Associations Evoked During Memory EncodingRecruit the Context-Network

Jan Peters,1,2,3* Irene Daum,1,2 Elke Gizewski,4 Michael Forsting,4 and Boris Suchan1,2

ABSTRACT: An extensive cortical network consisting of structures inthe medial temporal lobe (hippocampus and parahippocampal cortex),lateral parietal cortex, retrosplenial cortex, and medial prefrontal cortexhas recently attracted attention in cognitive neuroscience research, link-ing the network to both episodic memory and spatial processing. It hasbeen suggested that its function may be best characterized as supportingthe processing of contextual associations (context network). In thisstudy, we explored whether the role of this network in contextual proc-essing extends to associations that are evoked in a spontaneous manner.In a novel memory encoding task, participants indicated whether theyencoded pictures (objects and novel faces) based on an evoked associa-tion or based on a perceptual feature. Memory encoding with subjectiveassociations enhanced memory formation relative to feature-basedencoding, and this effect was more pronounced for rapidly evoked asso-ciations. Functional magnetic resonance imaging during encodingyielded significant activations in all regions of the context network, i.e.,medial prefrontal cortex, lateral parietal cortex, retrosplenial cortex,and posterior medial temporal lobe for the associative vs. feature-basedcomparisons. The low number of misses did not permit the analysis of asubsequent memory contrast. Our data suggest that the context net-work, which includes the posterior hippocampus and parahippocampalcortex, might support the linkage of external stimuli to long-term mem-ory representations. VVC 2008 Wiley-Liss, Inc.

KEY WORDS: associative memory; hippocampus; recollection Grantsponsor: International Graduate School of Neuroscience, Ruhr-University of Bochum

INTRODUCTION

The parahippocampal cortex (PHC) in the medial temporal lobe(MTL) is known to play an important role both in spatial processing(Epstein and Kanwisher, 1998) and episodic memory (Eichenbaumet al., 2007). In a recent attempt to reconsolidate this involvement in

seemingly unrelated cognitive domains, it wassuggested that the PHC, along with regions in theretrosplenial cortex (RSC), medial prefrontal cortex(mPFC), and lateral parietal cortex (LPC) is part of anetwork that mediates the processing of contextualassociations (Bar et al., 2007a,b).

Evidence for a role of this network in associativeprocessing comes from studies investigating the per-ception of high- and low-contextual stimuli (Bar andAminoff, 2003). High-contextual stimuli are stimulithat have many contextual associations, one examplebeing famous faces (Bar et al., 2007a), whereas low-contextual stimuli generally generate fewer associations(Bar and Aminoff, 2003). The comparison of brainactivity during the perception of high vs. low-contex-tual stimuli yielded activity in the posterior PHC,RSC, and mPFC, an effect observed in several studies(Bar and Aminoff, 2003; Bar et al., 2007b). Based onthese observations, the PHC, mPFC, and RSC arethought to form the so-called context network (Baret al., 2007b).

Associative processing during memory encoding is apowerful mnemonic technique and is generallybelieved to involve binding processes supported by thehippocampal formation (Davachi, 2006; Eichenbaumet al., 2007; Mayes et al., 2007), the highest conver-gence zone in the MTL (Lavenex and Amaral, 2000).Yet, a recent meta-analysis also yielded a relativelyconsistent involvement of the PHC in associativememory encoding and retrieval (Eichenbaum et al.,2007). Encoding that leads to subsequent recollectiveas opposed to familiarity-based recognition involvesboth hippocampal and PHC processing (Eichenbaumet al., 2007). For example, activity in these regionsduring encoding often predicts subsequent (source)recollection in functional magnetic resonance imaging(fMRI) neuroimaging studies (Davachi et al., 2003;Ranganath et al., 2004; Uncapher and Rugg, 2005)and successful encoding of associative informationsuch as face–name associations (Chua et al., 2007;Sperling et al., 2003), word pairs (Henke et al., 1999;Addis and McAndrews, 2006), or multiple contextualfeatures of a study episode (Uncapher et al., 2006) isaccompanied by hippocampal activation. Similareffects are seen during memory retrieval, where hippo-campal (Eldridge et al., 2000; Daselaar et al., 2006)and PHC activation (Eldridge et al., 2000) oftenaccompany recollection, an effect that has been shown

Jan Peters and Boris Suchan contributed equally to this work.

