Cerebral Cortex V 14 N 3 © Oxford University Press 2004; all rights reserved Cerebral Cortex March 2004;14:256–267; DOI: 10.1093/cercor/bhg125

Temporal and Cerebellar Brain Regions that Support both Declarative Memory Formation and Retrieval

Susanne Weis1, Peter Klaver1, Jürgen Reul2, Christian E. Elger1 and Guillén Fernández1,3

1Department of Epileptology, University of Bonn, 53105 Bonn, Germany, 2Department of Diagnostic and Therapeutic Neuroradiology, Medical Center Bonn, 53119 Bonn, Germany and 3F.C. Donders Center for Cognitive Neuroimaging, University of Nijmegen, 6500-HB Nijmegen, The Netherlands

Using event-related fMRI, we scanned young healthy subjects whilethey memorized real-world photographs and subsequently tried torecognize them within a series of new photographs. We confirmedthat activity in the medial temporal lobe (MTL) and inferior prefrontalcortex correlates with declarative memory formation as defined bythe subsequent memory effect, stronger responses to subsequentlyremembered than forgotten items. Additionally, we confirmed thatactivity in specific regions within the parietal lobe, anteriorprefrontal cortex, anterior cingulate and cerebellum correlate withrecognition memory as measured by the conventional old/new effect,stronger responses for recognized old items (hits) than correctlyidentified new items (correct rejections). To obtain a purer measureof recognition success, we introduced two recognition effects bycomparing brain responses to hits and old items misclassified as new(misses). The positive recognition effect (hits > misses) revealedprefrontal, parietal and cerebellar contributions to recognition, and inline with electrophysiological findings, the negative recognitioneffect (hits < misses) revealed an anterior medial temporal contribu-tion. Finally, by inclusive masking, we identified temporal and cere-bellar brain areas that support both declarative memory formationand retrieval. For matching operations during recognition, theseareas may re-use representations formed and stored locally duringencoding.

Keywords: declarative memory, event-related, fMRI, memory formation, recognition, retrieval

IntroductionThe kind of memory one ordinarily means when using the term‘memory’ is declarative memory, which enables us toconsciously remember past events and facts (Cohen andSquire, 1980). Declarative memory is based on at least twofundamental mnemonic operations: memory formation andretrieval (Gabrieli, 1998). Since only a few years ago, event-related functional magnetic resonance imaging (ER-fMRI) hasprovided the unique opportunity to study the neural correlatesof these mnemonic operations with great anatomical detail inhealthy human subjects (Dale and Buckner, 1997; Josephs et

al., 1997; Zarahn et al., 1997). Using ER-fMRI, encoding studieshave shown that successful declarative memory formation,measured as the difference in brain activity between subse-quently remembered and forgotten items, is accompanied byactivity increases in medial temporal and inferior prefrontalareas (e.g. Brewer et al., 1998; Wagner et al., 1998; Kirchhoffet al., 2000; Davachi et al., 2001; Otten et al., 2001; Otten andRugg, 2001a; Strange et al., 2002; Morcom et al., 2003: for areview, see Paller and Wagner, 2002) and activity decreases inposterior cingulate, parietal and dorsolateral prefrontal areas(Otten and Rugg, 2001b). ER-fMRI studies acquiring fMRI data

during simple recognition memory tests and applying the so-called old/new effect, the difference in brain activity betweencorrectly recognized old, previously studied items (hits) andcorrectly identified new, previously unstudied items (correctrejections), have shown activations in the anterior prefrontalcortex, parietal cortex, insula and medial-frontal areasincluding the anterior cingulate (e.g. Henson et al., 1999;Konishi et al., 2000; Donaldson et al., 2001a,b; for a review,see Rugg and Henson, 2002). The first aim of the present studyis to replicate these subsequent memory and old/new effects,which were so far obtained in separate encoding and retrievalexperiments, within a single study-test experiment.

Based on this empirical foundation, we aim to explore in thesecond step of this study whether recognition success can beassociated with both regional brain activity increases anddecreases. Brain activity increases for hits as compared tocorrect rejections (old/new effect) have been interpreted asrelated to the successful recovery of information from declara-tive memory (Donaldson and Buckner, 1999; Konishi et al.,2000; Donaldson et al., 2001a,b). A reversed old/new contrast,however, cannot delineate cleanly a brain activity decreaserelated to recognition success, because it would be heavilycontaminated by neural correlates of repetition priming(Buckner and Koutstaal, 1998; Donaldson et al., 2001a).Repetition priming is an implicit memory phenomenon thatimproves processing efficacy of repeatedly processed itemsand that is regularly accompanied by weaker brain activity toold as compared to new items (Tulving and Schacter, 1990; butsee Henson et al., 2000). However, repetition priming does notsupport conscious recognition (Donaldson et al., 2001a). Thus,the question that remains open is: can only repetition primingor also conscious recognition correlate with a decrease inneural activity? (Henson et al., 2003). Electrophysiological datain animals and humans suggest that recognition can also beaccompanied by brain activity decreases (Smith et al., 1986;Brown et al., 1987; Miller and Desimone, 1994; Brown andAggleton, 2001; Fernández et al., 2001). As outlined above, wecannot simply reverse the old/new effect. Rather, analogous tothe subsequent memory effect, we compare brain activity tocorrectly recognized old items (hits) and old items misclassi-fied as new (misses). In this contrast, henceforth called therecognition effect, all items are studied once before, but recog-nition success differs. Hence, a negative recognition effect(misses > hits) seems to be less contaminated by repetitionpriming than a reversed old/new effect, at least when primedand recognized items show stochastic independence in thesense that performance in the two tasks is uncorrelated at thelevel of individual items (Shimamura, 1985). And in addition,the recognition effect might generally be more closely relatedto recognition success than the old/new effect, because it does

