62 8 (cid:7)5.07
RightanteriorInsula 33 26 9 13.79 MedialPFC (cid:7)4 48 32 (cid:7)4.08
28 17 (cid:7)6 11.77 Leftmiddlefrontalgyrus (cid:7)15 43 29 (cid:7)4.03
Rightprecentral 38 7 29 7.78 Rightlateraloccipital 154 53 (cid:7)71 (cid:7)1 (cid:7)4.89
Rightmiddlefrontal 29 31 33 5.21 Lefthippocampus 130 (cid:7)23 (cid:7)17 (cid:7)10 (cid:7)5.40
dmPFC 726 8 14 42 8.42 Leftamygdala (cid:7)22 2 (cid:7)22 (cid:7)3.57
Dorsalanteriorcingulate 8 17 28 8.07 RightinferiorparietalLobule 92 29 (cid:7)74 30 (cid:7)6.08
Bilateralsuperiorfrontalgyrus 1 28 47 4.82 Rightamygdala 78 26 (cid:7)11 (cid:7)10 (cid:7)5.18
Leftsupramarginal 213 (cid:7)56 (cid:7)44 36 6.30 Righthippocampus 31 (cid:7)23 9 (cid:7)3.93
(cid:7)55 (cid:7)51 19 3.92 Leftlateraloccipital 62 (cid:7)44 (cid:7)59 (cid:7)4 (cid:7)4.06
Earlytemporalfactor:threat(cid:8)safe(cid:6)0 Ventralstriatum,nucleus 58 8 17 (cid:7)7 (cid:7)5.35
Leftpostcentral 1448 (cid:7)34 (cid:7)31 56 (cid:7)7.69 accumbens
(cid:7)53 (cid:7)25 44 (cid:7)5.23
Leftposteriorinsula (cid:7)44 (cid:7)29 11 (cid:7)3.37
Precuneus (cid:7)5 (cid:7)59 20 (cid:7)8.67
Paracentral 6 (cid:7)27 63 (cid:7)5.37 Table4.
Leftsuperiorfrontalgyrus 1073 (cid:7)17 32 51 (cid:7)8.34
(cid:7)17 4 37 (cid:7)5.01 Talairachcoordinatesof
Leftmiddlefrontalgyrus (cid:7)17 58 13 (cid:7)4.75 Cluster peak Peakstatistic,
Frontalpole (cid:7)1 56 4 (cid:7)4.59 Region extent x y z t(23)
Medialorbitofrontalcortex (cid:7)1 20 (cid:7)15 (cid:7)4.05
Rightposteriorinsula 556 62 (cid:7)16 14 (cid:7)7.47 Latetemporalfactor:threat(cid:8)safe(cid:5)0
Rightpostcentral 53 (cid:7)14 34 (cid:7)5.25 None
LeftInferiorParietalLobule 180 (cid:7)35 (cid:7)74 36 (cid:7)7.79 Latetemporalfactor:threat(cid:8)safe(cid:6)0
Rightsuperiorparietal 1421 11 (cid:7)67 59 (cid:7)7.20
TemporalanalysisoffunctionalMRIresponses lobule
Tocharacterizepotentiallytransientandsustainedresponses,the Leftsuperiorparietal (cid:7)25 (cid:7)67 54 (cid:7)4.02
functionalresponsewasestimatedateverygray-mattervoxelfor lobule
40sfollowingtheonsetofanexperimentalblock,andtemporal Precuneus 8 (cid:7)67 38 (cid:7)5.10
Leftlingualgyrus 389 (cid:7)14 (cid:7)74 (cid:7)16 (cid:7)6.48
factoranalysiswasusedtodescriberesponsesasacombinationof
Rightlingualgyrus 14 (cid:7)77 (cid:7)16 3.61
temporalfactors(Fig.2;seeMaterialsandMethods).Threetem-
Leftfusiform (cid:7)35 (cid:7)62 (cid:7)15 (cid:7)5.23