1Department of Neuropsychology, Institute of Cognitive Neuroscience,Ruhr-University of Bochum, Germany; 2 International Graduate Schoolof Neuroscience, Ruhr-University of Bochum, Germany; 3Neuroimage-Nord, Department of Systems Neuroscience, University Medical CenterHamburg-Eppendorf, Germany; 4Department of Diagnostic and Inter-ventional Radiology and Neuroradiology, University Hospital Essen,Germany

Grant sponsor: International Graduate School of Neuroscience, Ruhr-Uni-versity of Bochum*Correspondence to: Jan Peters, NeuroimageNord, Department of Sys-tems Neuroscience, University Medical Center Hamburg-Eppendorf,Martinistrabe 52, 20246 Hamburg, Germany.E-mail: jpeters@uke.uni-hamburg.deAccepted for publication 14 July 2008DOI 10.1002/hipo.20490Published online 5 September 2008 in Wiley InterScience (www.interscience.wiley.com).

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to be stable up to 6 weeks following study (Suchan et al.,2008). Regions of the parietal cortex (e.g., LPC and RSC) arealso involved in associative remembering, yet their precise func-tional role remains to be clarified (Wagner et al., 2005). Takentogether, these findings suggest common neural substrates forassociative memory processing and the activation of contextualassociations during perception.

There is considerably overlap between the context networkand brain regions commonly activated during fixation or restperiods in fMRI studies (Bar et al., 2007b), the ‘‘default net-work’’ of the brain (Raichle et al., 2001). MTL, RSC, andmPFC regions have been associated with remembering(Vincent et al., 2006; Addis et al., 2007) and future thinking(Addis et al., 2007; Buckner and Carroll, 2007). During restingstates, significant coherence of LPC and RSC activity withspontaneous signal fluctuations in the hippocampus wasobserved (Vincent et al., 2006). This resting state hippocampalcoherence network shows a remarkable overlap with regionsinvolved in successful recollection, including mPFC, LPC, andRSC/precuneus (Vincent et al., 2006). Recent evidence alsosuggested an involvement of this network in mind-wanderingduring periods of low demands on information processing(Mason et al., 2007). Taken together, these observations areconsistent with the idea that a comparable hippocampal-parietalcontext network (Bar et al., 2007b) is involved in episodicmemory, the processing of contextual associations and possiblybrain activity during resting states. These observations mightrepresent the continuous generation of predictions regardingthe immediate future based on associative links between currentstimuli and memory representations (Bar, 2007).

Associations evoked by a certain stimulus are most certainlysubjective. For example, a movie fan may have a considerablenumber of associations with the picture of a famous actress,whereas this image may evoke completely different associationsin a subject for whom the person is unfamiliar. In the lattercase, the image might even not evoke any associations at all.Thus, whether or not a certain stimulus evokes an associationdiffers between subjects. The context network has been shownto support the processing of associations inherent to the stimu-lus material (i.e., high vs. low-contextual stimuli, Bar and Ami-noff, 2003). The aim of this study was to assess whether simi-lar effects emerge when subjects are asked to introspectivelyreport whether a given stimulus evokes an association, therebyconsidering individual differences in the evocation ofassociations.

This issue was explored in a novel episodic memory encod-ing task in which subjects indicated their memory encodingstrategy for each memory item. Subjects were instructed topress one button if a given stimulus elicited an associationthat would help them remember it (association trial) andanother button if they felt that encoding was mainly based ona distinct perceptual feature of the stimulus (feature trial).During this encoding task, functional MRI was performed.Previous studies of the context network did not include behav-ioral measures of associative processing (e.g., Bar and Aminoff,2003). The present task allowed the assessment of a putative

behavioral correlate of the processing of contextual associationsduring memory encoding, namely subsequent recognitionaccuracy.

A relatively unconstrained encoding task has the disadvant-age that the exact types of associations that were evoked inour subjects (i.e., spatial, episodic or semantic associations)remain unknown. However, previous studies have shown thatvery different types of associations (i.e., spatial and nonspatialassociations) recruit the context network (Aminoff et al.,2007), and it has thus been argued that this network medi-ates associative processing regardless of the exact type of asso-ciation in question. The associations investigated in thisstudy were thus subjective in the sense that subjects intro-spectively reported the evocation of an association, but asso-ciations were not necessarily subjective in the sense that theyalways referred to, for example, subject-specific episodicmemory content.

