On the search for the neurophysiological manifestation of recollective experience

On the search for the neurophysiological manifestationof recollective experience

KEVIN M. SPENCER,a ENRIQUE VILA ABAD, b and EMANUEL DONCHINa

aDepartment of Psychology and Beckman Institute, University of Illinois at Urbana-Champaign, USAbFacultad de Psicologia, Departamento de Metodologia Ciencias Comportamiento,Universidad Nacional de Educacion a Distancia, Ciudad Universitaria, Madrid, Spain

Abstract

M.E. Smith~1993! obtained event-related brain potentials~ERPs! from subjects performing a recognition memory taskusing “remember”~R! and “know” ~K ! judgments, and reported observing in the ERP a “neurophysiological mani-festation of recollective experience” as a difference between the positive waveforms elicited by stimuli that yielded Rand K judgments. We replicated his experiment and examined the componential structure of the R.K effect in twoways. First, we found that correction for P300 latency jitter eliminated the effect reported by Smith. Second, theapplication of principal component analysis indicated that the positive waveform elicited by the words in the test listwas a P300. These analyses do not support the hypothesis that there is a new component~the “memory-evoked shift”!that is a specific manifestation of recollection.

Descriptors: Recognition memory, Recollection, Familiarity, ERPs, P300, Latency jitter

One approach to the use of event-related brain potentials~ERPs! inthe study of cognition adopts the subtractive model of Donders~1969!. Data are obtained in two experimental conditions that arepresumed to differ along a single dimension that defines somepsychological construct. A measure of the ERP is obtained for eachof the two conditions, and the difference between the measurescharacterizing the two conditions is taken as an ERP representationof the construct. The results of such experiments are usually pre-sented in the form of difference waves, which are then assignedsuch labels as the “Difference due to Memory”~“Dm”; e.g., Paller,Kutas, & Mayes, 1987! or the “Priming effect”~Rugg, 1995!. Twoassumptions lie at the core of this approach. One assumption is thatthe experimental conditions in which the subtracted ERPs wereobtained indeed differed on a single dimension. Another importantassumption is that the experimental manipulations affect exclu-

sively the amplitude of the ERPs so that the difference wavesrepresent different amounts of activation of the process manifestedby the ERP and that this difference in amplitude is measured by thedifference wave. Yet, one must accept this last assumption withextreme caution because amplitude differences between ERPs maybe due to variance in latency jitter, rather than to a genuine am-plitude difference between the ERP components examined by theinvestigator.

In this study we investigated the effect of latency jitter on thedifference between the ERPs associated with “remembered” and“known” items that was interpreted by Smith~1993! as a “neuro-physiological manifestation of recollective experience.” We exam-ined both the empirical validity of this effect and the conceptualimplications of interpreting the differences between two ERPs as“neurophysiological manifestations” of any psychological con-struct. We shall demonstrate that the amplitude differences thatunderlie Smith’s assertion are likely to be artifactual consequencesof differences in latency variability across the experimentalconditions.

The distinction between the retrieval of items from memorywith and without conscious recollection of the items’ previousoccurrence during study~e.g., Gardiner, 1988; Rajaram, 1993; Tulv-ing, 1985; cf. Düzel, Yonelinas, Mangun, Heinze, & Tulving, 1997!formed the theoretical framework for Smith~1993!. For example,one mightknow that Tirana is the capital of Albania yet lack theability to recall the episode in which this bit of information wasacquired. On the other hand, one might vividlyrememberbeingtold by a friend that “Tirana” is the solution to the 6-across entryin a crossword puzzle, whose clue is “The capital of Albania.” Thisdistinction has often been studied using the “remember0know”

Some of the research reported here was previously reported at the 34thAnnual Meeting of the Society for Psychophysiological Research~1994!.

This research was supported in part by grant NS31463 from the Na-tional Institutes of Health. K.M.S. was supported in part by predoctoraltraining program MH19554 and National Research Service Award MH11516from the Public Health Service. The participation of E.V.A. was madepossible by a grant from the Dirección General de Investigación Cientificay Técnica~DGICYT! of Spain.

We thank Michael Smith for providing us with the details of his ex-perimental procedures, and we acknowledge the helpful comments of ClayHolroyd, Leun Otten, and Marten Scheffers in the preparation of thismanuscript.

Address reprint requests to: Dr. Emanuel Donchin, Cognitive Psycho-physiology Laboratory, University of Illinois at Urbana-Champaign, 603East Daniel Street, Champaign, IL 61820, USA. E-mail: [email protected].

Psychophysiology, 37~2000!, 494–506. Cambridge University Press. Printed in the USA.Copyright © 2000 Society for Psychophysiological Research

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~R0K ! paradigm, introduced by Tulving~1985!. Such an investi-gation begins with a study period during which subjects examinea list of words to memorize. In a subsequent test period the sub-jects are presented with a test list composed of the words that werein the study list~old words! and an equal number of new words.Subjects report whether the test words are “old” or “new”. Forwords judged to be old, subjects indicate whether their decisionwas based on a conscious recollection of the occurrence of theword during the study episode~“remember,” or R response!, or ifit was based on some other means~“know,” or K response!.