poralfactorsthatcombinetoaccountfor89%ofthevariancein Rightfusiform 31 (cid:7)58 (cid:7)16 (cid:7)4.68
responses across voxels were retained: an “early” transient re- Leftthalamus (cid:7)6 (cid:7)31 (cid:7)2 (cid:7)4.88
sponse that peaked at 5 s after block onset, an “intermediate” Rightthalamus 11 (cid:7)28 (cid:7)2 (cid:7)4.63
responsefrom7.5to17.5s,anda“late”sustainedresponsebe- Rightsuperiorandmiddle 211 41 (cid:7)2 48 (cid:7)5.15
tween20and40s.Pooledacrossthreatandsafeblocks,during frontalgyri
the early temporal factor (Fig. 5; Table 2) signal increased in Rightmiddletemporal 61 62 (cid:7)44 (cid:7)1 (cid:7)4.16
saliencenetworkregions(e.g.,thalamusandanteriorinsula)and gyrus
visualcortex(e.g.,medialoccipitallobe),andsignalsdecreasedin
task-negative regions (e.g., precuneus, inferior parietal lobule,
andventromedialPFC).Thiswasfollowedbywidespreadsignal withpeakt (cid:4)(cid:7)4.41atx(cid:4)23,y(cid:4)2,z(cid:4)45).Asimilarsignal
(23)
decreases during the intermediate (Table 3) and late (Table 4) reductionoccurredatthecontralaterallocation(19voxelcluster
temporalfactors.Subsequentanalysesofthreateffectsonactiva- withpeakt (cid:4)(cid:7)5.14atx(cid:4)(cid:7)20,y(cid:4)5,z(cid:4)45),butthisdid
(23)
tion and functional connectivity were performed separately notmeettheclusterextentcriterionforsignificance.
withineachofthesetemporalfactorstodeterminehowresponses Differencesbecamemorewidespreadduringtheintermediate
unfoldedovertime. temporalfactor(Fig.6;Table5).Threatincreasedsignalinre-
gionsthathavepreviouslybeenlinkedto“anxiousanticipation”
Effectofthreatonresponsesforeachtemporalperiod (e.g.,rightanteriorinsula),striatum,andregionsoftheexecutive
The only effect during the early temporal factor was reduced control network (e.g., supramarginal gyrus, dorsomedial PFC,
signalintherightdorsolateralPFCduringthreat(72voxelcluster anterior thalamus, and caudate head). Threat decreased re-
McMenaminetal.•TemporalUnfoldingduringAnxiousStates J.Neurosci.,August20,2014•34(34):11261–11273•11267
Figure6. Theeffectofthreatonactivationduringthesecondtemporalfactor.Brainmapsdepicttheresultofunivariatetests(threatvssafe)duringthesecondtemporalcomponent.Statistical
mapsdepicteffectswithcorrectedp(cid:6)0.05.Theaverageevokedresponseslockedtotheonsetofthreatandsafeblocksaredepictedforseveralkeyregions.
Table6.