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not include any difference related to the actual study status ofthe items. Thus, as our second goal, we aim to identifyincreases and decreases in brain activity associated with recog-nition success as indexed by a positive (hits > misses) and anegative recognition effect (misses > hits). A recent meta-anal-ysis of four event-related fMRI studies employing differentkinds of study material suggested that less anterior MTL activityis related to the amount of familiarity across a variety ofstimulus materials (Henson et al., 2003). Another event-relatedfMRI study (Rombouts et al., 2001) found anterior parahippo-campal gyrus activation in a comparison of new to often seenitems, but this study did not control for performance. In linewith these findings as well as with electrophysiological data(Smith et al., 1986; Miller and Desimone, 1994; Brown andAggleton, 2001; Fernández et al., 2001), we expect negativerecognition effects in inferior temporal areas including theanterior MTL.

Given the encoding and recognition results of ER-fMRIstudies reported above, there seems to be no or almost nooverlap between brain areas involved in both memory forma-tion and recognition (see also Gabrieli et al., 1997). If,however, a brain area would support these two operations,neural representations stored locally during encoding could bere-used during recognition. Such a module would not only beefficient and intuitive, its existence is supported by electro-physiological data. For instance, the so called anterior MTL-N400, a negative component in event related potentialsrecorded invasively in epilepsy patients from the anterior MTL,probably from the perirhinal cortex (McCarthy et al., 1995)shows an amplitude difference between subsequently remem-bered and forgotten items during encoding (Fernández et al.,1999, 2002) as well as between correctly identified old andnew items during a recognition memory test (Smith et al.,1986). Therefore, this neural node within the anterior MTLseems to be critically involved in both memory formation andretrieval. However, most studies to date have examined eithermemory encoding or retrieval and have therefore not been abledirectly to compare encoding- and retrieval-related activationswithin subjects. The third aim of the present fMRI study is thusto characterize this node within a single study-test experimentby a functional imaging approach applying inclusively maskingof the subsequent memory effect and either the positive or thenegative recognition effect. Moreover, we aim to identifyfurther brain areas whose activity is correlated with bothsuccessful memory formation and recognition by whole braincoverage.

Material and Methods

SubjectsSixteen healthy volunteers (eight male, eight female) with normal orcorrected-to-normal vision participated in the experiment. Allsubjects were consistent right-handers according to the EdinburghHandedness Index (mean EHI = 88, range 73–100; Oldfield, 1971).Their mean age was 30 years with a range of 20–49 years. Followingapproval by the Medical Ethics Committee of the University of Bonn,all subjects gave their written informed consent according to theDeclaration of Helsinki (1991). They were paid for their participation.

Stimuli and TaskStimuli consisted of 480 color photographs of either buildings ornatural landscapes without any buildings (240 for each category) thatwere selected to be similar in complexity, brightness and contrast.

In the study phase, 120 randomly selected pictures of buildingswere randomly intermixed with 120 pictures of landscapes. Stimuliwere presented sequentially for 800 ms each with a randomized inter-stimulus interval (ISI) of 2000–3000 ms (mean 2500 ms). Sixty nullevents, consisting of a black screen shown for 2500 ms, wererandomly intermixed. Subjects were required to memorize eachpicture and to make a building–landscape decision by right-hand key-press.

In the following recognition phase, all stimuli from the study phaseplus 240 new, previously not presented photographs of buildings andlandscapes were shown sequentially and again randomly intermixed.The presentation rate was self-paced by subjects’ responses, resultingin a mean ISI of 2065 ms (SD 229 ms). Subjects were required to pressone of three keys according to the following response categories:picture seen before with high confidence, picture uncertain to beseen before or not, picture not seen before with high confidence.

