The role of the frontal cortex in memory: an investigation of the Von Restorff effect

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by  Anat Elhalal

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Elhalal, Anat and Davelaar, Eddy J. and Usher, Marius (2014) The role of the
frontal cortex in memory: an investigation of the Von Restorff effect. Frontiers
in Human Neuroscience 8 , ISSN 1662-5161.
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ORIGINALRESEARCHARTICLE
HUMAN NEUROSCIENCE published:27June2014
doi:10.3389/fnhum.2014.00410
The role of the frontal cortex in memory: an investigation
of the Von Restorff effect
AnatElhalal1*,EddyJ.Davelaar1 andMariusUsher2,3
1DepartmentofPsychologicalSciences,BirkbeckCollege,UniversityofLondon,London,UK
2SchoolofPsychologicalScienceandSagolSchoolofNeuroscience,TelAvivUniversity,TelAviv,Israel
3DepartmentofExperimentalPsychology,UniversityofOxfordandWahadhamCollege,UniversityofOxford,Oxford,UK
Editedby: Evidence from neuropsychology and neuroimaging indicate that the pre-frontal cortex
IlkeÖztekin,KoçUniversity,Turkey (PFC) plays an important role in human memory. Although frontal patients are able to
Reviewedby: formnewmemories,thesememoriesappearqualitativelydifferentfromthoseofcontrols
AsliKiliç,KocUniversity,Turkey bylackingdistinctiveness.NeuroimagingstudiesofmemoryindicateactivationinthePFC
GeoffWard,UniversityofEssex,UK
underdeepencodingconditions,andunderconditionsofsemanticelaboration.Basedon
*Correspondence:
these results, we hypothesize that the PFC enhances memory by extracting differences
AnatElhalal,Departmentof
PsychologicalSciences,Birkbeck and commonalities in the studied material. To test this hypothesis, we carried out an
College,UniversityofLondon,Malet experimental investigation to test the relationship between the PFC-dependent factors
Street,Bloomsbury,WC1E7HX and semantic factors associated with common and specific features of words. These
London,UK
experimentswereperformedusingFree-Recallofwordlistswithhealthyadults,exploiting
e-mail:[email protected]
the correlation between PFC function and fluid intelligence. As predicted, a correlation
was found between fluid intelligence and the Von-Restorff effect (better memory for
semantic isolates, e.g., isolate “cat” within category members of “fruit”). Moreover,
memory for the semantic isolate was found to depend on the isolate’s serial position.
The isolate item tends to be recalled first, in comparison to non-isolates, suggesting
that the process interacts with short term memory. These results are captured within
acomputationalmodeloffreerecall,whichincludesaPFCmechanismthatissensitiveto
bothcommonalityanddistinctiveness,sustainingatrade-offbetweenthetwo.
Keywords: PFC, frontal lobe, free recall, von restorff, distinctiveness, categorization, semantic memory,
computationalmodeling
INTRODUCTION et al., 2000). CVLT involves several memory tests including a
Free recall of word lists is a central experimental paradigm freerecalltestofacategorizedlist.Intwodifferentstudiesusing
that has driven research on the nature of memory encoding CVLT (Baldo et al., 2002; Alexander et al., 2003) frontal lobe
and retrieval processes and their neural substrate (Craik and patients showed semantic clustering well below healthy control
Lockhart, 1972; Tulving et al., 1994; for a review, see Davelaar participants. Converging evidence for frontal lobe involvement
andRaaijmakers,2012).Earlymemoryresearchhasshownthat in semantic clustering comes from ageing studies. For exam-
amajorfactorinenhancingmemoryperformanceisthedepthof ple, older people produce less clustered output on the CVLT
encoding:oneremembersmorewordswhenattendingtoseman- test(normtablesinDelisetal.,2000).Ageinghasmanyshared
tic relations between the words than when attending to their deficitswithfrontallobeimpairments,anditwassuggestedthat
sound (Craik and Lockhart, 1972). This research also showed frontal cortex decline in elderly people is responsible for these
theimportanceofsemanticrelationsbetweenlistwords,bothin impairments(foradetailedlist:Haarmannetal.,2005).