TalairachCoordinatesof
peak
Table5. Cluster Peakstatistic,
Talairachcoordi- Region extent x y z t(23)
Cluster natesofpeak Peakstatistic, Latetemporalfactor:threat(cid:5)safe
Region extent x y z t(23) Rightcaudate 85 14 2 24 6.04
Intermediatetemporalfactor:threat(cid:5)safe Rightthalamus 4 (cid:7)13 10 3.55
9 (cid:7)20 5 3.9
Posteriorcingulate 422 5 (cid:7)20 33 5.25 Rightsupramarginalgyrus 70 (cid:7)53 (cid:7)47 33 4.86
Thalamus (cid:7)1 (cid:7)17 11 4.07 Medialorbitofrontalcortex 46 (cid:7)2 38 (cid:7)22 4.70
Leftcaudate (cid:7)8 (cid:7)1 16 4.47 Latetemporalfactor:safe(cid:5)threat
Rightcaudate 10 (cid:7)1 16 4.11
LeftBNST (cid:7)5 (cid:7)6 1 4.87 LeftSPL 1865 20 71 39 (cid:7)7.15
RightBNST 8 (cid:7)4 5 4.32 RightSPL (cid:7)22 68 37 (cid:7)3.84
Ventraltegmentalarea (cid:7)4 (cid:7)9 (cid:7)7 3.67 LeftIPL 47 71 17 (cid:7)3.95
10 (cid:7)9 (cid:7)7 3.74 RightIPL (cid:7)43 74 16 (cid:7)4.25
dmPFC 268 8 29 50 6.80 Precuneus (cid:7)7 56 40 (cid:7)5.15
10 36 31 5.52 Leftpostcentral 51 20 46 (cid:7)4.01
RightSupramarginalgyrus 157 53 (cid:7)47 33 5.18 Leftprecentral 31 32 50 (cid:7)3.93
LeftSupramarginalgyrus 55 (cid:7)53 (cid:7)53 36 5.25 Rightaccumbensarea 228 8 14 (cid:7)1 (cid:7)5.78
Rightanteriorinsula,inferiorfrontalgyrus 45 35 23 (cid:7)7 5.31 Leftaccumbensarea (cid:7)10 16 (cid:7)4 (cid:7)4.99
Intermediatetemporalfactor:safe(cid:5)threat Leftamygdala (cid:7)10 (cid:7)1 (cid:7)17 4.83
Ventralstriatum (cid:7)19 10 (cid:7)13 (cid:7)4.08
LeftIPL 1443 (cid:7)32 (cid:7)74 30 (cid:7)7.23 14 8 (cid:7)10 (cid:7)4.02
RightIPL 31 (cid:7)77 25 (cid:7)4.92
Precuneus (cid:7)1 (cid:7)64 44 (cid:7)4.33
Leftpostcentral (cid:7)51 (cid:7)20 46 (cid:7)4.01
sponseswithintask-negativeregions(e.g.,bilateralinferiorpari-
Leftprecentral (cid:7)31 (cid:7)32 50 (cid:7)3.93
Rightfusiform 449 26 (cid:7)44 (cid:7)16 (cid:7)5.52 etallobule,precuneus,andparahippocampalgyrus).
Rightlingualgyrus 14 (cid:7)44 (cid:7)2 (cid:7)4.81 Many of the differences between threat and safe blocks ob-
Precuneus (cid:7)1 (cid:7)56 10 (cid:7)4.93 servedduringtheintermediatetemporalfactorpersistedintothe
Leftlingualgyrus 65 (cid:7)14 (cid:7)59 (cid:7)7 (cid:7)4.05 latetemporalfactor(Table6),suchasincreasedresponseswith
Rightpostcentralgyrus 64 23 (cid:7)35 63 (cid:7)4.39 threatintherightcaudateandthalamus,anddecreasedresponses
Rightprecentralgyrus 46 44 (cid:7)20 51 (cid:7)4.59
withthreatintheinferiorparietallobuleandprecuneus.How-
11268•J.Neurosci.,August20,2014•34(34):11261–11273 McMenaminetal.•TemporalUnfoldingduringAnxiousStates
ever,activationdifferencesalsoappeared
in new regions (Fig. 7); responses in-
creasedwiththreatinthemedialorbito-
frontalcortexanddecreasedwiththreatin
the ventral striatum, including locations
consistentwiththenucleusaccumbens.
EffectofthreatonresponsesinBNST
andamygdala
Figure8depictstheregionsofinterestfor
the left and right BNST. Given the chal-
lenge in imaging such a small structure,
we compared the pattern of functional
connectivityobservedintheseregionsto
thosefromarecentlypublishedpaperthat
investigatedtheBNSTwithalargesample
(N(cid:4)99)(Averyetal.,2014).Thepattern
of resting-state functional connectivity
obtainedbyAveryetal.(2014)isverysim-
ilar to the one observed here using our
BNSTROIs(duringsafeblockstobetterap-
proximatetherestingstate;Fig.8).