We predicted superior memory performance for picturesencoded with an associative compared with a feature-basedstrategy. Associative encoding yields increased depth-of-process-ing compared with feature-based encoding, a process known toenhance memory formation (Craik, 2002). For the fMRI data,we expected regions of the context network to be more activewhen subjects adopted an associative compared with a feature-based encoding strategy.

The investigation of subjective associations in the context ofa memory encoding task addresses a further important issue.Item-based encoding and associative encoding are frequentlycontrasted using experimental conditions which differ in termsof stimulation (Achim and Lepage, 2005) or in terms of taskinstructions (Henke et al., 1999), whereas the current task wasbased on conditions which differed solely in terms of the sub-jective evaluation of subjects in terms of evoked associationswhich allows the further characterization of the neuronalmechanisms which underlie associative memory encodingstrategies.

MATERIALS AND METHODS

Subjects

Twenty subjects participated in the study. Data from threesubjects were excluded because of an insufficient number ofevents for fMRI analysis (<8) in one or more of the experi-mental conditions (three subjects) or poor performance in thepostscan recognition test (>2 SDs below the group average,two subjects). Thus, data from 15 participants (age mean 528.47, standard deviation (SD) 5 5.22, eight male) enteredfMRI analysis. Recognition data were unavailable for one ofthese subjects because of technical problems during data acqui-sition. All participants were righthanded as assessed by theEdinburgh Handedness Inventory (Oldfield, 1971). Subjectswere recruited by advertisement, gave informed written con-sent, and were reimbursed for participation. The study

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procedure was approved by the Ethics committee of the Medi-cal Faculty of the Ruhr-University of Bochum.

EXPERIMENTAL PROCEDURES

Participants were instructed to memorize a series of objectsand faces for a later memory test. They were told to indicatetheir encoding strategy for each individual memory item by abutton press. Subjects were asked to press one button if thestimulus elicited an association which would help them remem-ber (association trial) and another button if they felt that a dis-tinct perceptual feature of the stimulus would enhance memory(feature trial). Several examples for each response type wereprovided to ensure proper understanding of the instructions(e.g., Press association if a face reminds you of an old teacheror friend or of a popular actor; Press feature if you notice a dis-tinct texture on the surface of this object/a distinct facial fea-ture). The sequence of events is depicted in Figure 1.

A set of 170 gray-scale pictures of common objects (Peterset al., 2007) and 170 gray-scale pictures of nonfamous faces(Kress and Daum, 2003; Minnebusch et al., 2007) were used

as stimuli. During encoding, 100 items of each category wererandomly selected to serve as study items, and face and objecttrials were randomly intermixed. The encoding task was imple-mented using the Experimental Run-Time System (BeriSoft,Germany).

Following study, participants completed a recognition mem-ory test outside the MRI scanner. They were shown all itemsfrom the study face together with 140 novel distracters (70faces and 70 objects) in random order. The recognition taskwas implemented using the Presentation � Software Package(Neurobehavioral Systems). After presentation of each item, a6-point scale was displayed which prompted subjects to ratetheir memory confidence with respect to the item’s status (old/new). The scale ranged from ‘‘certain old,’’ ‘‘probably old,’’‘‘maybe old’’ to ‘‘maybe new,’’ ‘‘probably new,’’ and ‘‘certainnew,’’ and participants were instructed to use the full range ofthe scale.

fMRI Data Acquisition

Images sensitive to blood-oxygenation level dependent(BOLD) signal were acquired on a 1.5 T Siemens SymphonyMRI scanner with an echo time (TE) of 30 ms and a repetition

FIGURE 1. Overview of the sequence of events during study(left) and test (right). Participants indicated whether they encodedan item based on an evoked association (‘‘Assoziation’’) or basedon a distinct stimulus feature (‘‘Merkmal’’). During recognition,

participants made recognition judgements on a six point scaleranging from ‘‘certain the stimulus is old’’ (‘‘sicher alt’’) to ‘‘certainthe stimulus is new’’ (‘‘sicher neu’’). ISI, interstimulus-interval.