the encoding and retrieval processes. For example, many stud- One important strategy for utilizing the relation between
ies have demonstrated enhanced memorability for semantically wordstoenhancememoryperformance(whichiscentraltoour
related words (e.g., Glanzer and Schwartz, 1971; Greene and investigation here) is to look for distinctiveness. For example,
Crowder,1984;Davelaaretal.,2006),andothershaveshownthat Hunt and Lamb (2001) reported that isolate-words presented
semanticclusteringtakesplacespontaneouslyinthefree-recallof withinalistofrelatedwords(allofwhichbelongtoasinglecat-
categorizedlists(Bousfield,1953). egorythatisdifferentfromtheisolate)havehigherprobabilityof
A series of neuropsychological and imaging studies indi- recall in a free recall test. For example: an isolate word, “Hour”
catethatsemanticmemoryenhancementinvolvestheprefrontal presentedwithintheanimallist:“Bear,Pig,Elephant,Deer,Cat,
cortex (Moscovitch, 1994; Tulving et al., 1994; Gershberg and Mouse,Cow,Tiger,Horse,Lion,Rat.”Thismanipulationbelongs
Shimamura, 1995; Baldo et al., 2002; Kishiyama et al., 2009; to a family of experiments, usually called the “Von Restorff”
Løvstad et al., 2012). A standardized neuropsychological test (VR)paradigm,afterVonRestorffwhoinitiallydesignedit(Von
which is utilized to measure the frontal lobes’ contribution to Restorff, 1933). It has also been proposed that the mechanism
memory is the California Verbal Learning Test (CVLT-II, Delis thatmediatestheeffectsofnoveltyanddistinctivenessisrelated
FrontiersinHumanNeuroscience www.frontiersin.org June2014|Volume8|Article410|1
Elhalaletal. Memoryforsemanticisolatesandclustering
to frontal cortex functions (Fabiani et al., 1998; Daffner et al., EXPERIMENT1:ACORRELATIONALSTUDYOFTHE
2000; Ranganath and Rainer, 2003; for a detailed overview, see RELATIONSHIPBETWEENFLUIDINTELLIGENCEAND
Kishiyamaetal.,2009). SEMANTICFACTORSINFREERECALL
More recently, a number of neuropsychological investiga- Experiment1wasdesignedtoexploretheroleofthefrontalcortex
tions have provided evidence to support the frontal mediation in semantically related memory functions. In order to investi-
of novelty-based encoding in memory. In particular, studies by gatethiswithhealthyyoungadults,acorrelationalapproachwas
Knight and colleagues (Kishiyama et al., 2009; Løvstad et al., adopted.Acorrelationbetweenfrontalcortexactivityandperfor-
2012)have shownthattheprefrontal cortexmodulates theVon manceonfluidintelligencetestswaspreviouslydemonstratedin
Restorff effect. Kishiyama et al. (2009) tested 16 patients with tasks such as the Cattell Culture Fair Test (Duncan et al., 1995,
damagetotheunilateralPFC(9Left,7Right)onaVonRestorff 1996,2000).Therefore,participants’performanceinthistestwas
paradigmforrecognitionmemoryofobjectimages.Whereasthe measuredandtranslatedintoIQscores.Theparticipantscarried
age-matchedcontrolgroupexhibitedanoveltyadvantageinrec- out a free recall test of different types of lists to measure mem-
ollection,thepatientsdidnotshowanynoveltyadvantage.Ina ory components which are believed to be related to the frontal
followupstudy,Løvstadetal.(2012)observedthatpatientswith cortex. Types of lists included semantic isolates (Von Restorff),
orbitofrontal or lateral prefrontal lesions exhibited a reduction listsofcategorizedwords,listsfromtheDRMparadigm,andlists
in the novelty-induced P3 response over frontal electrodes. The designedtomeasureproactiveinterference(PI).
lateral PFC patients showed sustained slow wave activity com- Investigationsoffrontalpatientsshowthatsemanticclustering
paredtotheorbitofrontalpatients,suggestingthatthetwoareas is mediated by the frontal cortex, as frontal lobe patients fre-
areinstrumentalinnoveltyprocessingandarepartiallydifferen- quentlyshowsemanticclusteringwellbelowhealthycontrolpar-
tiated in their contributions. This conclusion is consistent with ticipants (Gershberg and Shimamura, 1995; Baldo et al., 2002).
anumberoftheoriesthatattributeseveralmemoryprocessesto IntheDRMparadigm (Deese,1959;RoedigerandMcDermott,
thePFC:encodingofsimilaritiesalongwithdistinctivenessinthe 1995), participants are presented with lists of words, all strong
materialinadynamicway(Shimamuraetal.,1995;Fletcheretal., associatesofanon-presentedtargetword1.Falsememoryforthe
2000;Shimamura,2000;Frithetal.,2004). target word is measured. Melo et al. (1999) showed initial evi-
The central aim of our study is to examine the factors that dence of frontal patients producing more false memories than
contribute to the memory enhancements related to semantic controlsontheDRMparadigm,inagreementwiththehypothesis
structure and semantic isolates (VR-effect), and their frontal thatrelatesutilizingcommonfeaturesbetweenwordsinmemory
mediation.ResearchontheVR-effectconcentratedmainlyonthe to PFC functions. It was previously found that frontal patients
improvedmemoryofitemsthatare“physically”distinctivefrom showenhancedsensitivitytoproactiveinterference(forexample,
otheritemsintheexperiment(differentincolor,sound,font,etc). Shimamura et al., 1995). However, other scholars have claimed
However,thereisevidencethatsomewhatdifferentprocessesare thatitisthereleasefromproactiveinterferencethatisthemain
involved in the processing of semantic and physical distinctive- deficitinfrontalpatients(Moscovitch,1982).
ness(FabianiandDonchin,1995).Surprisinglyfewexperiments
haveinvestigatedthenatureofsemanticVon-Restorffeffect,and METHODS
specifically the effect of the serial position of an isolate word Participants
in free recall memory tests on its enhanced memorability. One Thestudywascarriedoutaspartofanundergraduatepractical
wouldexpecttheisolateadvantageinfreerecalltodependonthe class,inwhichstudentsparticipateinanexperimentinorderto
serialpositionoftheisolateinthelist.Intheextremecase,when produce their own empirical data and subsequently analyze it.
theisolateisthefirstiteminthelist,itisstillnotdistinctiveasthe Eighty-onestudentsatBirkbeckCollegetookpartintheexper-
participantdoesnotknowwhatcomesnext.Inlaterserialposi- iment,agesranging21–50,withameanof32.Sincethefocusof
tions,afewrelatedwordshavealreadybeenpresentedandthus theexperimentwassemanticeffects,non-nativeEnglishspeakers
theisolatewordismoredistinctive. wereexcludedfromthesample.Thirty-twoparticipantsdidnot
We start with an experimental investigation of the correla- meetthecriteriaoflivinginEnglishspeakingcountriesfromthe
tionsbetweenanumberofsemanticeffectsinmemoryrecall(in ageof12oryounger.Twomoreparticipantswereexcluded,since
particular VR and semantic clustering) and fluid-intelligence— theirmeasured IQscore was60.Thisscorewas assumedto not
a measure associated with frontal function. The results indicate represent thetrue IQofuniversity students,indicatingtheydid
thepresenceofindividualdifferences (fluid-intelligence),previ- notengagewiththetesttruly.Eventually,datawasanalyzedfrom
ouslyassociatedwiththelobes(Duncanetal.,1995,1996,2000) theremaining47participants.