Because R and K responses involve different processing oper-ations and hence, presumably, are implemented by different pat-terns of neural activity, it is interesting to determine whether theERP activity elicited by remembered items differs from the activityelicited by items that are known. Such information might be usefulin elucidating the neural circuitry that implements one or both ofthese recognition operations. Smith~1993!, therefore, comparedthe ERPs elicited by stimuli whose recognition was associatedwith either an R or a K response. He reported that a late positivecomponent of the ERP was larger in ERPs elicited by test wordsthat were associated with subsequent R responses than with sub-sequent K responses. The latency of this ERP component in thisexperimental setting~approximately 650 ms!, and its scalp distri-bution~maximal at central and parietal sites!, were those normallycharacterizing the P300 component~Sutton, Braren, Zubin, & John,1965!. Smith, however, argued that the difference between the Rand K ERPs, hereby termed theR.K effect, was not a differencein P300 amplitude. Rather, he attributed the observed effect to a“memory-evoked shift”~MES!. This new ERP component was the“neurophysiological manifestation of recollective experience.” Smithargued that it was not a P300 that produced the observed effectbecause all the words in the test list were equivalent with respectto “subjective probability” and to “subjective targetness,” variablesknown to affect P300. Smith inferred from the fact that mostsubjects made more R than K responses that the larger P300 am-plitude for R trials could not be attributed to lower “subjectiveprobability.” He also stated that because the R and K items wereboth old words, there should be no difference between them insubjective targetness that would evoke larger P300s for one or theother type.

This reasoning is predicated on the incorrect assumption thatthe P300 is elicited primarily by “targets” even though the evi-dence is clear that rare events, whether they are or are not thetargets, will elicit the P300~e.g., Duncan-Johnson & Donchin,1977!.1 Thus, the subjective targetness of the eliciting stimuli isirrelevant to whether or not the elicited component is a P300.Furthermore, the role that expectancies play in the control of P300amplitude is far more complex than would be implied by the merecounting of the number of stimuli that fall into various categories.It has been well established that subjects are sensitive to the mi-crostructure of the stimulus sequence in developing expectancieswith respect to any specific event in the sequence~Squires, Wick-ens, Squires, & Donchin, 1976!. If the positive peaks measured by

Smith are indeed instances of the P300, then his data are consistentwith the considerable evidence that the P300 elicited by recog-nized old items is larger than the P300 elicited by new items~e.g.,Karis, Fabiani, & Donchin, 1984; Neville, Kutas, Chesney, &Schmidt, 1986; Paller & Kutas, 1992; Rugg & Doyle, 1992; San-quist, Rohrbaugh, Syndulko, & Lindsley, 1980; Smith & Guster,1993; reviewed in Rugg, 1995!. Smith, however, asserted that theR.K effect was not a manifestation of this well-established en-hancement of the P300, but was rather due to the effects of anadditional, hitherto unknown, component, the “neurophysiologicalmanifestation of recollective experience” or MES.

The erroneous notion that P300 is elicited exclusively, or pri-marily, by targets is not uncommon. Yet, in the case of Smith~1993! it may not be necessary to determine which ERP compo-nent underlies the difference between R and K ERPs. An exami-nation of Smith’s data~see Figure 1! suggests that the amplitudedifference is a consequence of differences in the latency jitter ofthe P300s associated with the R and K decisions. The termlatencyjitter refers to the variability in the latency of the ERP componentacross the individual trials in an experiment. The fundamentalassumption of signal averaging is that the electroencephalogram~EEG! following the stimulus contains an ERP that is time lockedto the triggering event, while the ongoing EEG activity, beingrandom with respect to the eliciting event, will have an expectedvalue of zero. A consequence of the logic and nature of signalaveraging is that if the ERP is not perfectly time locked to theeliciting event then the signal average is not a valid estimate of theERP. Brazier~1964! was one of the first to note that amplitudes ofERPs are comparable if, and only if, the ERPs embedded in theindividual trials that are used in the computation of the signalaverage are perfectly time locked. At least, the distributions oflatencies in the two conditions are of a similar shape. When thereis latency jitter in the data, the signal average will underestimatethe amplitude of that component.

Examination of the waveforms of the ERPs recorded during thetest phase in Smith~1993! reveals that the positive component seenin the average of the R trials is sharply peaked. On the other hand,the positivity elicited in the K average displays a shallow wave-form even though it occupies the same latency range as does thepositivity associated with R trials. Whenever two instantiations ofthe same ERP component differ markedly in the degree to whichthey are peaked, amplitude differences between them are verylikely to be due, at least in part, to differences in the distributionsof the latencies of the component across the trials used for com-puting the averaged ERP. Thus, the R.K effect reported by Smithmay be due to latency jitter of P300 in the averaged ERP repre-senting the K trials.

Latency jitter is of particular concern when the objects of studyare the endogenous components of the ERP because their initiationis triggered by the completion of processing activities that mayvary in duration from trial to trial. Kutas, McCarthy, and Donchin~1977! presented subjects with three different oddball sequences,one constructed of two private names, one consisting of differentnames, some of men and some of women, and the third constructedfrom words that were, and were not, synonymous with the word“prod.” The elicitation of P300 on each trial depended, of course,on the subject identifying the word as a member of the rare cat-egory. It takes longer to decide whether a word is a synonym of“prod” than it takes to decide whether the string presented on thescreen is “Nancy” or “David.” These differences in categorizationtime account for the large differences in the average latency ofP300 reported by Kutas et al. However, it is also the case that the

1The assertion that P300 is elicited by the “targets in the oddballparadigm” is frequently found in the literature and derives from the findingthat P300 elicited by rare targets is somewhat larger than P300 elicited byrare nontargets~Duncan-Johnson & Donchin, 1977!. However, despite thissmall “target effect,” it is not true that only targets will elicit a P300.Indeed, Duncan-Johnson and Donchin~1977! also showed that it is theprobability of the event, rather than its target status, that determines whetheror not a P300 will be elicited.

ERPs and recollective experience 495

categorization time for individual words as synonyms of “prod” ismuch more variable across words than is the variability in the timeit takes to recognize correctly the string “Nancy” across its instan-tiations. As a consequence, the variability in the latency of P300would increase with the complexity of categorization and, as aconsequence, the amplitude of the P300 would decrease across thethree experimental conditions, being largest in response to thespecific names, and smallest in response to synonyms.