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time of 1.75 s. Such short TEs have been shown to minimizesignal drop out from the anterior temporal lobes (Ojemannet al., 1997). For each subject, 512 whole-brain volumes con-sisting of 25 slices of 3.4 3 3.4 3 3.0 mm3 voxels with 0.3mm gap and a field-of-view of 220 mm were obtained, and thefirst five volumes were discarded to allow for the stabilizationof the BOLD signal. Volumes covered all but the most superiorparts of the cerebrum. Additionally, a T1-weighted structuralscan was acquired for each subject (128 slices, 240 mm field-of-view, Repetition time 5 9.2 ls, TE 5 4.46 ls, 1 3 1 31.5 mm3 voxel size).

fMRI Analysis

FMRI data preprocessing and analysis was performed usingSPM5 (www.fil.ion.ucl.ac.uk/spm/, Wellcome Department ofCognitive Neurology, University College London, UK). Imageswere slice-time corrected, realigned, and normalized to the tem-plate of the Montreal Neurological Institute provided bySPM5. Subsequently, images were smoothed with a Gaussiankernel of 8 mm full-width half-maximum. Coordinates of sig-nificant activated foci were transformed into Talairach space(Talairach and Tournoux, 1988) using the algorithm suggestedby Brett (http://www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html). Anatomical labeling was performed using the TalairachDaemon database (Lancaster et al., 2000) and further con-firmed by visual exploration of activations overlayed onto themean structural image of all participants.

Data were modeled for each subject by convolving the ca-nonical hemodynamic response function with the event train ofstimulus onsets. Contrasts of interest were computed for eachindividual subject, and the resulting single-subject contrastimages were then taken to a second-level random-effects analy-sis. Data analysis was carried out using a 2 3 2 factorial designwith the factors Stimulus type (objects/faces) and Encodingstrategy (associative/feature-based encoding). We first computedthe main effects of Stimulus type (objects > faces and faces >objects, collapsing across encoding strategies) and of Encodingstrategy (associative > feature-based and feature-based > asso-ciative, collapsing across stimulus type). The interaction termwas assessed using an F-contrast. All SPMs were thresholded atP < 0.05 (k >10 voxels), corrected for multiple comparisonsusing false-discovery rate correction (Genovese et al., 2002).For all activations of interest, subject-specific percent signalchanges (averaged across all voxels in a given cluster) wereextracted using MarsBar (Brett et al., 2002). An additional fol-low-up analysis was performed including trial-by-trial RT as acovariate of no interest at the first level.

We also analyzed activity in a priori defined region-of-inter-ests (ROI). Spherical ROIs (8 mm radius) were centered atactivation peaks in mPFC, RSC, PHC, and LPC from previousstudies of resting state activity (Fox et al., 2005) and contextualprocessing (Bar and Aminoff, 2003). The statistical thresholdfor this analysis was again set to P < 0.05, small-volume cor-rected using FDR correction.

RESULTS

Behavioral Data

Behavioral data from the study phase (RTs and numbers oftrials per condition) are listed in Table 1. Data from the post-scan recognition test are listed in Table 2. Association-basedencoding was higher for objects than for faces (see Table 1 andFig. 2, t(14) 5 26.909, P < 0.001), whereas faces were morefrequently encoded with a focus on a distinctive feature (t(14)5 6.723, P < 0.001). This is illustrated in a frequency histo-gram of associativity (i.e., the proportion of associationresponses for each individual face and object stimulus, see Fig.2). A bipolar distribution of associativity within one stimuluscategory may indicate that a subset of items were consistentlyencoded using associations, whereas another subset was consis-tently encoded using features. However, this effect was notobserved. For both faces and objects, a wide range of associativ-ity emerged, indicating considerable variability in the adoptedencoding strategy, both between subjects and between individ-ual stimuli. This is in line with the idea that the associationsevoked were highly subject specific.

RTs during study were faster for association trials (see Table1, main effect Encoding strategy: F(1,14) 5 30.674, P <0.001), and this effect was more pronounced for objects thanfaces (Encoding 3 Stimulus interaction F(1,52) 5 5.701, P 50.032).

For recognition accuracy, we analyzed the mean subsequentrecognition confidence (see Fig. 3A). Objects were rememberedsignificantly better than faces (main effect Stimulus type:F(1,52) 5 118.70, P < 0.001) and associative encoding yieldedbetter recognition accuracy than feature-based encoding (maineffect Encoding strategy: F(1,52) 5 7.621, P 5 0.008). Theinteraction did not reach significance (P 5 0.167).

We hypothesized that associations which are rapidly evokedmay be particularly strong, and their effect on memory forma-tion may be particularly pronounced. Consistent with this hy-pothesis, the trial-by-trial correlation between RTs duringencoding and subsequent recognition confidence was signifi-cantly more negative for association trials than for feature trials

TABLE 1.