that mediate both VR and clustering effects. As both temporal
clustering (CVLT) and novelty based encoding were found to Design
be deficient in patients with frontal lesions, we will take it as Thisexperimentwasofacorrelationaldesign.Measuredvariables
ourworkinghypothesisthattheyarebothmediatedbyafrontal wereIQand5differenttypesofsemanticmemoryscores.
mechanism. This hypothesis is obviously tentative at this stage
(see General Discussion). Based on this, we developed a neuro-
1Forexample,inthe“sleep”list,thewordspresentedareallstrongassocia-
computationalmodelthatmakesspecificparametricpredictions
tionsof“sleep,”whichisnotpresented:“bed,rest,awake,tired,dream,wake,
forVR-effectsandsemanticclusteringinfreerecall.Finally,two snooze,blanket,doze,slumber,snore,nap,peace,yawn,drowsy”(Roediger
experimentswerecarriedoutthatconfirmedthesepredictions. andMcDermott,1995).
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Elhalaletal. Memoryforsemanticisolatesandclustering
Materials Instructionsweretopress“Enter”aftereveryword,whichcleared
TheCattelltestwasusedtomeasureIQ. therecallboxforanewword.Pressing“Enter”onanemptybox
Thirtylistsof12–15wordseachwereusedtomeasurespecific was the agreed sign for no more recalled words. That led to a
memoryfunctions.Alllistsinvolvedsemanticallyrelatedwords. screen asking them to “press any key to move to the next list.”
Categorieswerechosentohavenooverlaptominimizebetween- Participantsweregiven60storecallwords,afterwhichthepro-
listseffects.Allcategorizedlists(exceptthoseoftheoriginalDRM grammovedtothesamescreenautomatically.Participantswere
task)werecreatedusingtheVanOverscheldeetal.(2004)norms. first briefed with this procedure by a class presentation which
wasfollowedbyindividualpracticepriortotheexperiment.The
DRMlists.SixlistsweretakenfromtheDRMparadigm(Roediger whole experiment took under 1h, with the Cattell test lasting
and McDermott, 1995) from which 15 words were presented; about25mins(includinginstructions).Participantsthenmoved
these were all strong associates of a word that was not pre- to a computer room and proceeded with the memory test for
sented.Forexample,thewords:hot,snow,warm,winter,ice,wet, 30min.
frigid,chilly,heat,weather,freeze,air,shiver,arctic,frostwerepre-
sented, which are all associated with the word cold which was RESULTS
not presented. The number of times the non-presented words IQscoreswerecalculatedbasedonCattelltestresults.MeanIQ
werefalselyrecalledwascounted.ThefollowingDRMlistswere forthesamplewas107,withastandarddeviationof13.Thisis
used: feelings, colors, food, furniture, weather, medicine (from abovethepopulationmean,asonewouldexpectfromasample
RoedigerandMcDermott,1995). ofuniversitystudents.
Von Restorff lists. Six categories were chosen from the Van
Memoryforisolatewords(VonRestorffeffects)
Overschelde et al.(2004)norms. Lists of 11words were created
IQwascorrelatedwiththetotalnumberofwordsrecalledfrom
from each category, with the 12th word from an unrelated cat- VR lists: r =0.335, p<0.05. In addition, IQ was corre-
(45)
egory inserted in different positions in the list, as the 1st, 6th,
latedwithdifferentmeasures oftheisolationeffect. Correlation
and10thword.Forexample:Beer,Vodka,Rum,Whiskey,Tequila, betweenIQandthenumberofisolatesrecalledwasr =0.407,
(45)
Gin,Liquor,Scotch,Martini,House,Bourbon,Daiquiri. p<0.005.ToshowthattheimpactofIQisspecificfortheiso-
lates, the number of isolates recalled was divided by the total
Categorizedwordslists—blocked.Sixlistsof12wordswerecre-
numberoflist-wordsrecalled.Theresultingmeasurewascorre-
ated,withwordstakenfromthreedifferentcategories(fromthe
lated with IQ as well: r =0.336, p<0.05. Isolates appeared
VanOverscheldeetal.(2004)norms,fourwordsfromeachcate- (45)
in three serial positions in VR lists: 1st, 6th, and 10th. Looking
gory).Firstthewordsfromthefirstcategorywerepresented,then
for the number of isolates produced from each serial position
from the second, then third. For example: Eagle, Robin, Hawk,
separately,onlythecorrelationwiththe6thposition(dividedby
Crow,Priest,Pope,Bishop,Nun,Barbie,Ball,Puzzle,Lego.
thetotalnumberofwordsrecalled)reachedsignificance:r =
(45)
0.403,p<0.005.Forthe1stand10thpositions,correlationswere
Categorizedwordslists—cyclical.Sixlistsof12wordswerecre-
lowerand non-significant[forthe1st:r =0.198,p=0.181,
ated,withwordstakenfromthreedifferentcategories(fromthe (45)
NS;forthe10th:r =−0.32,p=0.828,NS].Afurthermea-
VanOverscheldeetal.(2004)norms,fourwordsfromeachcate- (45)
sureoftheVR-effectwascalculated:thenumberoftimesaword
gory).First,asinglewordfromthefirstcategorywaspresented,
is recalled from each of the three serial positions when it is an
thenasinglewordfromthesecond,thenfromthethird,andso
isolate, compared to when it is not an isolate (this could be
on.Forexample:Rose,Ballet,Window,Tulip,Tango,Door,Lily,
foundfromtheotherVRlistsinwhichisolatesappearedindiffer-
Salsa,Wall,Iris,Waltz,Floor.
entserialpositions).Significantcorrelationwasfoundagain,for
Proactiveinterferencelists.Sixlistsof12wordswereconstructed. the6thserialpositiononly:r(45) =0.303,p<0.05[forthe1st:
Every two consecutive lists were with words from the same r(45) =0.197, p=0.185, NS, for the 10th: r(45) =−0.068, p=
category. 0.651,NS].Probabilitiesofrecallandfirst-recallarepresentedin
ThememorytestwascreatedusingtheEprimeenvironment Figure1.
forpsychologicaltesting(pack1.1). Theresultsshowhigherprobabilityofrecallforisolateitemsat
lateserialpositions,andhigherprobabilitiesoffirstrecallforall
Procedure serial positions tested. Serial position curves exhibit high noise.