Stimuli were presented using the Experimental Run-time System(http://www.erts.de) and back-projected onto a translucent screenpositioned opposite the magnet bore using an LCD-projector. Subjectsviewed the stimuli by way of a mirror mounted on the head coil whilelying in a supine position with their head stabilized by an individuallymolded vacuum cushion.

fMRI Data AcquisitionAll scans were performed on a 1.5 T scanner (Symphony; Siemens,Erlangen, Germany) using standard gradients and a circular polarizedphase array head coil. For each subject, we acquired two series, onefor the study phase and one for the recognition phase, of T2

*-weightedaxial EPI-scans including eight initial dummy scans parallel to the AC/PC line with the following parameters: number of slices (NS), 30; slicethickness (ST), 4 mm; interslice gap (IG), 0.4 mm; matrix size (MS),64 × 64; field of view (FOV), 220 mm; echo time (TE), 50 ms; repeti-tion time (TR), 2.95 s. The encoding run comprised 282 scans persubject. During recognition, we acquired 282–402 scans per subject(mean number of scans: 336), depending on the individual responsetimes. T1-weighted 3D-FLASH scans were acquired between thefunctional runs for anatomical localization (NS = 120; ST = 1.5 mm;IG = none; MS = 256 × 256; FOV = 230 mm; TE = 4 ms; TR = 11 ms).

fMRI Data AnalysisMR images were analyzed using Statistical Parametric Mapping(SPM99; www.fil.ion.ucl.ac.uk) implemented in MATLAB (MathworksInc., Sherborn, MA). To correct for their different acquisition times,the signal measured in each slice was shifted relative to the acquisi-tion time of the middle slice using a sinc interpolation in time. Allimages were realigned to the first image to correct for head movementand normalized into standard stereotaxic anatomical MNI-space byusing the transformation matrix calculated from the first EPI-scan ofeach subject and the EPI-template. Afterwards, the normalized datawith a resliced voxel size of 4 × 4 × 4 mm were smoothed with a 8 mmFWHM isotropic Gaussian kernel to accommodate intersubject vari-ation in brain anatomy. Proportional scaling with high pass filteringwas used to eliminate confounding effects of differences in globalactivity within and between subjects. All analyses were restricted totrials on which encoding responses were correct. The expectedhemodynamic response at stimulus onset for each event-type wasmodeled by two response functions, a canonical hemodynamicresponse function (HRF; Friston et al., 1998) and its temporal deriva-tive. The temporal derivative was included in the model to account forthe residual variance resulting from small temporal differences in theonset of the hemodynamic response, which is not explained by thecanonical HRF alone. The functions were convolved with the event-train of stimulus onsets to create covariates in a general linear model.During recognition, the presentation rate was self-paced, hence reac-tion time to recognition trials was included in the model as a nuisancevariable to discount the possibility of a confounding effect of differ-ences in reaction times. Parameter estimates for the HRF regressorwere calculated from the least mean squares fit of the model to thetime series. Parameter estimates for the temporal derivative were notconsidered in any contrast. Subsequently, effects of interest werespecified by appropriately weighted linear contrasts of the HRFparameter estimates and determined using planned comparisons on a

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voxel-by-voxel basis; the corresponding linear combination of param-eter estimates for each contrast were stored as separate images foreach subject. For the sake of our study goals, trials related to ‘uncer-tain’ responses were modeled by a separate regressor, but not consid-ered in any contrast.

An SPM99 group analysis was performed by entering contrastimages into one-sample t-tests, in which subjects are treated asrandom variables. Voxels with a significance level of P < 0.005uncorrected belonging to clusters with at least 10 voxels are reported.Since the subsequent memory effect and the recognition effect werecomputed bi-directionally, this effectively results in a two-sidedthreshold of P < 0.01. Activations are shown projected onto selectedcoronal slices of the mean high-resolution T1-weighted volume,highlighting regions of interest. The reported voxel coordinates ofactivation peaks were transformed from MNI space to Talairach andTournoux (1988) atlas space by non-linear transformations (http://www.mrc-cbu.cam.ac.uk/imaging/mnispace.html). To address fur-ther the question of overlap between areas involved in both encodingand recognition, we recomputed the subsequent memory effect andthe recognition effects with a statistical threshold of P < 0.05. Thenwe inclusively masked the subsequent memory effect by the positiverecognition effect and the negative recognition effect respectively.These analyses permit the identification, at a high level of sensitivity,of regions in which the subsequent memory effect overlaps with rec-ognition effects, while maintaining an acceptable type I error rate.According to Fisher’s method of combining probabilities, the prob-ability of two independent statistical tests conjointly attaining signifi-cance at P < 0.05 is P < 0.017.

Results

Behavioral ResultsDuring encoding, the building–landscape decision task wasmade with a mean accuracy of 92% (range 85–98%). Incorrectresponses were recorded for 5% (2–10%) and no responses for3% (0–7%) of all encoding trials.

Recognition memory performance and reaction times arelisted in Table 1. Accuracy of recognition was assessed by thedifference in probabilities of a correct old judgment and an oldjudgment for a new item (Pr = probability hit – probability falsealarm). While recognition performance did not differ betweenstimuli classes [mean Prbuilding = 0.40 (SD = 0.14) versus Prland-

scape = 0.43 (SD = 0.15), t15 = 1.019, n.s.], it was well abovechance level [mean Pr = 0.41 (SD = 0.13), t15 = 13.01; P <0.0001]. Collapsing across both stimuli classes (building andlandscape), we obtained a sufficient number of trials for eachresponse category to reach an adequate contrast-to-noise ratiofor our ER-fMRI analyses (78–153 trials per subject for hits,58–113 for misses, 93–170 for correct rejections and 52–97 forfalse alarms).