This precisely was the pattern of results reported by Kutas et al.~1977!. However, once adjusted for latency jitter~see more below!the amplitude differences disappeared. In general, whenever oneencounters a difference in the amplitude of an ERP componentacross two conditions and one of the ERPs is characterized by aP300 that is shallow in its waveform, whereas the other conditionsis associated with a sharp, peaked, P300, it is likely that the loweramplitude P300 reflects the effects of latency jitter.The burden ofproof in such cases is on the investigator, the most parsimoniousaccount for the results being that the amplitude difference reflectsthe effects of latency jitter and is not “real.” A report in which thewaveforms differ markedly in their shape, or in which the pro-cessing demands can vary widely from trial to trial, and in whichthe effect of latency jitter on ERP amplitudes has not been ad-dressed, is inadequate.

The test phase waveforms in Smith~1993! associated with Rand K responses clearly differ in shape in a manner that suggeststhat the R.K effect may be attributed to latency jitter. The appli-cation of latency jitter correction~LJC; also known as latencyadjustment! techniques~cf. Gratton, Kramer, Coles, & Donchin,

1989! should eliminate this difference. To test this hypothesis wereplicated Smith~1993! and assessed, using LJC, the extent towhich the R.K difference could be explained by P300 latencyjitter, obviating the need to invoke an overlapping ERP activityrelated to recollective experience. Furthermore, we applied an ERPdecomposition technique~principal components analysis, or PCA!to the data as an additional test of whether non-P300 activitycontributed to the R.K effect. If another kind of ERP activity wasresponsible for the R.K effect, it should be appear as a factorseparate from the P300 in the PCA results.

Methods

The procedures described by Smith~1993! were followed in thepresent study with the following exceptions:

1. Word stimuli were selected in the same manner as Smith~1993!,but different words were used.

2. Subjects were given a practice study-test block at the beginningof the experiment so that their performance would not be af-fected by learning the task. Smith~1993! did not report givingpractice trials to the subjects.

3. After the study-test blocks, subjects were given an “oddball”task to perform to obtain “reference” P300s for comparisonwith the memory-related ERPs. These data are not presented inthis report.

Figure 1. Test phase event-related potentials~ERPs! from Smith ~1993! and the present study~midline electrode sites! for theremember~R!, know ~K !, and New conditions. Note that the time scale of the ERPs from Smith~1993! spans a smaller range thanthe time scale of the ERPs from the present study. The amplitude scale is the same for both plots.

496 K. M. Spencer, E. Vila Abad, and E. Donchin

4. Filter settings for the amplifiers were 0.3–100 Hz in the originalstudy, 0.01–30 Hz here. The 0.3-Hz high-pass setting used bySmith~1993! may reduce the amplitude of broad signals such asthe P300, and the 100 Hz low-pass setting was not necessarybecause nearly all EEG activity occurs in frequencies below30 Hz.

5. In the original study, trials contaminated by artifacts such aseyeblinks were excluded from the averages. In the present studywe did not reject trials that included eyeblink or eye-movementartifacts. Instead, an eye-movement correction procedure~Grat-ton, Coles, & Donchin, 1983! was applied to all the data. Theonly trials that were excluded from averages were ones in whichanalog0digital converter saturation occurred or amplifier chan-nels went flat.

6. Subjects had to have at least 15 trials in each condition to beincluded in an analysis. A minimum-trial criterion was not re-ported in Smith~1993!, although the author did report exclud-ing two of the subjects due to excessive eyeblink artifacts.

7. Analyses of variance~ANOVAs! used the Greenhouse–Geissercorrection~Keselman & Rogan, 1980!.

SubjectsTwenty undergraduates from the University of Illinois at Urbana-Champaign gave their informed consent and were paid for theirparticipation in the study. Two subjects’ data were not used be-cause they did not make enough K responses. The analyses pre-sented here are based on data from the 24 remaining subjects~13women, 11 men; ages ranged from 18 to 37 years; 19 right-handedsubjects, 1 left-handed subject, 4 no data as assessed by the Ed-inburgh Handedness Inventory@Oldfield, 1971#!.

Stimuli and Word ListsStimuli were words randomly selected from the 3–7 letter nouns ofthe Rubin and Friendly~1986! category norms. They were pre-sented in white upper-case letters for 300 ms on a computer mon-itor approximately 1 m from the subject. The stimuli wereapproximately 0.58 of visual angle in height and between 1.4–3.28of visual angle in width. Five independent sets of 100 words apiecewere drawn at random from the master set. One of these sets wasalways used for the practice block, and the other four sets werepresented in a random order for each subject. The study list in eachblock consisted of 50 words, and the corresponding test list wasmade up of the same 50 words~old! plus the remaining 50~newwords! from the set. The lists used for study and test were coun-terbalanced across the subjects so that the study words for one halfof the subjects were the new test words for the other subjects andvice-versa. The words used as stimuli for the oddball task were notpart of the lists for the memory task.

Experimental ProceduresSubjects were seated in an acoustically shielded, dimly lit room.The experiment consisted of one practice block before electrodeswere attached, then four blocks followed by an “oddball” task. Forthe study phase of each block, subjects made a subjective judgmentas to whether each item was “interesting” or “uninteresting.” Eachtrial began with a fixation cue~“.,” ! presented for 500 ms in thecenter of the display. It was followed by a word that was displayedfor 300 ms, replaced by a blank screen. The next trial would begin2,000 ms after word onset. All subjects responded by pressing the

left button of a response box for interesting words and the rightbutton for uninteresting words. After a 2-min pause the test phasebegan. The subjects’ instructions for the test phases were to firstdecide if each word was “old”~i.e., it had occurred in the previousstudy block! or “new.” The subjects were given the followinginstructions to follow if the word was thought to be old:

Often, when remembering a previous event or occurrence, we con-sciously recollect and become aware of aspects of the previous experience.At other times we simply know that something has occurred before, with-out being able to remember detailed information about that past occur-rence. For example, you probably have had the experience of recognizingsomeone, without being able to remember where you met that personbefore. When you see a word in the test portion, think about whether youcan consciously remember what you were experiencing when you first sawthe word. If you can, then categorize it as an R item when the response cueoccurs.