Theexperimentwascarriedoutinaclassroom.Participantswere This could be attributed to the experimental design which was
instructed to keep silence at all times to avoid interfering with optimizedforcorrelationanalysis,andhencetherewasnocoun-
other participants. Participants first performed the Cattell test, terbalancingorrandomizationinlistspresentation.Inaddition,
followedbythememorytest.Participantsweretoldtheywould only two lists were presented per participant per isolate serial
be presented with lists of words which they should read subvo- positionwhichmayhavecontaminatedthedatawithwordspe-
cally,andthereaftertrytorememberasmanyofthemaspossible cificeffects.Theprobabilitiesofrecallandfirstrecallsplitbythe
inanyorder. IQ median score are presented in Figure2. It can be seen that
The memory test comprised of 30 lists of words. Each word higher-IQindividualstendtoshowmoreadvantagefortheiso-
was presented for 1.5s. After each list a recall box appeared lates in comparison to lower-IQ individuals, as verified by the
and participants typed in as many words as they remembered. correlationanalysis.
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Elhalaletal. Memoryforsemanticisolatesandclustering
FIGURE1|Probabilitiesofrecall(A)andfirstrecall(B)fortheVonRestorfflistsbytheisolateserialpositioninthelist:greenfor1,bluefor6and
redfor10.
FIGURE2|Probabilitiesofrecall(leftpanels)andfirstrecall(rightpanels),fortheVonRestorfflistsbytheisolateserialpositioninthelist,splitbyIQ
medianscore(greenforhigher-IQindividuals,blueforlower-IQindividuals).
Memoryforcategorizedlists:blockedandnon-blocked by chance. High correlations with IQ were found both for the
IQwascorrelatedwiththetotalnumberofwordsrecalledfrom blockedlists[r =0.464,p<0.05]andthenon-blockedlists
(45)
categorizedlists:r =0.335,p<0.05.Inaddition,IQwascor- [r =0.367,p<0.05].
(45) (45)
relatedwithdifferentmeasuresofcategorization.Categorization Probabilities of recall for the blocked and non-blocked lists
factorswerecalculatedinaccordancewiththeCVLTtestmethod ofcategorizedwordssplitbythemedianIQscorearepresented
(Stricker et al., 2002). Essentially, the number of pairs of same inFigure3.Thisshowsanoveralladvantageforhigher-IQindi-
category words that were recalled consecutively was counted viduals in both conditions (also see Supplement, Figure S1 for
and corrected by the number of such pairs expected to occur afirstrecallprobability,showingthatHigh-IQparticipantshave
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Elhalaletal. Memoryforsemanticisolatesandclustering
FIGURE3|Probabilitiesofrecallforblockedcategorizedlists(left)andnon-blockedcategorizedlists(right),splitbyIQmedianscore(greenfor
higher-IQindividuals,blueforlower-IQindividuals).
anincreasestendencytostartrecallwiththefirstitemofthelast continuous distractor task, and the dissociations between them
category—anoveltyeffect). (Davelaaretal.,2005,2006).
Counter to predictions, no correlations were found with any Like in SAM (Raaijmakers and Shiffrin, 1980), this model
measures of the proactive interference lists, nor the DRM lists. includes a short-term activation buffer, so that the last words
Thiscouldbeduetothehomogeneityoftheexperimentalsam- in the list would still be active in such a buffer at the time of
ple,whichmayhaveproducedlessdifferentiationthanbetween recall.Thefrontalmechanisminteractswiththebufferfunction
healthysubjectsandpatients. to enhance encoding of semantic relationships between words.
Finally, we report in the Supplement (Figure S2) tempo- Theneuropsychologicalliteraturedescribedaboveandtheexper-
ral order effects (lag-CRP; Howard and Kahana, 2002) for imentalresultspresentedheresupporttheassumptionthatthere
randomizedandcategorizedlists(seeDiscussion). are additional memory processes to those implementing the
buffer which are mediated by the PFC. While the buffer only
DISCUSSION maintains some information about previously presented items
Correlationswerefoundbetweenfluid-IQandsemanticcluster- in an active state, these additional mechanisms play a role in
ing,aswellasIQandtheVonRestorffeffectformid-listitems. enhancing the encoding of semantic relationships (both simi-
The correlation between IQ and semantic clustering in healthy laritiesanddifferences)asillustratedbysemanticclusteringand
adults supports similar results found in frontal patients and theVR-effect.Welabelthismodelthe“categorization-activation-
neuroimaging (Gershberg and Shimamura, 1995; Savage et al., novelty model” (CAN) to reflect the functional role of its
2001; Baldo et al., 2002). It was expected that a relationship components.
would be established between the PFC and sensitivity to nov- Thepresentmodeldoesnotaddressoneimportantaspectof
elty,aswellasdistinctiveness.Thisisbasedonresultsfromother memory encoding and retrieval: the changing context. This has
paradigms(RanganathandRainer,2003;Kishiyamaetal.,2009; been demonstrated to be critical in accounting for order effects
Løvstad et al., 2012), and supported by the newly found corre- infreerecallparadigmsatdifferenttemporalscales(Howardand
lationbetweentheVonRestorffeffectandfrontalfunctions(for Kahana, 2002; Polyn and Kahana, 2008; Polyn et al., 2009); see
mid-listisolates).Inagreementwithpatientsandneuroimaging alsoFigureS2(insupplement)fordatafromExperiment1,show-
data, correlations were also found between semantic cluster- ing an interaction between lag-recency and semantic relation).
ing and IQ. Counter to predictions, however, no correlations This important component will need to be integrated into the
werefoundwithproactiveinterferenceorreleasefromproactive presentmodelinfuturestudies(seeGeneralDiscussion).
interference.