An ANOVA comparing reaction times (Table 1) for hits,misses, correct rejections, and false alarms revealed a reliableeffect of response category [F(3,45) = 8.42, P < 0.005]. Post-hocpaired-sample t-tests showed that reactions to correctly identi-fied old items were faster than incorrect reactions to old items(t15 = 3.78, P < 0.005), correct reactions to new items (t15 =3.21, P < 0.01) and incorrect reactions to new items (t15 = 5.99,P < 0.0001). All other post-hoc tests did not reveal any reliabledifference (max t15 = 1.51, n.s.).

Imaging DataIn an exploratory analysis, we directly compared encodingactivity to photographs showing either buildings or land-scapes. Processing of building stimuli compared to processing

of landscape stimuli showed small bilateral, left lateralized acti-vations in superior temporal areas [Talairach and Tournoux(1988) coordinates: x = 52, y = 8, z = –16 and x = –44, y = –4,z = –16], while processing of landscapes as compared to build-ings showed more activity in a small area of the right middlefrontal gyrus [Talairach and Tournoux (1988) coordinates: x =40, y = 20, z = 40). These findings may indicate a slightly higherdegree of verbal coding for buildings and non-verbal visual-perceptual coding for landscapes (Kelley et al., 1998). Given,however that these small differential effects are not of primaryinterest for the purpose of our study and that there is no differ-ence in recognition performance, both stimuli classes werepooled together to increase statistical power for all furtheranalyses.

Subsequent Memory EffectInitially, we sought to verify prior results regarding brainregions involved in successful formation of new declarativememories. Addressing this question requires a comparisonbetween learning events that lead to the successful and unsuc-cessful formation of memories. As in previous studies, weacquired brain responses to each item during study andconducted contrasts to compare events that were rememberedand those that were forgotten as measured by the subsequentrecognition memory test during the second experimental run.Figure 1 and Table 2 show brain regions that exhibit signifi-cantly more activity to subsequently recognized than forgottenitems. In line with previous findings, these encoding areascomprise bilateral fusiform and parahippocampal areas as wellas areas in the left basal and lateral frontal cortex [BrodmannArea (BA) 45, 47]. Additionally, we found an activation in theleft parietal lobe located in the angular gyrus (BA 39). Allactivations appear to be more pronounced in the left than theright hemisphere.

Negative Subsequent Memory EffectIn addition to areas predicting subsequent memory by anincrease of activation, we intended to identify areas in which adecrease of activation is associated with subsequent memory.Table 2 shows areas that exhibit significantly more activityduring learning for subsequently forgotten as opposed tosubsequently remembered items. For this contrast we foundactivations in right medial parietal cortex (BA 7) and in leftposterior cingulate cortex.

Table 1Mean recognition performance and reaction times (RT) with their standard deviations (SD)

Old New

Hits Misses Correct rejections False alarms Uncertain

Number 130 66 140 50 95

SD 28 23 23 19 62

RT (ms) 1382 1479 1462 1445 1727

SD 194 214 187 196 103

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Figure 1. Subsequent memory effect. Regions activated more in case of successful as opposed to unsuccessful memory formation during encoding. The activation map (P <0.005, uncorrected; minimal cluster size 10 voxels) is shown overlaid onto a canonical brain rendered in three dimensions. Specific activations are additionally shown superimposedonto selected coronal slices of the mean high-resolution T1-weighted volume. Slices are numbered according to coordinates of Talairach and Tournoux (1988). IFGa, anterior aspectof the inferior frontal gyrus; IFGp, posterior aspect of the inferior frontal gyrus; PHG, parahippocampal gyrus.

Table 2Activation peaks with their localization, significance level and the size of the respective activation cluster (number of voxels)