Behavioral Data From the Study Phase

Trial type

Mean (range)

no. of trials

for fMRI analysis

Mean (SD)

reaction time

during encoding

Faces

Association 24.67 (8–57) 2112 (490)

Feature 73.60 (42–92) 2404 (291)

Objects

Association 64.60 (38–90) 1908 (338)

Feature 34.13 (10–62) 2475 (294)

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(mean [SD]: association trials 5 20.20 [0.11], feature trials 50.001 [0.13], t(1,13) 5 23.946, P 5 0.001). This effect stillemerged when we directly compared fast and slow associationtrials that were matched on face/object ratio, i.e., recognitionwas better for fast trials (mean recognition rating [SD]: fastassociation trials 5 5.23 [0.36], slow association trials 5 5.08[0.42], t(1,13) 5 1.905, P 5 0.040), indicating that rapidlyevoked associations were more potent in enhancing memoryformation. A similar correlation emerged in a subject-by-subjectanalysis (Fig. 3B). Subjects that responded faster during encod-ing showed better subsequent memory for association trials(P 5 0.015) but not for feature trials (P 5 0.377).

RTs were generally faster during association trials, and thisraises the question as to whether subjects initially attempted toretrieve an association, and only then, failing to do so, focusedon feature-based encoding. This could mean that responsesduring feature-based encoding may not necessarily reflect theprocessing of feature-level information, but may merely reflectthe failure to retrieve an association. To address this issue, wecompared RTs for slow (i.e., below median) association trialsand fast (i.e., above median) feature trials. These sets of trialswere again matched on face/object ratio (see earlier). RTs weresignificantly faster during fast-feature trials than during slowassociation trials (2480 ls vs. 2117, P < 0.001). Fast responsesduring feature-based encoding were thus faster than slowresponses during associative encoding, which argue against theidea that processing of feature-level information alwaysoccurred later than the evocation of associations. Mean subse-quent recognition accuracy was still significantly better for slowassociation trials compared to fast feature trials (5.09 vs. 4.85,

P 5 0.002), indicating that superior subsequent recognitionduring association trials was not simply due to faster RTs.

fMRI Data

Whole-brain analysis

FMRI data were analyzed using a 2 (Stimulus type: objects/faces) 3 2 (Encoding strategy: associative/feature-based) facto-

TABLE 2.

Behavioral Data From the Recognition Phase

Trial type

Response Categories

Certain old 6 Probably old 5 Maybe old 4 Maybe new 3 Probably new 2 Certain new 1

Faces

Association trials 0.33 (0.17) 0.26 (0.12) 0.19 (0.09) 0.12 (0.10) 0.08 (0.07) 0.02 (0.04)

Mean (SD) proportion of trials 7 (2–12) 6 (2–15) 5 (1–13) 4 (0–21) 2 (0–7) 1 (0–4)

Mean (range) no. of trials

Feature trials

Proportion of trials 0.18 (0.11) 0.25 (0.09) 0.24 (0.08) 0.17 (0.09) 0.14 (0.10) 0.02 (0.02)

No. of trials 14 (2–32) 19 (2–30) 18 (7–34) 12 (3–24) 10 (2–28) 2 (0–5)

New

Proportion of trials 0.04 (0.04) 0.14 (0.07) 0.18 (0.05) 0.27 (0.13) 0.29 (0.12) 0.07 (0.06)

Objects

Association 0.85 (0.12) 0.09 (0.08) 0.02 (0.03) 0.01 (0.02) 0.02 (0.03) 0.01 (0.01)

Proportion of trials 54 (32–79) 5 (0–15) 1 (0–6) 1 (0–3) 1 (0–10) 1 (0–2)

No. of trials

Feature

Proportion of trials 0.79 (0.16) 0.11 (0.11) 0.04 (0.05) 0.01 (0.01) 0.03 (0.03) 0.02 (0.02)

No. of trials 28 (9–52) 4 (0–15) 2 (0–7) 1 (0–2) 1 (0–5) 1 (0–2)

New

Proportion of trials 0.02 (0.03) 0.01 (0.01) 0.02 (0.03) 0.07 (0.07) 0.21 (0.13) 0.66 (0.19)

FIGURE 2. Frequency histogram of associativity (i.e., the pro-portion of ‘‘association’’ responses) for faces and objects. Plottedare absolute numbers of stimuli falling into 0.1 size bins, sepa-rately for faces and objects. Objects had a higher associativity thanfaces, but in both stimulus classes, ranges of associativity wereobserved.