In order to better understand the mechanism by which the SIMULATIONSTUDY:THECAN-MODELFORTHEROLEOF
PFCutilizestherelationshipbetweenwordsinalisttoenhance THEPFCINMEMORY
both semantic clustering and the memory of semantic isolates, We assume that the frontal mechanism has two main compo-
wedeveloped(inthenextsection)acomputationalmodel.This nents:afastlearningcategorizationlayerandanoveltydetection
was based on the activation-buffer model that was previously mechanism (see also Grossberg, 1978a,b). The CAN model is
usedtoaccountfordatainimmediate-free-recall(IFR)andinthe comprised of four components: the frontal mechanism, a short
FrontiersinHumanNeuroscience www.frontiersin.org June2014|Volume8|Article410|5
Elhalaletal. Memoryforsemanticisolatesandclustering
termactivationbuffer,alayerofsemanticfeaturesandacontext thecategorizationunit,hencethecategorizationunitisdynam-
mechanism. ically learning a new category online. The more category mem-
bers presented in the list, the stronger the connections become
ACTIVATIONBUFFERANDTHESEMANTICLAYER between the category’s shared features and the categorization
Theactivationbufferisalexicallayer(eachunitcorrespondsto unit.However,ifanitemfromadifferentcategoryispresented,its
a word), with recurrent excitation and global lateral inhibition featuresactivateadifferentcategorizationunit(duetotheinitial
(HaarmannandUsher,2001;Davelaaretal.,2005).Thisleadsto random connections). The new categorization unit then learns
3–4 items being co-active during the list presentation, allowing the second category. At retrieval, activation sent from the cate-
themodeltoaccountforserialpositionfunctions(bothrecency gorizationlayertothesemanticfeatureslayerenhancesrecallof
andprimacy)inIFR(Davelaaretal.,2005).Sincewefocusedhere categorymembersconsecutively,leadingtosemanticclustering.
onsemanticrelationsbetweenthewordsinthelist,weincluded
foreachwordasemanticrepresentationinasemanticlayerwhose NOVELTYDETECTIONANDENCODING
unitscorrespondtothesemanticfeaturesoftheword.Eachlexical Asecondfrontalcomponentdetectsnoveltyintheinputbycom-
unitisthusconnectedwiththesemanticunitsthatcorrespondto paring the predicted (a leaky integrated value of its history; see
its“semanticrepresentation”(seeFigure4).Wordsfromthesame Detailed Description) activation values in the semantic features
categorywereassumedtohavesharedsemanticrepresentations. layer to the current ones. When a large difference is detected, a
Finally,weassumedtheexistenceofalist-contextrepresentation “surprise” signal is produced by the novelty mechanism which
(AndersonandBower,1972).Duringlistpresentation,thisrep- boosts both the effect of the sensory input (this can be viewed
resentation becomes connected with the activated units in the as enhanced attention) and the learning rate between the cate-
semanticandthelexicallayers. gorizationlayerandthesemanticfeatureslayer.Thismechanism
enablessimulationoftheVon-Restorffeffectthroughthestronger
CATEGORIZATIONLAYER encodingofanisolate.Italsoenablessimulatingthedependency
The categorization layer is comprised of multiple units with oftheVon-Restorffeffectontheisolate’sserialpositionasfound
strongcompetitionandinitialrandomconnectivitytotheseman- in the experiment above. When the isolate is in the first serial
tic features. During the encoding phase, when a member of a position,thereisstillnoprediction,andthereforenoadvantage
certain category gets input, its semantic representation in the in encoding. When a few category members have already been
semantic layer becomes active. The activation sent to the cate- presented before the isolate, the frontal mechanism detects the
gorization layer causes a categorization unit (or a few units in isolate’snoveltyandenhancesactivationandlearning.Therefore,
somecases)towinthecompetitioninthislayer.Hebbianlearn- the isolate can be more easily encoded and later recalled. It is
ing then takes place between the semantic features layer and predicted that the closer the isolate is to the end of the list, the
highertheprobabilitythatitsenhancedactivationwouldenable
ittosurvivethecompetitioninthelexicallayeruntiltheendof
thesimulation.Therefore,isolatesnearertheendofthelisthave
abetterencodingadvantage.
Thecombinationofthecategorizationandnoveltydetection
mechanismsenablesthemodeltosimulatedifferencesinseman-
tic clustering between frontal patients and healthy controls, as
well as the PFC sensitivity to novelty, the dependency of the
Von-Restorff effect on the serial position of the isolate and the
correlation found between PFC function and the magnitude of
Von-Restorff effect. The model components are illustrated in
Figure4.
RETRIEVAL
Attheretrievalstage,activationissentfromthecontexttothelex-
ical, semantic and categorization layers. Every item that crosses
the retrieval threshold is retrieved and subsequently inhibited.
ThePFChasanadditionalroleinmonitoringretrieval:thecat-
FIGURE4|Schematicdiagramoftheencodingstageofthemodel. egorization layer is reset following the occurrence of a certain
Thetoplayeristhelexicallayer,themiddleisthesemanticfeatureslayer. numberofunsuccessfulretrievalattempts.