Effect Anatomical region BA Coordinates t-value No. of voxels

x y z

Subsequent memory effect Left angular g. 39 –28 –72 40 5.27 23

Left fusiform g. 20 –44 –48 –28 6.15 85

Right fusiform g. 37 24 –56 –16 4.31 37

Left. parahippocampal g. PHG 35 –20 –8 –36 4.15 11

Right parahippocampal g. PHG 35 36 –12 36 6.60 27

Left inferior frontal g. IFGa 47 –44 44 –12 4.56 36

Left inferior frontal g. IFGp 45 –40 12 28 6.60 40

Negative subsequent memory effect Right precuneus 7 8 –48 52 3.94 18

Left cingulate g. 24 –16 4 36 5.30 11

Repetition priming effect Left middle occipital g. MOG 19 –36 –92 8 5.15 17

Left middle occipital g. MOG 18 –20 –92 20 4.47 14

Right middle occipital g. MOG 19 28 –84 0 3.68 12

Left lingual g. LG 19 –32 –64 –4 4.81 15

Old/new effect Left superior parietal l. SPL 7 –32 –64 52 5.56 176

Left inferior parietal l. 40 –56 –32 40 5.05 19

Right inferior parietal l. 40 36 –40 40 5.26 53

Right fusiform g. 37 40 –48 –16 5.37 10

Left superior temporal g. 22 –60 –48 16 3.99 10

Left cerebellum CH –20 –56 –36 6.32 36

Left cerebellum CH –44 –60 –48 4.68 39

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Repetition Priming EffectRepetition priming refers to an implicit memory phenomenonin which repeatedly presented items are processed more effi-ciently, most often accompanied by weaker brain responses toold as opposed to new items. Figure 2A and Table 2 show brainregions exhibiting a decrease of activation to previously seenstimuli as opposed to new ones. As expected, we found activa-tions in bilateral middle occipital gyri (BA 18/19). Moreover,there is an activation in left lingual gyrus.

Old/New EffectFigure 2B and Table 2 show five brain regions that exhibitmore neural activity for correctly identified old items (hits)than for correctly identified new items (correct rejections): (i)

a medial-superior frontal area including the superior frontalgyrus medially and laterally in the dorsal-lateral prefrontalcortex (DLPFC), the anterior cingulate and pre- as well assupplementary motor areas (BA 6, 32); (ii) an area in the rightsuperior frontal gyrus (anterior prefrontal cortex: APFC, BA10); (iii) bilateral, left lateralized areas in the parietal lobewithin BA 7 and 40; (iv) an area in the left insula cortex (BA13); (v) and, finally, bihemispheric activations in the cere-bellum.

Positive Recognition EffectTo explore in more detail brain areas engaged in successfulmemory retrieval, we examined the difference in brainresponses to correctly recognized old items (hits) and old

Table 2Continued)

Coordinates are listed in Talairach and Tournoux (1988) atlas space. BA is the Brodmann area nearest to the coordinate and should be considered approximate (g., gyrus).

Effect Anatomical region BA Coordinates t-value No. of voxels

x y z

Old/new effect Right cerebellum CH 20 –60 –36 4.18 22

Right cerebellum CH 48 –64 –40 4.08 12

Left insula 13 –36 –4 16 4.09 13

Left precentral g. PCG 6 –40 0 36 5.18 22

Left superior frontal g. SFG 6 0 16 56 6.03 94

Right cingulate g. ACG 32 –4 36 28 7.08 34

Right superior frontal g. SFG 10 32 60 16 5.53 17

Right inferior frontal g. 47 32 20 –16 4.15 13

Right middle frontal g. 32 12 12 44 3.86 11

Left cingulate g. 23 –4 –12 24 4.79 27

Positive recognition effect Right angular g. AG 39 40 –60 32 3.73 11

Vermis, cerebellum Ve 0 –60 –20 4.82 42

Left pons Po –16 –48 –24 5.63 52

Right middle frontal g. MFG 6 16 –12 56 4.86 13

Left cerebellum –20 –72 –28 4.18 15

Negative recognition effect Left parahippocampal g. RC/Hi 35 –24 –20 –16 3.77 6

The subsequent memory masked inclusively by the positive recognition effect

Left cerebellum –12 –64 –28 3.76 23

Vermis, cerebellum Ve 0 –60 –20 3.21 23

Right angular g. AG 39 40 –60 32 3.85 14

Left pons Po –28 –32 –28 3.83 34

Left fusiform g. FG 20 –36 –60 –24 4.23 30

Left inferior temporal g. ITG 20 –56 –16 –24 3.81 29

Left parahippocampal g. RC 20 –36 –8 –24 2.51 12

Right parahippocampal g. RC 20 40 0 –36 3.56 12

The subsequent memory masked inclusively by the negative recognition effect

Left parahippocampal g. RC/Hi 28 –24 –16 –16 2.99 17

Left cerebellum –44 –48 –28 5.37 12

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items misclassified as new (misses). This contrast (Fig. 3A andTable 2) shows some overlap with activations seen in the old/new contrast regarding gross anatomy, but with the followingdifferences: (i) the right prefrontal activation is centered in themiddle frontal gyrus (BA 6) instead of area BA 10; (ii) contraryto the cerebellar old/new effect, the cerebellar recognitioneffect appears to be stronger and more pronounced at midlinestructures like the vermis, the intermediate cerebellar hemi-spheres and the tonsils and it is extended to the relay stationfor cerebellar afferents, the pons; and (iii) there is an activationof the right angular gyrus, which is not seen in the old/neweffect. Nevertheless, the overall location of activations inprefrontal, parietal and cerebellar areas is not entirely differentfrom the old/new effect.

Negative Recognition EffectNegative recognition effects were obtained by comparingbrain responses to misses with responses to hits. As describedin the introduction, repetition priming contaminates this effectto a lesser degree. Applying the same minimal cluster size asused for all other contrasts did not lead to a reliable negativerecognition effect. However, considering clusters consisting offive voxels or more reveals a left anterior MTL activation (Fig.3B, Table 2), which is exactly in line with our hypothesis basedon electrophysiological findings in humans (Smith et al., 1986)and animals (Brown and Aggleton, 2001). The activation iscentered in the anterior parahippocampal gyrus, but, as can beseen in Figure 3B, the activation might extend into the hippo-campus.