If however you are confident that a test word occurred on the studylist, but can’t recollect many details about your experience when you firstsaw it, then categorize it as a K item when the response cue occurs.

As in the study trials, each test trial began with a 500-msfixation cue followed by a word, presented for 300 ms, and then ablank screen. At 2,000 ms after word onset, a response cue waspresented for 2,000 ms, and then the next trial would begin with afixation cue. The response cue was composed of the letters “R”and “K” to the left and right of the center of the display. Thepositions of the letters varied randomly from trial to trial, so thaton half the trials the response cue was “R K” and “K R” for theother half. To respond with a “remember” judgment, subjects pressedthe button~left or right! corresponding to the letter R, and pressedthe button corresponding to K for “know” judgments. Thus, sub-jects were discouraged from preparing a response until after theresponse cue was presented. No response was to be made to wordsjudged as New. On the average, there was a 6.8-min delay betweenthe presentation of a word during the study phase and its presen-tation in the corresponding test phase.

Electrophysiological Recording and ProcessingThe EEG was recorded from tin electrodes at the right mastoid and13 scalp sites in an electrode cap~Electro-Cap International! ref-erenced to the left mastoid. Scalp sites were from the International10-20 system~Jasper, 1958!: F3, Fz, F4, C3, Cz, C4, P3, Pz, P4,T5, T6, O1, and O2. Electrode impedances were below 10,000Vand within 5,000V of each other. A vertical electrooculogram~EOG! was recorded from electrodes placed at supra- and infra-orbital sites around the right eye, and the horizontal EOG wasrecorded from electrodes placed on the outer canthi of the left andright eyes. Ag0AgCl electrodes were used for EOG recordings andwere bipolar referenced. A Grass Model 12 amplifier system wasused to amplify the electrophysiological signals, which were sam-pled continuously at 200 Hz. The continuous data recordings wereedited offline to obtain 2,300-ms-long single-trial epochs, begin-ning 300 ms before word onset and ending 2,000 ms after wordonset. EEG recordings were algebraically re-referenced to linkedmastoids and corrected for eye movements~Gratton et al., 1983!.Individual subject averages were derived for each condition~R, K,and New responses in the test phase! and were baseline-correctedusing a 100-ms prestimulus baseline. The ERP data from the studyphase are not presented in this report, because we obtained thesame results as Smith~1993!, and the data are not pertinent to ourexperimental hypotheses.


Latency Jitter Correction (LJC) ProceduresLJC of the P300 component was performed using a peak-pickingtechnique and digital filter passband selected on the basis of asimulation study~Spencer & Donchin, 1996!. This simulation ex-amined the efficacy of several latency-estimation techniques~in-cluding peak picking and template matching! with different filterranges, under various signal-to-noise ratios. Before LJC, each sin-gle trial epoch was baseline corrected with the 100-ms prestimulusbaseline and digitally filtered~0–1 Hz! to remove contaminationfrom higher-frequency “noise” in the EEG. The peak-picking tech-nique simply finds the most positive point within a specified rangeof the epoch and reports its latency and amplitude. Because theamplitude of the P300 is generally maximal at the Pz electrode site,single-trial latency estimates were calculated using this site. Oncethis procedure has been performed on all the single trials for agiven condition and subject, the epochs are shifted so that for eachtrial the peak of the P300 is aligned with the mean of the single-trial latencies. The shifted trials are then used to compute a newERP in which the P300 has been corrected for latency jitter.

A basic assumption of LJC is that each trial contains the targetcomponent~in this case, the P300!. Otherwise noise waveforms

may be included in the post-LJC average, and the amplitude andlatency of the target component in the post-LJC average will not beestimated accurately. Thus, some procedure must be used to dis-tinguish trials containing the target component from the trials thatdo not~cf. Ford, White, Lim, & Pfefferbaum, 1994!. We identifiedtrials that contained P300s using the amplitude and latency distri-butions of the largest positive peaks identified by the peak-pickinglatency estimation technique. This procedure is illustrated for fourrepresentative subjects in Figure 2. This figure displays the pre-LJC ERPs for the R and K conditions~top!, the distributions ofsingle-trial amplitude and latency estimates from the peak-pickingtechnique~middle!, and the resulting post-LJC ERPs~bottom!.The peak-picking technique was applied to the sets of R and Ktrials for each subject individually. In the first phase of LJC, thelargest positive peak across the poststimulus epoch~0–1,800 ms!was found for each trial. This phase typically produced a multi-modal distribution, with a prominent cluster of peaks in the latencyrange of the P300 in the average ERP. A smaller cluster of peakswas usually found in the latency range of the P2 component.~Notethat in experimental paradigms that require subjects to categorizevisually presented words, the latency of the P300 is often around

Figure 2. Examples of the results from the latency jitter correction~LJC! procedure~see Methods! for four representative subjects.Top row: Pre-LJC averages~site Pz shown!. Middle row: Output of peak-picking technique. The latency and amplitude of the mostpositive peak detected between 0 and 1,800 ms on each trial is plotted. Brackets indicate the latency range of the trials included in LJC.Bottom row: Post-LJC averages~Pz site!.


600 [email protected]., Fabiani, Gratton, Karis, & Donchin, 1987#, so it isreasonable to expect that the P2 and P300 single-trial distributionswill not overlap in the present paradigm.! If the P300 in the pre-LJC average ERP returned to baseline before the end of the epoch,another group of post-P300 positive peaks would often be found atthe end of the epoch, probably representing noise waveforms.