Contextisrepresentedbyasingleunit(listcontext)inthebottom-left,and
thecategorizationlayer(componentofthePFC)isillustratedinthe
DETAILEDDESCRIPTION
bottom-right.Duringlistpresentation,lexicalunitsreceiveinput.Activation
spreadstothesemanticfeatureslayerandfurthertothecategorization Encoding
layer.EpisodicencodingbyHebbianlearningtakesplacebetweenthe Encoding a list of words is simulated by activating lexical units
contextandthelexical,semanticandcategorizationlayers.Inaddition,fast oneatatimebyaninput.Activationspreadsfromthelexicalunits
Hebbianlearningtakesplacebetweenthecategorizationlayerandthe
tothesemanticfeatureslayerthroughapredefinedconnectivity
semanticlayer.
matrix.Activationthenspreadsfromthesemanticfeatureslayer
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Elhalaletal. Memoryforsemanticisolatesandclustering
to the categorization layer through random initial connections. input is clamped to each list unit for T time steps. Each lexical
Connectionsbetweencategorizationunits(whichareactiveabove unitgetsactivationfromthesemanticlayer:ξ(cid:2)WxyF(y(t−1)).
ij j
a learning threshold) and active semantic features are strength- The activations of the semantic layer are denoted by y. Wxy is
j
ened. In addition, the activation in the semantic features layer the connectivity matrix, (the superscript xy stands for the con-
is constrained by an adaptation component. When novel input nectionsfromthesemanticfeatures,y,tothelexicalitems,x,all
ispresented,thedifferencebetweenthesemanticfeatures’leaky connections are symmetric) and ξ is the parameter multiplying
integratedvalue(oractivationhistory,whichisactuallytheadap- that activation. The activation in the layer is not allowed to get
tation component value) and the current activation is likely to negative.Theactivationofthelexicalunitsduringapresentation
crossathreshold.Asaconsequence,theinputtothelexicallayer ofalistof12wordsisshowninFigure5.
(aswellasthelearningratebetweenthecategorizationlayerand
thesemanticfeatures)isincreased(the“surprise”effect). Thesemanticfeatureslayer.Thesemanticfeatureslayeriscom-
Themodelisappliedtosimulatefreerecallofcategorizedlists, prised of 45 units which are reciprocally connected with the
ofnormalsubjectsandfrontalpatients.Attheencodingstage,12 lexicalunitsthroughtheconnectivitymatrixWyx.Competition
lexicalunitsgetactivated(or16inaCVLTsimulation)forTtime in the semantic features layer is mediated by global inhibition,
stepseach.Thefollowingeventstakeplaceateachtime-step: similar to the lexical layer. Semantic features receive activation
from the lexical layer (through Wyx), as well as input from
– Theadaptationofthesemanticfeatureslayerisupdated the frontal mechanism (categorization layer and the “surprise”
– If the difference between the semantic layer activation to the signal). The semantic features activation is described by the
adaptationvalue(absolutevalue)crossesathreshold,theinput followingequation:
tothelexicalitemsaswellasthelearningbetweenthesemantic (cid:2) (cid:3) (cid:4)
featuresandthecategorizationlayersareraisedforthecurrent yi(t)=λyi(t−1)+(1−λ) −βy(cid:2)F yj(t−1)
(cid:3) (cid:4) (cid:5)
item +χ(cid:2)Wyx(cid:2)F x(t−1) −κa(t)
– Thelexicallayeractivationisupdated ij j i
– Thesemanticfeatureslayeractivationisupdated
Where y(t) is the activation of the semantic feature i at time
– Thecategorizationlayeractivationisupdated i
t, λ and F(y) are the same as described above, β is the global
– The connections between the three layers: lexical, semantic y
featuresandcategorizationtothecontext,areupdated inhibitionparameterandχ(cid:2)WyijxF(xj(t-1))istheactivationthe
– Iftheactivationofone(ormore)categorizationunit(s)crosses semanticfeaturesreceivefromthelexicallayer.
the learning threshold, the connections between this unit(s) Thetermairepresentstheadaptationinthesemanticfeatures
andthesemanticfeaturesarestrengthened layer.
Its value is updated in every time step, according to the
The lexical layer (activation buffer). The lexical layer is com- semanticfeaturesactivation:
prised of 50 units, out of which 12 serve as list items. During a (cid:3) (cid:4)
simulationoflistpresentation,lexicalunitsareactivatedsequen- ai(t)=λaai(t−1)+(1−λa)F yi(t−1)
tiallybyclampingeachunitfora“sensory”inputforTtimesteps.
Units are connected to themselves via self excitation to main-
tainactivityafterinputoffset.Theyarealsonegativelyconnected
to all other units in the layer which creates global inhibition.
The balance between the magnitude of the self excitation and
globalinhibitioncreatesalimitedcapacitybuffer.Unitsthatare
active above threshold in the lexical layer are considered to be
the short term activation buffer. When a new item is activated,
its activation causes the activation of one of the previous item
todiminishthroughtheglobalinhibition.Thenewitemwould
eventuallyreplacetheweakestiteminthebuffer.Bufferdynamics
aredescribedbythefollowingequation:
(cid:2) (cid:3) (cid:4) (cid:3) (cid:4)
x(t)=λx(t−1)+(1−λ) αF x(t) −β (cid:2)F x(t−1)
i i i x j
(cid:3) (cid:4) (cid:5)
+I(t)+ξ(cid:2)WxyF y(t−1) +N(0,0.2)
i ij j
Where F(x) = x/(1 + x) for x > 0, and 0 otherwise (O’Reilly
and Munakata, 2000). x(t): activation of lexical item i at time
i
t. All activations are set to zero at the beginning of a simula- FIGURE5|Thedynamicsofthelexicallayerduringa12itemslist
tion.λ:atimeconstant,controllingtheamountofchangeineach simulation.Theactivationofeachitemisshownasadifferentcolorgraph.