Figure 2. Repetition priming effect (A) and old/new effect (B). Regions activated more for new as opposed to old stimuli during recognition (A). Regions activated more for hits asopposed to correct rejections during recognition (B). Activation maps (P < 0.005, uncorrected; minimal cluster size 10 voxels) are shown overlaid onto a canonical brain renderedin three dimensions. Specific activations are additionally shown superimposed onto selected coronal slices of the mean high-resolution T1-weighted volume. Slices are numberedaccording to coordinates of Talairach and Tournoux (1988). ACG, anterior aspect of the cingulate gyrus; CH, cerebellar hemisphere; LG, lingual gyrus; MOG, middle occipital gyrus;PCG, precentral gyrus; SFG, superior frontal gyrus; SPL, superior parietal lobule.

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The Subsequent Memory Effect Inclusively Masked by the Positive Recognition EffectTo identify brain areas showing increased activity for bothsuccessful declarative memory formation and retrieval, wemasked the subsequent memory effect by the positive recog-nition effect. Figure 4A and Table 2 show regions that are acti-vated by these two contrasts. In line with our hypothesesregarding the critical role of the inferior and medial temporallobe we identified bilateral activations in the anterior half ofthe inferior temporal cortex. In both hemispheres, this areareaches the depth of the collateral sulcus, which is covered byperirhinal cortex (Amaral and Insausti, 1990). Additionally, weidentified a major activation in the cerebellar vermis and itsafferent relay station, the pons. Further activations are locatedin left fusiform gyrus, right angular gyrus and in bilateral cere-bellar hemispheres.

The Subsequent Memory Effect Inclusively Masked by the Negative Recognition EffectInclusively masking the subsequent memory effect by the nega-tive recognition effect allows the identification of brain areasassociated with activity increases during successful memoryformation and activity decreases during successful memoryretrieval. Figure 4B and Table 2 show brain areas exhibitingsuch a pattern of reactivity. Again, in line with our hypotheseswe revealed an anterior MTL activation including the lefthippocampus, but centered in the left parahippocampal gyrus.

Discussion

Memory FormationReplicating almost all earlier findings, we revealed subsequentmemory effects in a fusiform/parahippocampal and two left

Figure 3. Recognition effects. Regions activated more for hits as opposed to misses (positive recognition effect, A). Regions activated less for hits as opposed to misses (negativerecognition effect, B). For (A), the activation maps (P < 0.005 uncorrected; minimal cluster size 10 voxels) is shown overlaid onto a canonical brain rendered in three dimensions.Specific activations are additionally shown superimposed onto selected coronal slices of the mean high-resolution T1-weighted volume. For (B), all activations are shown on twoslices (P < 0.005 uncorrected; minimal cluster size five voxels). Slices are numbered according to coordinates of Talairach and Tournoux (1988). AG, angular gyrus; MFG, middlefrontal gyrus; Po, pons; RC/Hi, rhinal cortex/hippocampus; VE, vermis.

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inferior frontal areas, one in the posterior and one in theanterior aspect of the inferior frontal gyrus (Brewer et al.,1998; Wagner et al., 1998; Kirchhoff et al., 2000; Davachi et al.,2001; Otten et al., 2001; Otten and Rugg, 2001a; Strange et al.,2002). The additional subsequent memory effects in the pari-etal lobe and the cerebellar hemisphere were previously lessoften reported (Davachi et al., 2001; Otten and Rugg, 2001a).However, the left lateralization of the subsequent memoryeffects found here is not exactly in line with other studies alsousing picture stimuli (Brewer et al., 1998; Kirchhoff et al.,2000). It might be explained by the additional use of verbalcodes for picture details (Kelley et al., 1998; Opitz et al., 2000).Regardless, our results confirm that prefrontal and medialtemporal areas are involved in declarative memory formation,

where prefrontal cortex may execute working memory opera-tions associated with maintenance, selection and organizationof incoming information (Wagner, 1999; Fletcher and Henson,2001) and the MTL may execute a rather specific operation ofdeclarative memory formation in the hippocampus and asubordinate support operation in the parahippocampal region.This support operation may make semantic representations ofeach study item available in the service of comprehension,semantic-associative processing, and memory formation(Nobre and McCarthy, 1995; Fernández et al., 2002).