If the peak-picking technique was detecting random noise wave-forms rather than true ERP waveforms, it might be expected thatthe distribution of single-trial latencies across the epoch would berectangular, that is, approximately equal in each part of the epoch~Donchin & Heffley, 1978!. To examine this possibility, the single-trial latency distribution for each subject and condition~R and K!was submitted to a chi-squared test for goodness of fit, testing theobserved distribution against the null hypothesis of a rectangulardistribution. For each combination of subject and condition, thistest was statistically significant~at a 5 0.05!, indicating that thepeak-picking technique was successfully detecting ERP wave-forms, not noise.

The distributions of positive peak amplitudes and latencies wereused to select trials containing P300s. If the most positive peak ona given trial was in the P2 range, or in the post-P300 range, thenwe deemed it unlikely that a P300 had been elicited on that trial,because the P300 probably would have been larger in amplitudethan the small P2. The distributions of single-trial peak amplitudesin the P2, P300, and post-P300 latency ranges overlapped in thelower amplitude range~Figure 2, middle row!, so the peak-pickingtechnique was not likely to have been biased toward selecting anon-P300 peak when a small P300 had been elicited on a particulartrial. Therefore, trials on which the most positive peak did not fallwithin the P300 latency range were excluded from the set of trialsto be latency corrected for the post-LJC average. The latency rangefor included trials typically began after the P2 peak latencies, atabout 450 ms, and extended to the end of the P300 waveform~orto the end of the epoch, if the P300 did not return to baseline! inthe pre-LJC average. The latency ranges for trials included in LJCare shown for the representative subjects in the middle row ofFigure 2.

Once the set of trials containing P300s had been selected for agiven condition and subject, the mean single-trial P300 latencywas computed, and the epochs were shifted so that the P300 peakon each trial was aligned to this latency. The standard deviation ofsingle-trial latencies was used as a measure of latency jitter. Post-LJC P300 peak amplitude was measured from the unfiltered, post-LJC ERP average.

It should be noted that we also attempted to perform LJC on theNew trials~that is, on test trials in which we presented words thatwere not included in the study list!. However, we found that it wasimpossible to select trials containing P300s using the method de-scribed above. The chi-squared goodness-of-fit test for the Newtrials did not differ significantly from a random distribution formost of the subjects. Our failure to detect a substantial number ofP300s in the New single trials is consistent with the average ERPs,which suggest that New judgments elicited few or no P300s. Thisresult provides further support that the LJC procedure could dis-tinguish successfully between single trial distributions that did anddid not contain P300s.

PCA ProceduresTwo PCAs ~Donchin & Heffley, 1978! were performed on thedata. The first PCA was performed on the pre-LJC R, K, and Newaverages on all electrode sites for each subject. The second PCAwas performed on the post-LJC R and K averages, again on allelectrode sites for each subject. The PCAs were based on thematrix constructed by computing the covariance between all pairsof time points in the 0–1,300-ms period~digitally filtered at 0–8 Hz,then resampled at 100 Hz! across experimental conditions, elec-trode sites, and subjects. All factors that each accounted for morethan 1% of the total variance were retained and rotated with theVarimax procedure.

Statistical AnalysesThe dependent variables used to analyze the ERP data were:~1! av-erage amplitude averaged across all scalp sites~prior to LJC!,which is the measure Smith~1993! used to analyze the R.K

Figure 3. Left: Percentages of test items classified into each category for Smith~1993! and the present replication study. Right:Percentages of items classified during study as “interesting” or “uninteresting” according to the responses they elicited at test~“remember” or “know”!. Standard deviation bars are shown.


effect; ~2! peak amplitude at Pz~after LJC!, which corresponds tothe LJC method;~3! the mean of single-trial P300 latencies~de-rived from LJC!; ~4! the standard deviation of single-trial P300latencies, as a measure of latency jitter~also derived from LJC!;and ~5! factor scores from PCA averaged across all scalp sites,before and after LJC. Average amplitude and pre-LJC PCA factorscores were submitted to an ANOVA with response type~R0K 0New! as the factor. These measures were also analyzed with plannedcomparisons~R0K, R0New, and K0New! to identify the factor~s!that could contribute to an R.K effect, if such an effect werefound. Post-LJC measures~P300 peak amplitude, mean single-triallatency, standard deviation of single-trial latencies, and PCA factorscores! were submitted to an ANOVA with just the R and K re-

sponses as levels of the response type factor, because LJC wasperformed on just the R and K ERPs. For ANOVAs with more thantwo conditions, degrees of freedom were adjusted with theGreenhouse–Geisser correction for inhomogeneity of covarianceassociated with repeated measures designs~Keselman & Rogan,1980!.

Results

Overt Response MeasuresConfirming Smith~1993!, the proportion of interesting and un-interesting responses assigned to words presented in the studyphase did not differ. In the left-hand side of Figure 3 are compared

Figure 4. Test phase event-related potentials~ERPs! from the present study, all electrode sites.


the recognition data acquired in the test phase in our study with theequivalent data reported by Smith~1993!. Subjects made more Rthan K responses to correctly classified old words,F~1,23! 5 9.32,p , .01, and a greater proportion of the errors on new items wereK, rather than R, responses,F~1,23! 5 21.45,p , .0001. Thesedata are similar to Smith’s, although subjects in our study hadsomewhat higher error rates and variances. In contrast to Smith’sfindings, however, there was an association between study- andtest-phase judgments, as shown in the right-hand side of Figure 3.R words were likely to have been classified as interesting,F~1,23! 543.94,p , .0001, and K words were likely to have been classifiedas uninteresting,F~1,23! 5 61.27,p , .0001.