timestep;α:theself-excitationparameter;β :theglobalinhibi- Itcanbeseenthatthefirstthreeactivateditemsreachhigheractivation
x values,becausetheyfacelesscompetitionfrompreviouslypresenteditems.
tion parameter; I(t): the sensory input to unit i at time t. The
i
FrontiersinHumanNeuroscience www.frontiersin.org June2014|Volume8|Article410|7
Elhalaletal. Memoryforsemanticisolatesandclustering
In addition, the activation in the layer is not allowed to get stimuli(orstudiedmaterial)isenhancedbyincreasingtheinput
negative. parameter(tothelexicalitemslayer)toI .Inaddition,thelearn-
s
ing between the categorization layer and the semantic features
The connectivity matrix between the lexical and the semantic layerisincreasedtoδ .
s
layers.Eachlexicalunitisconnectedviatheconnectivitymatrix When simulating a frontal patient, no learning takes place
Wxy with a number of semantic units. These connections are betweenthecategorizationlayerandthesemanticfeatureslayer,
xy yx
symmetric: W =W . Since the lexical layer corresponds to a andstimulusnoveltyisnotdetected.
ij ji
localisticrepresentationofitems,thepatternofWxycorresponds
toadistributedrepresentationofeachitemintermsofsemantic Thecontext“layer.”Contextisrepresentedbyasingleunitinthis
features.Theconnectivitymatrixbetweenthelexicalitemslayer model,andcanbeseenasa“listcontext.”EpisodicHebbianlearn-
and the semantic features layer is as follows: Wxy is defined in ingtakesplacebetweenthecontextandthelexicalitemslayer,the
thebeginningofeachsimulation.Tosimulatealistofunrelated semanticfeatureslayerandthecategorizationlayer:
items, each element of the matrix is set to one with a proba-
bility of 16%, which means that on average each lexical unit is Cxi =Cxi+F(xi(t))
representedby6–7semanticfeatures.Tosimulatealistofwords
Cy =Cy +F(y(t))
which belong to the same semantic category, a set of features i i i
(usually 5) is set to one for all of these words, in addition to Cz =Cz +F(z(t))
i i i
randomlyselecteddistinctivefeatures.SeeFigureS3(inthesup-
plement) for a connectivity matrix of a lexicon in which words Where Cx, Cy, and Cz are the (vectors of) magnitudes of the
belongto4differentcategorieswhicharerepresentedbysetsof5 connectionsofthecontexttothedifferentlayers,respectively.
featureseach.
The following two model components are the categorization Retrieval
mechanism and the novelty detection mechanism, which we At retrieval, the categorization layer activates the semantic fea-
associatewiththePFC. tureslayer.Inaddition,thecontextactivatesthesemanticfeatures,
thelexicalitemsandthecategorizationlayers.Whentheactiva-
Thecategorizationmechanism.Thecategorizationlayerconsists tionofalexicalitemcrossesaretrievalthreshold,itisconsidered
of 10 units. Their activation is initialized to zero at the begin- to be recalled. Its activation is reset after recall. If more than 2
ningofthesimulation.Thedynamicsofthecategorizationunits’ unsuccessful retrievals have been made (repetitions and intru-
activationisdescribedbythefollowingequation: sionscountedtogether),theactivationofthecategorizationlayer
(cid:6) (cid:3) (cid:4) isreset.
z(t)=λz(t−1)+(1−λ) −β (cid:2)F z(t−1) ThefollowingstepstakeplaceforTRtimesteps:
i i Z i
(cid:3) (cid:4)(cid:7)
+φ(cid:2)WzyF z(t−1) – Theadaptationofthesemanticfeatureslayerisupdated
ij j
– Thelexicallayeractivationisupdated
Wherez(t)istheactivationofcategorizationunitiattimet,λ – Thesemanticfeatureslayeractivationisupdated
i
– Thecategorizationlayeractivationisupdated
isatimeconstant,controllingtheamountofchangeineachtime
step, β is the global inhibition parameter. φ(cid:2)WzyF(z(t−1)) – Iftheactivationofalexicalunitcrossestheretrievalthreshold,
Z ij j
itisconsideredtoberecalled(andfollowingreset)
istheactivationsentfromthesemanticfeatureslayer,Wzyisthe
– Ifmorethantwounsuccessfulretrievalsoccurred,thecatego-
connectivitymatrixbetweenthecategorizationandthesemantic
rizationlayerisreset
featureslayer.
The categorization layer is reciprocally connected with the
Thelexicallayer(activationbuffer).Thedynamicsofthelexical
semanticfeatureslayer.Theconnectionsareinitializedtorandom
values, distributed between 0–1: Wyz(t = 1) (cid:3) U(0,1). Hebbian layerinretrievalissimilartoencoding,asidefromtheactivation
receivedfromthecontext.Thetermμ Cx(t−1)isaddedtothe
learning takes place between categorization units which cross a x i
equation.
learningthresholdandthesemanticfeatures:
Wyz =Wyz+δF(z)TF(y) The semantic features layer. Two additional terms are added
to the dynamics of the semantic features layer in retrieval: the
activation received from the context (μ Cy(t − 1)) and that
Theconnectionsbetweeneachcategorizationunitandallfeatures y i
arenormalizedaftereachupdate. received from the categorization layer ((cid:10)(cid:2)WyijzF(yj)). When
a lexical item’s activation exceeds the retrieval threshold, it
The novelty (distinctiveness) mechanism: enhancing attention is considered to be recalled. A recalled item can be a suc-
and encoding of novel stimuli. At each time step, the novelty cessful one if a list item is recalled for the first time, or an
mechanismismonitoringthedifferencebetweenthecurrentacti- unsuccessful one when an item is repeated, or when an item
vationinthesemanticfeatureslayerandthepredictedone,which which was not activated during encoding becomes active dur-
is mathematically identical to the definition of the adaptation ingretrieval(intrusion).Whenanitemisrecalleditsactivationis
term:a(t).Ifthisdifferencecrossesathreshold,theattentionto inhibited.