In the BNST (Fig. 9), responses in-
creasedduringtheintermediateperiodof
threat blocks in the right (Fig. 9; t (cid:4)
(23)
2.61,p(cid:4)0.016)andleft(t (cid:4)3.00,p(cid:4)
(23) Figure7. Theeffectofthreatonactivationduringthethirdtemporalfactor.Brainmapsdepicttheresultofunivariatetests
0.006)hemispheres,consistentwithfind-
(threatvssafe)duringthethirdtemporalcomponentdiffersbetweenthethreatandsafeconditions.Statisticalmapsdepicteffects
ingsduringextendedaversivemanipula- withcorrectedp(cid:6)0.05.TheaverageevokedresponseslockedtotheonsetofthreatandsafeblocksaredepictedformedialOFC
tions(Mobbsetal.,2010;Somervilleetal., andnucleusaccumbens.
2010;Alvarezetal.,2011).TheleftBNST
exhibitedatrendtowardsustainedsignal
increaseunderthreatduringthelatetem-
poralfactor(t (cid:4)1.85,p(cid:4)0.077);ef-
(23)
fects of threat were not detected for any
other temporal factor in either BNST
(ps (cid:5) 0.11). Signal in the left amygdala
decreasedduringthelatetemporalfactor
(t (cid:4)(cid:7)4.01,p(cid:6)0.001),andatrend-
(23)
level decrease was detected in the right
amygdala(t (cid:4)(cid:7)1.80,p(cid:4)0.085);ef-
(23)
fects of threat were not detected for any
othertemporalfactorineitheramygdala
(p(cid:5)0.14).
Effectofthreatonnetworkmeasures
duringeachtemporalfactor
We probed network-based properties of
functional connectivity focusing on the
amygdala, BNST and three well studied
large-scalenetworks,namely,thesalience,
the executive control, and the task-
negative networks (see Materials and
Methods;weexcludedtheamygdalafrom
thesaliencenetworktostudyitsproper-
tiesseparately).Togaugethepotentialfor
communicationwithinandbetweennet-
works,wedeterminednetworkmeasures
of efficiency and betweenness based on
theanalysisofinformationflow(Missiuro
etal.,2009).Increasedefficiencywithina
network reflects increases in functional Figure8. DepictionofmaskusedfordefiningtheBNSTinthepresentstudy(topright).Thepatternofrestingstatefunctional
connectivity involving the edges of that connectivityfromapreviouslypublishedpaper(imagesadaptedfromAveryetal.,2014)isconsistentwiththoseobservedbetween
network; increased efficiency between ourBNSTregionsandtherestofthebrainduringsafeblocks.
McMenaminetal.•TemporalUnfoldingduringAnxiousStates J.Neurosci.,August20,2014•34(34):11261–11273•11269
shock might have contributed to the re-
ported effects. Thus, we re-ran network
analyses after excluding trials where the
temporal factor of interest overlapped
withphysicalshockdelivery.Thisresulted
in a reduced dataset (with 10–12 threat
blocksperparticipant),butthechangesto
network efficiency and betweenness were
qualitatively preserved in the salience net-
work,executivenetwork,andtheamygdala.
Relationshipofself-reportedanxietyto
threat-relatedchangesin
networkproperties
We focused on individual differences in
self-reported anxiety and network prop-
ertiesoftheBNSTandamygdala.Werea-
sonedthatifthesestructuresinfluencethe
flow of signals during threat, their be-
tweenness scores should be altered. In-
deed, during the intermediate temporal
window, a threat by anxiety interaction
wasdetectedintheBNST(z(cid:4)2.45,p(cid:4)
0.029) but not the amygdala (z (cid:4) 0.05,
p (cid:4) 0.956). Thus, the extent to which
threat increased the betweenness of the
BNST was greater for participants with
highrelativetolowself-reportedanxiety.
No effects were detected in the first or
thirdtemporalwindows.
Figure9. AverageresponseintheleftandrightamygdalaandBNSTlockedtotheonsetofthreatandsafeblocks.