The negative subsequent memory contrast, more activity forsubsequently forgotten than subsequently remembered items,revealed only two small clusters of voxels in the precuneus andthe cingulate gyrus. The location of these activations is roughly

Figure 4. Subsequent memory masked inclusively by recognition effects. Regions activated more during successful as opposed to unsuccessful memory formation and more forhits as opposed to misses (subsequent memory effect and positive recognition effect, A). Regions activated more during successful as opposed to unsuccessful memory formationand less for hits as opposed to misses (subsequent memory effect and negative recognition effect, B). For (A), the activation maps (P < 0.017 uncorrected; minimal cluster size10 voxels) is shown overlaid onto a canonical brain rendered in three dimensions. Specific activations are additionally shown superimposed onto selected coronal slices of the meanhigh-resolution T1-weighted volume. For (B), all activations are shown on two slices (P < 0.017 uncorrected; minimal cluster size five voxels). Slices are numbered according tocoordinates of Talairach and Tournoux (1988). AG, angular gyrus; FG, fusiform gyrus; ITG, inferior temporal gyrus; RC, rhinal cortex; Hi, hippocampus; Po, pons; Ve, vermis.

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congruent with activations described in the initial reports ofthis effect (Otten and Rugg, 2001b; Wagner and Davachi,2001). These positive correlates of forgetting have been inter-preted as related to task-appropriate and task-inappropriateallocation of neurocognitive resources away from the processleading to effective memory formation (Otten and Rugg,2001b; Wagner and Davachi, 2001).

RecognitionThe old/new contrast revealed major activations in the parietallobe, in frontal midline structures (anterior cingulate and thesuperior frontal gyrus), the left insula, the right anterior aspectof the superior frontal gyrus and in both cerebellar hemi-spheres with a left hemispheric dominance. As intended, thesefindings replicate earlier ER-fMRI findings that suggest distrib-uted cerebral and cerebellar brain regions participating inrecognition memory (Henson et al., 1999; Konishi et al., 2000;McDermott et al., 2000; Cabeza et al., 2001; Donaldson et al.,2001a,b). Among these regions, the midline structures acti-vated (anterior cingulate and the superior frontal gyrus) mightcontrol subject responses by evaluating stimulus representa-tions restored in the parietal lobe (Buckner et al., 1996;Fletcher et al., 1996). Especially with the large number ofstimuli used here, a high degree of interference or responsecompetition makes an effective control of response selectionand inhibition necessary (Carter et al., 1998; Braver et al.,2001; Potts and Tucker, 2001; Stern et al., 2001; Levy andAnderson, 2002). Together with the left prefrontal subsequentmemory effect described above, the right anterior prefrontalactivation is fully in accord with the hemispheric encoding/retrieval asymmetry (HERA) model of a prefrontal encodingand retrieval asymmetry as proposed initially by Tulving et al.

(1994). The right anterior prefrontal activation might correlatewith postretrieval monitoring processes and not with theactual process of memory retrieval (Rugg et al., 1996; Schacteret al., 1997; Buckner et al., 1998). The old/new effects incerebellar hemispheres indicate that the cerebellum plays arole in memory retrieval (Bäckman et al., 1997; Cabeza et al.,1997; Andreasen et al., 1999). The implication of this findingwill be discussed below, interpreted in the context of the areasinvolved in both memory formation and retrieval.

The newly introduced positive recognition contrast (i.e.more activity for hits than misses) revealed activations in thefrontal and parietal lobe that are close to activations revealedby the old/new contrast, but without direct overlap. The cere-bellar activation is compared to the old/new effect morecentered at midline structures (i.e. vermis, intermediate cere-bellar hemispheres and tonsils) and extended to pontine areaswhere input from prefrontal, parietal and temporal cortices isrelayed to the cerebellum (Schmahmann, 1996). The failure tofind exact overlap between the positive recognition- and theold/new effect must, like all null results, be treated withcaution. This is especially so, given that the power to detect arecognition effect was lower than the power to detect an old/new effect, a consequence of fewer old misses than newcorrect rejections. Nevertheless, our findings seem to supportthe view that frontal, parietal and cerebellar regions areinvolved in the successful recovery of declarative memoriesduring a recognition memory task.

The small negative recognition effect may indicate that lessactivity in the anterior MTL is related to recognition success.This finding is in line with our hypothesis and electrophysio-

logical studies (Smith et al., 1986; Riches et al., 1991; Millerand Desimone, 1994; Brown and Aggleton, 2001). It is unlikelythat this effect is solely based on repetition priming, becauseboth classes of items have been encountered once before.However, since our study design does not provide a behavioralmeasure of repetition priming, we are unable to test stochasticindependence between primed and recognized items. Though,the location of priming effects in occipital areas only (Fig. 2B)makes a repetition priming account for the negative recog-nition effect in the anterior MTL highly unlikely. Nevertheless,there seem to be alternative interpretations for the negativerecognition effect: old items misclassified as new could be re-encoded during the test phase leading to an encoding relatedactivity increase (Buckner et al., 2001), or the subjects’ new-decision could be accompanied by an activity increase relatedto novelty detection (Tulving and Kroll, 1995; Tulving et al.,1996). The first alternative interpretation is not mutually exclu-sive with the recognition account (see below) and the latterinterpretation seems to be less plausible, because a reversedold/new contrast with more statistical power (more items) didnot show any activation in the anterior MTL (data not shown).