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rial design. Regions previously implicated in the processing ofcontextual associations and associative memory encoding (seeTable 3 and Fig. 4) were more active during associative com-pared with feature-based encoding, including right RSC/precu-neus (x 5 26, y 5 258, z 5 30, k 5 479 voxels, z value 54.53, BA29/30/31), bilateral mPFC (x 5 24, y 5 38, z 5218, k 5 306 voxels, z value 5 4.41, BA10/11/25), left LPC(x 5 248, y 5 276, z 5 36, k 5 114 voxels, z value 54.55, BA39) and left posterior MTL (x 5 222, y 5 246, z5 4, k 5 49 voxels, z value 5 4.24, hippocampus and PHC).

In the light of the RT differences between feature and associ-ation trials, we additionally analyzed the fMRI data includingtrial-by-trial RTs as a regressor at the first level of analysis. Itshould be noted that RT differences between conditions arenot necessarily a confound, but like the BOLD signal, mayalso represent neural activity differences between conditions.Nonetheless, this additional analysis revealed a very similar pat-tern of activity in the context network during association trials(Fig. 5), suggesting that differences between association trialsand feature trials cannot be solely attributed to RT differences.

Individual subjects showed a similar activation of LPC andanterior as well as posterior midline structures (mPFC andRCS/precuneus) during encoding with evoked associations. Fig-ure 6 shows the contrast associative > feature-based memoryencoding in four representative participants. For visualizationpurposes, these SPMs were thresholded at P < 0.025 (uncor-rected) with an extent threshold of 50 voxels.

The reverse contrast (feature-based > associative encoding)yielded activations in the right superior (x 5 28, y 5 268,z 5 52, k 5 81 voxels, z value 5 5.16, BA7) and inferiorparietal lobule (x 5 40, y 5 242, z 5 50, k 5 48 voxels,z value 5 4.93, BA40) as well as regions in the occipital lobeand precuneus (see Table 3).

A priori region-of-interest analysis

To investigate whether the activations observed during associ-ation trials indeed overlap with regions previously identified inthe processing of contextual associations and resting states, weperformed an addition ROI analysis (see Materials and Meth-ods section). We examined activity in the contrast association> feature trials in spherical ROIs (8 mm radius) centered atpeaks of activation in four regions (PHC, RSC, mPFC, LPC)derived from previous studies (Bar and Aminoff, 2003; Foxet al., 2005, see Table 4). Associative encoding yielded signifi-cant activations in all of these ROIs (P < 0.05, corrected, seeTable 4).

DISCUSSION

In this study, we investigated the effects of subjective associa-tions evoked during memory encoding on activation of thecontext-network, a network recently implicated in the process-ing of contextual associations. Behavioral data indicate thatevoked associations enhanced memory formation relative toencoding based on a stimulus feature, an effect that was partic-ularly pronounced for rapidly evoked associations. FMRI datashow that, relative to feature-based memory encoding, subjec-tive associations resulted in robust activity in a hippocampal-parietal system (context network) including posterior MTL,LPC, RSC, and mPFC. In a first step, we will discuss the sig-nificance of these findings with regard to the cortical networksmediating the processing of (contextual) associations. We willthen focus on the relevance of our data to current theories ofmemory encoding.

FIGURE 3. Behavioral data from the postscan recognitiontest. A: Mean 6 standard error of mean (SEM) subsequent recog-nition confidence. This measure was greater for objects than faces(P < 0.001) and for association (black) compared with feature tri-als (gray, P 5 0.008). The interaction did not reach significance

(P > 0.1). B: RTs during encoding plotted against the mean subse-quent recognition confidence rating for associative (black) and fea-ture-based encoding (gray). Fast-responding subjects showed bettersubsequent recognition memory for association trials (P 5 0.015)but not for feature trials (P 5 0.377).

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In line with our hypotheses, the brain regions which wereactivated during memory encoding based on spontaneous asso-ciations show a remarkable overlap with regions previouslyreported to form a context network that includes posteriorPHC and hippocampus (Bar et al., 2007b). For example, theperception of high- vs. low-contextual objects resulted in PHCand RSC activity (Bar and Aminoff, 2003), and a similar effecthas recently been reported for the processing of famous com-

pared to nonfamous faces (Bar et al., 2007a). Similarly, process-ing of concrete compared with abstract words also activates thePHC (Fiebach and Friederici, 2004) and RSC/precuneus(Binder et al., 2005), indicating that these effects may general-ize to verbal material with many (concrete words) as opposedto fewer associations (abstract words). A number of theoriesendorse the idea that concrete words have more semantic(Schwanenflugel and Shoben, 1983) or image-based associa-

TABLE 3.