Discussion
networksreflectsincreasesinthefunctionalconnectivityofedges The present study sought to understand
linking the two networks; increased betweenness of a network theevolutionoffunctionalMRIresponsesasparticipantsentered
suggeststhatthenodesinthatnetworkparticipatemoreheavily into threat (“anxiety” provoking) periods relative to safety. To
inthefunctionalconnectionsbetweenothernetworks(i.e.,they helpdiscoverthestructureoftheresponseswithoutmakingas-
becomemore“central”). sumptionsofresponseshape,weusedfactoranalysis.Wefound
Figure10showsfunctionalconnectivitywithinandbetween thatthreetemporalfactorsweresufficienttodescribebrainre-
networksforthethreetemporalperiods,andFigure11depicts sponses: an initial transient temporal factor, an intermediate
how threat alters network structure. During the first temporal temporalfactor,andarelativelysustainedlatetemporalfactor.Net-
component, threat increased the salience network’s within- work analysis for each temporal factor revealed changes in brain
networkefficiency(z(cid:4)2.77,p(cid:4)0.010)andbetween-network networkorganizationasparticipantsexperiencedthreat.Thesefind-
efficiency(z(cid:4)1.95,p(cid:4)0.046),consistentwithHermansetal. ingshighlighttheneedtocharacterizehownetworkorganization
(2011)findingofincreasedsaliencenetworkconnectivitywhile unfoldswithtime.
inan“anxiousstate”(watchingahorrormovie).Decreasedbe-
tweennessintheexecutivenetworkwasalsodetected(z(cid:4)(cid:7)2.33,
p(cid:4)0.047),suggestingthatitbecomesrelativelylesscentralfor Effectsofthreatonresponsesandfunctionalconnectivity
duringtheinitialtransientresponse
thecommunicationbetweenothernetworks.Nootherchanges
toefficiencywithin((cid:2)z(cid:2)(cid:6)1.12,p(cid:5)0.302)orbetweennetworks Transientresponsestotheonsetofbothsafe-andthreat-blocks
((cid:2)z(cid:2)(cid:6)1.44,p(cid:5)0.120)wasdetected;ornetworkbetweenness((cid:2)z(cid:2) increased in the salience network and visual regions, but de-
(cid:6)1.58,p(cid:5)0.247). creasedwithinthetask-negativenetwork.Theseresultsarecon-
The effects of threat on network properties were mostly re- sistentwithpreviousfindingsthatasaliencenetworkcenteredon
versed during the second temporal factor. Threat decreased theanteriorinsulaisresponsibleforallocatingattentiontoward
within-networkefficiencyforthesalience(z(cid:4)(cid:7)2.82,p(cid:4)0.007), motivationally salient stimuli (Seeley et al., 2007; Menon and
executive (z (cid:4) (cid:7)1.79, p (cid:4) 0.096), and task-negative networks Uddin,2010)andatask-negativenetworkthatdeactivateswhen
(z(cid:4)(cid:7)2.45,p(cid:4)0.020);italsodecreasedthebetween-network taskdemandsrequireattendingtoexternalstimuli(Gusnardet
efficiencyforallnetworks((cid:2)z(cid:2)(cid:5)1.93,p(cid:6)0.043).Importantly, al.,2001;Foxetal.,2005;Buckneretal.,2008).Surprisingly,we
threatincreasednetworkbetweennessoftheamygdalanetwork detectedminimalactivationdifferencesbetweenthreatandsafe
(z(cid:4)2.56,p(cid:4)0.023);atrendlevelincreaseinbetweennessofthe duringthisinitialtemporalfactor.Wesuspectthatthisresultmay
executivenetworkwasalsodetected(z(cid:4)2.23,p(cid:4)0.058).Dur- be attributable to the fact that both block onsets were motiva-
ingthethirdtemporalfactor,nosignificanteffectsweredetected. tional; the onset of threat blocks for obvious reasons and the
Finally, note that although signal related to the delivery of onsetofsafeblocksbecausetheyprovidedasafetysignal(Chris-
physicalshockwasregressedout,itispossiblethatresponsesto tiansonetal.,2011).
11270•J.Neurosci.,August20,2014•34(34):11261–11273 McMenaminetal.•TemporalUnfoldingduringAnxiousStates
Figure10. Averagefunctionalconnectivitybetweenregionsacrossparticipantsduringthreatandsafeblocksforeachofthethreetemporalfactors.