Test Phase ERPsIn Figure 1 are exhibited the ERPs recorded during the test phaseat the midline electrodes by Smith~1993! together with the cor-responding waveforms from our data. The test phase ERPs re-corded at all the electrodes used in our study are shown in Figure 4.Visual inspection of the two data sets indicates that we have suc-cessfully replicated Smith’s~1993! finding of an R.K effect onP300 amplitude, in addition to a general Old.New P300 effect.The average amplitude of the P300~measured in the 500–900-mslatency range! was largest for R items, smaller for K items, and

smallest for New items~see Figure 5!. An overall effect of con-dition ~R0K 0New! was found, as well as significant differencesbetween the R and K, R and New, and K and New P300s.~SeeTable 1 for ANOVA results.!

As can be seen in Figure 1, the pattern of the waveforms of ourdata match the pattern reported by Smith~1993!. We are, however,inclined to consider the positive wave peaking at around 600 ms asan instance of the P300~Sutton et al., 1965!. We do so becausethese data are entirely consistent with the attributes of the P300~Fabiani et al., 1987!. The scalp distribution is clearly that char-acterizing the P300~Pz.Cz.Fz!, the entire sequence satisfies thedefining attributes of an oddball paradigm~Donchin & Coles,1988!, and the latency range is clearly that encompassing the P300~Fabiani et al., 1987; Kutas et al., 1977!. This conclusion is sup-ported by the results of the PCA reported below.

LJCThe grand-average ERPs from the midline sites are presented inFigure 6, in which we compare ERPs computed before and afterLJC.~Note that while LJC was performed with a 0–1-Hz filter, thepost-LJC ERPs in Figure 6 are presented without filtering.! In theLJC data, P300 amplitude was measured as the peak amplitude atPz, as in the LJC procedure~see Methods!. P300 latency wasmeasured as the mean of single-trial latencies, and the standarddeviation of single-trial latencies was used as a measure of theamount of latency jitter. P300 peak amplitude for the R and Kconditions was 21.4 and 21.9mV, respectively, and these valuesdid not differ,F~1,23! 5 0.25,p . .05. Thus, LJC of the R and KP300s eliminated the amplitude difference that constitutes the MESof Smith ~1993!. P300 mean latency was shorter for R items thanK items, 778 vs. 874 ms:F~1,23! 5 14.60,p , .001; and the RP300s had a smaller latency standard deviation, and hence lesslatency jitter, than the K P300s, 196 vs. 251 ms:F~1,23! 5 14.27,p , .001. These results are consistent with our hypothesis that theR.K effect results from different amounts of P300 latency jitter inthe two conditions.

Thus, the LJC data support our view that the difference in P300amplitude between the R and K conditions was due to differencesin the degree of latency jitter between the conditions, not to anintrinsic difference in P300 amplitude. Furthermore, our data donot provide any support for the assertion that the R.K effect in theERPs prior to LJC was due to some ERP activity overlapping theP300, because LJC of the P300 eliminated the effect. This hypoth-esis was also tested directly by using PCA.

Figure 5. Average amplitude of the event-related potential~ERP! in the500–900-ms interval for the remember~R!, know~K !, and New conditionsat the midline electrode sites.

Table 1. Pre-LJC Statistical Results for P300 Average Amplitude and PCA Factor Scores Averaged Across all Sites

ANOVA Avg. amp. Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7

R0K 0New 15.78 0.56 33.63 0.75 2.54 1.55 5.05 1.15~2,46! **** **** *R0K 6.05 0.52 28.13 0.02 0.53 0.07 3.49 1.13~1,23! * ****R0New 27.93 0.07 53.60 1.04 2.55 2.50 1.20 0.13~1,23! **** ****K 0New 11.27** 1.04 13.07 1.83 4.46 2.67 13.95 1.90~1,23! ** * **

Note:ANOVAs were performed with the condition factor consisting of each combination of the levels “remember”~R!, “know”~K !, and New. LJC5 latency jitter correction; PCA5 principal components analysis.Degrees of freedom are presented with each ANOVA, along withF ratios for the dependent variables tested. Asterisks indicate thelevel of significance of theF test if obtained: *p , .05. **p , .01. *** p , .001. **** p , .0001.


PCATo determine whether there was an R.K effect in addition to theP300 elicited by the stimuli, the test phase ERPs were submitted toPCA~see Methods!. PCA identifies sources of variance in the ERPacross experimental conditions and is useful for teasing apart over-lapping ERP components. If another component of the ERP isresponsible for the R.K effect, then such a component should beextracted from the variance by PCA. Thus, the MES should emergeas a factor that differentiates between the R and K conditions, andis active in the same latency range in which the R.K effect isobserved. The factor corresponding to the MES should possess ascalp distribution consistent with this effect. Thus we performedtwo PCAs, the first on the pre-LJC R, K, and New ERPs, and thesecond on the post-LJC R and K ERPs.~A PCA on just the pre-LJCR and K ERPs was also performed but is not presented here,because the factor patterns and statistical results were nearly iden-tical to those from the R0K 0New PCA.!

Seven factors were extracted in the pre-LJC PCA. The factorloadings are presented in Figure 7, the factor scores in Figure 8,and the percentage of variance accounted for by each factor after

Figure 6. Pre- and post-latency jitter correction~LJC! event-related potentials~ERPs! at midline electrode sites for the remember~R!and know~K ! conditions. Note that the amplitude scale has been altered from the scales in Figures 1 and 3 to accommodate the largeramplitude of the post-LJC P300 component. Also, while LJC was performed with a 0–1-Hz filter, the post-LJC ERPs are presentedwithout filtering.