Given our study design, we cannot dissociate betweensubprocesses within recognition – whether an activation isrelated to recollection or familiarity (Mandler, 1980). This issuecould be further evaluated by a study design including forinstance a source memory judgment (Cansino et al., 2002).However, following Brown and Aggleton (2001) or Brown andBashir (2002), the negative recognition effect in the anteriorMTL might rather support a familiarity-based decision than anactual recollective experience (Henson et al., 2003). It mayreflect a process enabling recognition by more efficientprocessing of recognized stimuli with reduced neural activityduring an active memory search (Jiang et al., 2000), or by aneural activity increase in the presence of novel stimuli or oldstimuli incorrectly classified as new (Brown and Bashir, 2002).

Memory Formation and RecognitionThe largest activation clusters of the subsequent memory effectmasked by the positive recognition effect are located in theinferior and anterior medial temporal lobe as well as cerebellarand pontine regions. When masking the subsequent memoryeffect by the negative recognition effect, activations arelocated in the MTL

Thus, the anterior inferior temporal cortex including theanterior parahippocampal region seems to be conjointlyinvolved in both successful encoding and recognition. Thisfinding confirms suggestions based on across-study compari-sons of electrophysiological findings in epilepsy patients(Smith et al., 1986; Fernández et al., 1999, 2001, 2002). Such amodule has originally been described on the basis of electricalrecordings in non-human primates showing that this brainarea is sensitive to both object encoding and object recog-nition (Desimone et al., 1984; Riches et al., 1991; Miller andDesimone, 1994). During recognition, the neural representa-tion of each test stimulus, i.e. a unique pattern of activationthat is evoked by a visually perceived item during recognition,may be matched with stored representations previouslyformed locally during encoding. Moreover, the inferior andmedial temporal cortex is ideally located for this efficientpattern matching, because it is the final route of the ventralvisual pathway, providing integrated visual and semantic infor-mation (Ungerleider and Mishkin, 1985; Haxby et al., 1991;

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Nobre and McCarthy, 1995; Büchel et al., 1998; Lerner et al.,2001).

Our findings suggest an important role of the cerebellum andits afferent relay station, the pons, in declarative memory.Functional imaging studies provide mounting evidence that thecerebellum coordinates diverse aspects of cognitive processes(for a review, see Desmond and Fiez, 1998). Up to now,however, it is unclear whether the cerebellum providesdomain-general computations supporting diverse cognitiveoperations or different operations with specific roles in partic-ular cognitive domains. Several proposals have been made fora general operation, including a central timing processor(Keele and Ivry, 1990) for sequential parsing of temporallycomplex material (Llinas, 1974; De Zeeuw et al., 1998). Thach(1998) proposed that cerebellar processing entailsstimulus–response linkage by grouping single-responseelements into larger task adequate combinations. The cere-bellum also seems to be involved in processes contributingspecifically to learning and memory. It is not only criticallyinvolved in basic delay conditioning, where it is the locus ofmemory formation, consolidation, and storage (Thompson andKim, 1996; Attwell et al., 2002), it is also involved in spatiallearning and memory (Pellegrino and Altman, 1979; Lalondeand Botez, 1990; Goodlett et al., 1992). Humans with acquiredcerebellar lesions have, however, only minor deficits in declar-ative memory (Schmahmann, 1998). In imaging studies ofdeclarative memory, cerebellar activations were ratherobtained during retrieval than encoding tasks (Desmond andFiez, 1998), suggesting that a cortical-cerebellar network self-initiates and monitors conscious retrieval (Bäckman et al.,1997; Andreasen et al., 1999) or that the cerebellum generatescandidate responses during a search and selection process(Cabeza et al., 1997; Desmond et al., 1998). Our data show thatthe cerebellum participates in both memory formation andretrieval. However, the fact that cerebellar lesions cause onlyminor deficits in declarative memory suggests that thecerebellum is not directly involved in storage and retrievaloperations. It might rather support mnemonic operations byproviding a temporal structure for a coherent episode.

In conclusion, by replicating ER-fMRI studies investigatingeither memory formation or recognition we have providedwithin-study confirmation for brain areas involved in twofundamental mnemonic operations: either the formation or theretrieval of declarative memories. Based on this empirical foun-dation, we have described for the first time brain regionssupporting successful memory retrieval by both activityincreases (frontal, parietal, cerebellar areas) and decreases(anterior MTL). Finally, we have initially identified withinsubjects and within one experiment inferior- and medial-temporal as well as cerebellar areas supporting both memoryformation and retrieval. Such integrated modules may re-usestored representations formed locally during encoding for effi-cient matching operations during recognition.

AcknowledgementsWe thank Doug Davidson, Karl Magnus Petersson, Indira Tendolkarand Miranda van Turennout for instructive comments on the manu-script and Karsten Specht for technical advice in data acquisition andanalysis. G.F. is supported by BONFOR, the intramural researchsupport program and the German Research Council (DFG Fe479/4-1;SFB-TR 3/A4).

Address correspondence to Dr Guillén Fernández, F.C. DondersCenter (181), PO Box 9101, 6500 HB Nijmegen, The Netherlands.Email: guillen.fernandez@fcdonders.kun.nl.

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