However,differencesbetweenthreatandsafewereapparent balancebetweenlarge-scalenetworkstofavoractivationofthe
inthisearlytimewindowwhenusingnetworkanalysis.Specifi- executivenetworkoverthetask-negativenetwork.
cally,theonsetofathreatblockincreasedefficiencywithinthe TheinvolvementoftheBNSTintheprocessingofextended
saliencenetworkanddecreasedthebetweennessoftheexecutive threat has been extensively discussed by Davis et al. (2010),
control network. This suggests that threat altered communica- wholinkthisstructuretosituationsinvolvinga“long-lasting
tionwithinthesaliencenetwork,aswellastheextenttowhichthe stateofapprehension”.Here,weobservedresponsesinapu-
executive control network facilitated communication between tativeBNSTsitethatweresustainedduringtheintermediate
othernetworks.Thus,signalingwithinthesaliencenetworkmay period. Some evidence of BNST involvement during the late
havebecomemoreeffective,asreflectedinthetightercorrelation period was also observed, albeit only at a trend level (p (cid:4)
betweenpairsofregionsinthisnetwork.Inaddition,theexecu- 0.077).Althoughspeculative,itispossiblethatthelateperiod
tivenetworkmayhavebecomemoresegregatedfromcommuni- also partly signaled upcoming safety because threat and safe
cationbetweenothernetworks. blocksalwaysalternated;thus,“apprehension”mayhavebeen
partlyoffsetbyimpending“relief”.Ofcourse,otherneuroim-
Effectsofthreatonresponsesandfunctionalconnectivity aging studies have also reported responses in putative BNST
duringtheintermediateperiod sitesduringthreat(Somervilleetal.,2010;Alvarezetal.,2011;
Severaloftheregionsthatexhibitedincreasedsignalunderthreat Grupeetal.,2013).
duringtheintermediatetemporalwindow,includingthethala- In terms of network level changes, threat decreased effi-
mus,caudate,andsupramarginalgyrus,participateintheexecu- ciency in the salience network during this temporal factor,
tivenetwork;severaloftheregionsthatdecreasedsignalunder oppositetotheeffectdetectedduringtheinitialperiod.Thus,
threat,includingtheinferiorparietallobuleandprecuneus,par- transientincreasesinconnectivityinthesaliencenetworkare
ticipateinthetask-negativenetwork.Previousstudieshavere- notsustainedforthedurationoftheanxiousstate,highlight-
ported threat-related decreases across task-negative regions ing the need to characterize how network organization un-
(Choi et al., 2012) and the relationship between executive and foldswithtime.Thisfindingisrelevantinthecontextofthe
task-negativenetworksistypicallyantagonistic(Foxetal.,2005). important report by Hermans et al. (2011), who described
Itisthusreasonablethatthreathasopposingeffectsonthesetwo greatersaliencenetworkconnectivityduringperiodsofanxi-
systems. Additional threat-related signal increases during this ety associated with watching an aversive movie. Given the
temporalfactorwerefoundintherightanteriorinsulaanddor- presentresults,wespeculatethattheirfindingsmayhavede-
somedialPFC.Therightanteriorinsulaissuggestedtoplayan pendedonrecurringtransientprocesses,suchasresponsesto
important role in “balancing” the activation of executive and emotionallysalientobjectsinthemovie(Langetal.,1998),or
task-negativenetworks(Sridharanetal.,2008),andthedorso- anxiety-induced alterations of early perceptual processes
medialPFCisimplicatedintheprocessingofinstructedthreat (Shackmanetal.,2011).
and/orappraisalofthreat(Mechiasetal.,2010).Together,these Network-leveleffectsofthreatweredetectedinvolvingboth
tworegionslikelycontributetodeterminingwhethertheorgan- the amygdala and BNST. During the intermediate period
ismisinathreateningcontextandmaybeinvolvedinshiftingthe amygdala betweenness increased, leading to the working hy-