Figure 7. Factor loadings for the principal components analysis~PCA! onprelatency jitter correction~LJC! remember~R!, know ~K !, and Newevent-related potentials~ERPs!.


rotation in Table 2. Because the loadings and scores of Factor 2correspond to the time course and scalp distribution, respectively,of the P300 in the grand-average ERPs~for comparison refer toFigures 4 and 5!, we associate this factor with the P300 compo-nent. By comparing the patterns of statistical results for P300average amplitude and the scores for the seven factors in Table 1,it can be seen that the only factor that differs between the R, K, andNew conditions in a manner consistent with the P300 is Factor 2.Whereas Factor 6 occurs during the latency range of the R.Keffect and differs significantly between the R, K, and New condi-tions, this factor could not account for the R.K effect because itmainly differs between the K and New conditions. The scores forFactor 6 are in fact somewhat larger for the K condition than theR condition. Therefore, Factor 6 is not responsible for the R.K

effect, and if anything, it would serve to decrease this effect in thevoltage data. Thus, there does not appear to be any other source ofvariance in the data that could account for the R.K effect otherthan the P300.

This conclusion is supported by the PCA on the post-LJC R andK ERPs~see Figure 9 for factor loadings and scores, and Table 2for percentages of variance accounted for by each factor!. In thisPCA, Factor 3 clearly represents the P300 component, and there isno significant difference between its scores for the R and K con-ditions,F~1,23! 5 1.55,p . .05. Neither is there an effect on thescores of Factor 1,F~1,23! 5 0.00,p . .05. Factor 3 does differbetween the R and K conditions,F~1,23! 5 5.58,p , .05, but asfor Factor 6 in the pre-LJC PCA, this factor would only decreasean R.K effect if one had been observed. As in the PCA on the

Figure 8. Factor scores for the principal components analysis~PCA! on pre- latency jitter correction~LJC! remember~R!, know ~K !,and New event-related potentials~ERPs!.

Table 2. Percentages of Variance Accounted for by Each Factor After Varimax Rotation,for the Factors Extracted in the Pre- and Post-LJC PCAs

PCA Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7

Pre-LJC 57.4 17.3 9.6 3.3 2.4 1.8 1.3Post-LJC 91.3 3.6 2.1 — — — —

Note: LJC 5 latency jitter correction; PCA5 principal components analysis.


pre-LJC ERPs, no factor displays a pattern of results that would beconsistent with some ERP activity that overlapped the P300 toproduce the R.K effect.

We thus conclude that the R.K effect can be explained as aneffect due to the P300 component, not to some other ERP activityrelated to recollection processes. It appears that the difference inP300 amplitude between R and K ERPs was caused by differentamounts of P300 latency jitter in these conditions, and this con-clusion is supported by several converging measures: P300 ampli-tude before and after LJC, variance in single-trial latencies, andPCAs on the ERPs before and after LJC.

Discussion

Smith~1993! reported that when subjects were instructed to reportwhether experiences of recollection or feelings of familiarity ac-companied their recognition of items from a study list, the sub-jects’ responses were associated with different ERPs. Smith did notattribute this difference to a currently known ERP component, andargued instead that this “memory-evoked shift” is an altogethernew component, different from the P300, representing the “neuro-physiological manifestation of the recollective experience.” In otherwords, the recollective experience is, presumably, due to the ac-tivity of neural structures whose activity is manifested on the scalpby the ERP difference. We argue that the difference in process-ing between the R and K trials is not in the activation of aspecifically “recollection-related” structure, but is rather a conse-

quence of the fact that the R decisions are reached with a moreconsistent latency than are the K decisions. As a consequence, thedifference reported by Smith is due to different amounts of P300latency jitter between the R and K conditions. After replicatingSmith’s paradigm and obtaining mostly the same patterns of overtresponse and ERP data, we applied an LJC technique and foundthat removal of P300 latency jitter eliminated the R.K effect.Furthermore, PCA did not identify any sources of variance otherthan the P300 that could account for this effect. Hence we haveconcluded that the R.K effect, in our data at least, is due todifferent degrees of P300 latency jitter in the two conditions. Itshould be noted that our data leave us agnostic regarding theexistence of recollection specific structures. These may very wellexist but their existence does not derive from the data of Smith andthe present data.

Our analysis thus indicates that the R and K responses werecorrelated with different amounts of variance in the timing of theprocess that is manifested by the P300. R responses were associ-ated with P300s that had shorter, less variable single-trial latenciesthan the P300s associated with K responses. This finding may bethe result of the task instructions, in which subjects were told tofirst decide if they could “consciously remember” what they wereexperiencing when they saw the current item in the study task. Ifthey had such a recollective experience, they were told to make anR response. Otherwise, they were instructed to make a K responseif they could not “recollect many details” about their experiencewhen the item was first seen. One possible explanation for the

Figure 9. Factor loadings~top! and scores~bottom! for the principal components analysis~PCA! on post-latency jitter correction~LJC! remember~R! and know~K ! event-related potentials~ERPs!.


pattern of single-trial P300 latencies we found may be that subjectsused a strategy like the following:

First, a search ensued for representations related to the occur-rence of the item in the study task. If such representations could befound, strong enough to satisfy some subjective criterion, the searchwould be terminated and an R response made. If this criterion wasnot met, subjects would next evaluate whether they had a “feelingof familiarity,” again using some subjective criterion, to justify a Kjudgment. If this criterion was met, a K response would be made,and if not, a “default” New judgment would be reached, whichwould not require an overt response. R decisions would thus bemade faster than K decisions, and as P300 latency is correlatedwith the latency of the decision process~Kutas et al., 1977;McCarthy & Donchin, 1981!, R P300s would have shorter laten-cies on the average than K P300s. The greater latency variability ofK P300s, as compared with R P300s, could be due to an increasedvariability in the timing of the K decision as its latency increases.