Whole-Brain Results of the Factorial Analysis (FDR-Corrected for Multiple Comparisons, P < 0.05, 10 Voxels Extent Threshold)

Region ~BA No. of voxels

MNI coordinates

z valueX Y Z

Associative > Feature-based encoding

R parahippocampal gyrus 37 51 12 210 212 4.67

– 6 24 210 3.93

L lateral parietal cortex 39 114 248 276 36 4.55

R precuneus/posterior cingulate/retrosplenial 31 479 26 258 30 4.53

30 2 250 20 4.22

29 26 248 12 3.96

L/R medial frontal gyrus 11 306 24 38 218 4.41

25/11 22 30 220 3.97

10/11 8 42 214 3.96

L parahippocampal gyrus/hippocampus 30 49 222 246 4 4.24

222 238 8 3.91

R middle temporal gyrus 21 32 56 0 214 4.19

62 26 214 3.85

L precuneus 19 21 232 282 44 4.13

L middle temporal gyrus 21 71 258 0 224 4.08

21 254 8 226 3.76

21 254 28 224 3.63

L anterior cingulate 32 10 26 22 34 3.99

R mediodorsal thalamus 2 13 6 214 12 3.97

R putamen 2 10 30 212 4 3.96

L insula 13 10 242 6 24 3.77

R posterior cingulate 30 12 18 268 2 3.76

R putamen 2 10 18 12 6 3.73

L parahippocampal gyrus 34 16 216 22 218 3.69

L anterior cingulate 25 14 22 16 26 3.67

L anterior cingulate/medial frontal gyrus 42 51 28 46 10 3.63

10 28 52 16 3.58

L middle temporal gyrus 22 13 262 236 4 3.55

Feature-based > associative encoding

R superior parietal lobule 7 81 28 268 52 5.16

7 18 264 50 4.67

R inferior parietal lobule 40 48 40 252 50 4.93

R cuneus/middle occipital gyrus 19 62 30 288 26 4.69

19 32 284 18 4.27

L precuneus 7 13 214 266 48 4.41

L middle temporal gyrus 37 14 248 264 0 4.39

L middle occipital gyrus 19 15 226 288 14 4.27

Material 3 Encoding Interaction

No significant clusters were observed at the chosen threshold

BA, Brodmann Area.

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tions (Paivio, 1991). Our findings extend these previous obser-vations of contextual processing in this network by showingthat these effects are not limited to contextual associations thatare inherent to the stimulus material but they also apply toassociations that participants subjectively report. For example,famous faces activate contextual associations in the PHC (Baret al., 2007a), and our data show a very similar effect (Fig.4D) for nonfamous faces that elicited a subjective associationin our subjects. Our data are thus in line with the recent pro-posal by Bar et al. (2007b) that the same regions that consti-tute the ‘‘default-network’’ of the human brain appear to alsosupport the processing of (contextual) associations. Importantly,the present task involved the evocation of highly subjectiveassociations, but the recruited brain regions were consistent

across subjects (see Fig. 6), implying a common neural basisfor a highly individual cognitive operation.

It should be pointed out that the observation of activity inregions of the ‘‘default network’’ (Raichle et al., 2001) duringassociative processing in this study and in others (Bar et al.,2007a,b) does not permit the conclusion that associative proc-essing reflect what occurs during resting periods (Poldrack,2006), although some recent data suggest that this may be thecase (Mason et al., 2007). The cognitive operations that giverise to ‘‘default network’’ activity during resting periods remainto be clarified. However, our data do support the view that thevery same regions that form the ‘‘default network’’ appear to besensitive to demands in associative processing. This idea is alsosupported by recent evidence implicating this network in the

FIGURE 4. Regions more active when subjects adopted anassociative compared with a feature-based encoding strategy, pro-jected onto the standard MNI brain. The SPM is thresholded at P< 0.05 (k > 10 voxels, false-discovery rate corrected for multiplecomparison across whole-brain volume, top row) and signal-change timecourses averaged across all activated voxels in a givencluster are plotted below. Associative encoding was accompanied

by signal increases in posterior (A) and anterior (B) midlineregions, LPC (C) and posterior parahippocampal cortex/hippo-campus (D). LPC, lateral parietal cortex; RSC, retrosplenial cortex;mPFC, medial prefrontal cortex; HC, hippocampus; PHC, para-hippocampal cortex. [Color figure can be viewed in the onlineissue, which is available at www.interscience.wiley.com.]