FrontiersinHumanNeuroscience www.frontiersin.org June2014|Volume8|Article410|8
Elhalaletal. Memoryforsemanticisolatesandclustering
Thecategorizationlayer(andconnectivitymatrixtotheseman-
tic features layer). The dynamics of the categorization layer in
retrievalissimilartoencoding,asidefromtheactivationreceived
fromthecontext.Thetermμ Cz(t−1)isaddedtotheequation.
z i
Furthermore, the value of the parameter multiplying the acti-
vation received from the semantic features layer (φ) is reduced.
It is more important for the PFC to be affected by success-
ful/unsuccessful retrievals, than by the current activation of the
semanticfeatureslayer.
In addition to the described dynamics, the unsuccessful
retrievalsaremonitored.Thisismodeledasasymbolicalgorithm
ratherthananeuralnetworksincethisprocessisoutsidethescope
ofthecurrentmodelingattempt.Whenthenumberofunsuccess-
fulretrievals(repetitionsorintrusions)exceeds2,theactivation
ofthecategorizationunit(s)thatwereactiveduringtherecallsare
inhibitedfortherestofthesimulation.Inaddition,theactivityof
thewholecategorizationlayerisreset.Adifferentcategorization
unit will become active due to the activation received from the FIGURE6|ProbabilityofrecallofaCVLT—likelist,red:modelwithout
context. thefrontalmechanisms,blue:modelwhichincludesthefrontal
mechanisms.Thefrontalmechanismsenhancerecallofacategorizedlist.
SIMULATIONRESULTS
The model was applied to simulate semantic clustering in free
recall as well as the experimental Von-Restorff results presented withoutthefrontalmechanismsoutputwaslesscategorizedthan
earlier.Inparticular,thedifferencebetweenfrontalpatientsand the model with the frontal mechanisms: 2.8 (±1.8) in compar-
normalsubjectsisexplored.Inordertosimulateafrontalpatient, ison with 5.4 (±2.2) (p<0.001). For example, in a single trial
the frontal mechanisms are disabled, hence no learning takes inwhichthepresentedlistwas:a1,d1,c1,d2,c2,d3,a2,b1,a3,
placebetweenthecategorizationlayerandthesemanticfeatures b2, c3, a4, b3, d4, b4, c4 (letters represent categories, numbers
layerandnoveltyisnotmonitored. representcategoryexemplars),Themodelwiththefrontalmech-
anismproducedthefollowingoutput:b4,c4,d4,c2,c4,c3,d3,
d2, d4, c2, d3, a2, a1 (The first recalled items are the recency
Modelingclusteringofacategorizedlist
items, therefore are not categorized). Alternatively, the model
AspartoftheCVLTtask(Delisetal.,2000)participantsareasked
withoutthefrontalmechanismsproduced:c4,b4,d4,c3,a4,a1,
to memorize a list of 16 words from four different categories
c4,d3,d1.
whicharepresentedinarandomorder.TheCANmodelisused
tosimulatethedifferencesinsemanticclusteringbetweenfrontal
patients and normal subjects. The CVLT includes a few repeti- ModelingtheVR-effect
tions of encoding and retrieval of the list. Only the first trial is The experimental results indicate that while isolate items have
simulatedhere. advantageinlateserialpositions,theyarelesswellremembered
In the simulation, the lexicon for this task is constructed whentheyappearinthebeginningofthelist.TheCANmodelis
of four categories, with four items in each category. These 16 appliedtosimulatingthesedata.Thelexiconforthistaskiscon-
itemsarepresentedinarandomorderwithnotwoconsecutive structedoftwocategories.Allstudieditemsexceptonebelongto
items from the same category, similar to the CVLT paradigm. asinglecategory,whiletheisolateitembelongstoadifferentcate-
Presentation order changes with every run of the simulation gory.Seethesupplementfordetailedillustrationsoftheencoding
(see Figure S3 in Supplement). In the Supplement we show a andretrievalphases.
detailedillustrationofthesemanticrepresentationsoflistitems During the presentation of a category, a categorization unit
andtheoperationofthecategorizationunitsduringencodingand becomes associated with it. When an isolate is activated, usu-
retrieval. ally a different categorization unit (different from the one that
Boththemodelwithoutthefrontalmechanismsandtheone learned thecategory oftheotherlistitems)becomes active and
which included them were able to recall the CVLT–like lists becomesassociatedwiththeisolate.Theitemsactivatedafterthe
(seeFigure6),thelatterrememberingconsistentlymorewords, isolatebelongtothefirstcategorywhichwasalreadylearnedby
exceptintherecencypositionswhicharemediatedbythelexical theformercategorizationunit.Thatcategorizationunitbecomes
buffer.Inthemodelwithoutthefrontalmechanisms,recencyis reactivatedduetothelearningthatalreadytookplacebeforethe
duetotheitemswhichwerestillactiveinthelexicallayeratthe isolatepresentation.Theactivationinthecategorizationlayercan
timeofrecall.Addingthefrontalmechanismscreatedpreference beseeninthetoppanelofFigure7.Forexample,inthemiddle
forcategorymembersofthemostactiveitems,loweringtherecall paneltheisolateappearsinserialposition7(ataroundt =180).
ofitemnumber14. Categorizationunitnumber5getsassociatedwiththemaincate-
Semantic clustering index was calculated in a similar way to gory,whilecategorizationunitnumber2(and8tosomeextent)
theCVLTtest(Delisetal.,2000;Strickeretal.,2002).Themodel getassociatedwiththeisolate.
FrontiersinHumanNeuroscience www.frontiersin.org June2014|Volume8|Article410|9