Even if LJC did not completely remove the R.K effect, thereare problems with Smith’s view that the effect could not be attrib-uted to the P300. According to his first argument, a larger P300amplitude for R than K items could be explained if there was alower “subjective probability” that an old item would elicit an Rthan a K response. However, the opposite situation is much morelikely. Note that correctly recognized old words were more likelyto result in R than K responses. Thus, the subjective probabilityassociated with K items was lower than the subjective probabilityof the R items. As a consequence, the K items should have elicitedlarger P300s, because it is well known that the amplitude of theP300 evoked by a stimulus in an “oddball” series is inverselyrelated to the probability of that stimulus~Duncan-Johnson &Donchin, 1977!. ~Although the subjective probability of a stimulusat a given point in a series is not necessarily the same as its globalprobability.!

However, it may be the case that the classical probability ef-fects associated with P300 amplitude in an oddball task do notcome into play in the R0K paradigm. In an oddball task, P300amplitude is inversely related to stimulus probability when sub-jects attend to the probability structure of the stimulus series~Duncan-Johnson & Donchin, 1982; Squires et al., 1976!. It isplausible that probability effects were not apparent in this taskbecause subjects did not devote as much attention to the probabil-ity structure of the series as they would have in a simple oddball.Donchin and Coles~1988! pointed out that the elicitation of aP300, and its amplitude and latency, depend not on the sequence ofphysical stimuli presented to the subject but, rather, on the mannerin which the sequence is organized into a sequence of “events.”Within the framework of the context-updating model the elicitationof the P300 will be determined by events that force a reevaluationof the validity of the current model of the context. In the studyreported here, the critical events included the combination of aword with its recognition or nonrecognition as coupled with theactual choice made by the subject between the R and K responses.The relation of these item-specific events interacts, in determiningP300 amplitude, with the immediate past history of the sequence.

In the classic oddball paradigm, subjects may be instructed tokeep an internal count of one class of stimuli, or to make responsesto one or all of the stimulus categories. The task requirements ofthe R0K paradigm are much more complex. The subjects decidewhether a word is old or new and for words judged old, thesubjects must focus attention on their internal state to determinewhether their decision was associated with a recollective experi-ence of the study episode, or a feeling of familiarity for the item.

In fact, it is not the test items themselves that are being classifiedby the subjects but their internal experiences. Therefore, subjectsin the Smith ~1993! recognition task would not be expected toattend to the probabilities of the R and K items to the degree thatthey would attend to the probabilities of stimuli in an oddball task,and the probabilities of the R and K items therefore would not havea large effect on P300 amplitude.

Smith ~1993! further suggested that because both R and Kitems were old words, they possessed the same “subjective target-ness” in comparison with new words, and thus the two types of oldwords should evoke P300s with the same amplitudes. As improb-able nontargets elicit a P300 that is much larger than that elicitedby probable targets~Duncan-Johnson & Donchin, 1977!, there isno reason to assume that “subjective targetness”~a term undefinedby Smith! plays any defining role in identifying the P300. It is truethat for fixed levels of probability items embedded in task relevantsequences will elicit a larger P300. Smith may be assuming that theR and K items were targets assigned the same task relevance.Considering that the recognition task instructions stressed the oc-currence of a recollective experience for making the R0K judg-ment, as discussed above, a larger P300 amplitude on R trials, hadit been observed to survive the LJC analysis, may be readily ex-plained by the fact that R items were assigned a greater degree oftask relevance~Johnson & Donchin, 1978!.

Another issue of concern is that other reported effects in theERP0memory literature may be similarly confounded by latencyjitter, because LJC methods are seldom used in these studies. Onereason why LJC is rarely applied may be that some investigatorsare not as concerned as we are with analyzing the componentialstructure of the effects. All too often one encounters the assertiononce a difference has been established between the ERPs elicitedin two experimental conditions the goal of the study has beenachieved. There is no need, the argument goes, to engage in thedifficult process of decomposing the difference to determine which,if any, of the known ERP components underlies the difference. Wedo not find this case to be compelling. We suggest that it is moreuseful to isolate processes used by the human information process-ing system in acquiring, processing, organizing, storing, and re-trieving information, all of which participate in the phenomenaglobally subsumed under the rubric of “memory.” A detailed com-ponential examination of the ERPs recorded during the study andtest phases of a memory experiment is more likely to reveal theunderlying processes. Investigators need to relate psychologicalconstructs to variability in the processes manifested by specificERP components, rather than simply associating global undiffer-entiated ERP “difference waves” with the constructs~e.g., the Dm@Paller et al., 1987#; and the MES@Smith, 1993; Smith & Guster,1993#!. The wider use of ERP decomposition methods, such asPCA, would be helpful in this regard.

Donchin and Fabiani~1991! termed these two approaches tothe use of ERPs in cognitive neurosciencealgorithmic mappingand construct mapping, respectively. With construct mapping, apsychological construct is directly associated with an ERP effect.An example is Smith~1993!, in which the R.K effect was directlyrelated to recollective experience. When there is a difference inERPs between experimental conditions, the investigator identifiesthe ERP effect with the construct that is assumed to be affected bythe experimental manipulation. This construct probably comprisesa large number of more elementary processes and the global dif-ference wave approach does not allow a detailed examination ofthe internal structure of the construct. With algorithmic mapping,on the other hand, the ERP effect is mapped to variance in the


computational processes that are manifested by amplitude and0orlatency variance in ERP components. These processes are but asmall part of the set that underlies the proposed psychologicalconstruct. For instance, in this study, we related the differencebetween R and K ERPs to differences in the variance of P300

latency on single trials, which we proposed was correlated with thelatency of the R0K decision process. In our opinion, algorithmicmapping is the more fruitful approach for the study of ERPs andmemory processes.

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~Received December 10, 1998;Accepted August 6, 1999!


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On the search for the neurophysiological manifestation of recollective experience