FIGURE 5. Activity in the contrast associative > feature-basedmemory encoding with trial-by-trial RTs included as a covariate ofno interest at the single-subject level (threshold P < 0.05, k > 10voxels, false-discovery rate corrected for multiple comparisons

across whole-brain volume). LPC, lateral parietal cortex; RSC, ret-rosplenial cortex; mPFC, medial prefrontal cortex; HC, hippocam-pus; PHC, parahippocampal cortex. [Color figure can be viewed inthe online issue, which is available at www.interscience.wiley.com.]

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elaboration of future and past events (Addis et al., 2007). Ourdata also show that the network recruitment during associativeprocessing is statistically robust, present at the level of individ-ual subjects, and it is also observed when subjective associationsare taken into account.

Behaviorally, we observed superior subsequent recognitionfor pictures which are encoded with a spontaneous association.This is in line with the idea that relational processing duringencoding may enhance memory formation (Eichenbaum,2004). Relational processing during encoding is commonlyassociated with greater hippocampal and PHC activation(Henke et al., 1999; Achim and Lepage, 2005; Eichenbaumet al., 2007), an effect that was also observed in this study. Thepresent findings demonstrate that this effect is robust in thecontext of a task which places minimal constraints on encodingoperations. The beneficial effect of associative processing onmemory formation was enhanced on trials with shorter RTs, aneffect that was observed both trial-by-trial and subject-by-sub-ject. One possibility is that subjective associations which areevoked rapidly and with ease may have been associated withmore extensive and robust long-term memory networks. Ourdata are thus compatible with the idea that associating a stimu-lus with such a more extensive and robust long-term memory

representation may also result in a more robust memory traceof the stimulus itself.

Interestingly, the LPC activity which emerged during associa-tion trials was not observed in previous studies investigatingcontextual processing (Bar and Aminoff, 2003). However, thisregion has repeatedly been shown to be involved in memory re-trieval (Wheeler and Buckner, 2003; Wagner et al., 2005; Vin-cent et al., 2006) and, like RSC and mPFC, shows a positivecorrelation with the hippocampus during resting periods (Vin-cent et al., 2006). In contrast to previous studies (Bar andAminoff, 2003), the present task involved an introspective eval-uation of encoding strategy requiring the direction of attentionto the internal representation of the activated association.Directing attention to internal representations is one hypothesisof the functional role of parietal cortex in memory processes(Wagner et al., 2005) and our data are compatible with thissuggestion.

Of note, the present observation of increased mPFC activa-tion during subjective associative encoding is not in oppositionto current views of the functional role of the rostral PFC. Themedial aspect of rostral PFC that has been implicated in stimu-lus-dependent attentional processes (Burgess et al., 2007) is sit-uated more rostrally than the activation observed in the presenttask, which appears to overlap more with those portions ofmPFC that are also recruited during mentalizing (Gilbert et al.,2006).

Our data have some implications for the ongoing debateconcerning stimulus-dependent and stimulus-independent cog-nitive operations in default-network regions. Some studies havesuggested that default-network structures may support stimu-lus-independent thought (McGuire et al., 1996; Christoffet al., 2004; Mason et al., 2007). Our data show that stimulus-triggered associative processing relies on similar brain regions,indicating that need to process associations between representa-tions may be the critical factor regarding an involvement of‘‘default-network’’ or ‘‘context-network’’ regions (Bar et al.,2007b).

Interestingly, there was some degree of overlap with regardto the brain regions involved in association and feature trials

TABLE 4.

Results of the Region-of-Interest Analysis

8mm spherical ROIs [center coordinates]

Peak activation coordinates (MNI) in ROI

from the contrast association trials > feature trials

Z value PSVCx y z

‘‘Context network’’ (Bar and Aminoff, 2003, Exp. 1)

Parahippocampal cortex [224, 242, 27] 220 238 8 3.34 0.031

‘‘Task-negative network’’ (Fox et al., 2005)

Medial prefrontal cortex [21, 49, 22] 26 56 22 3.06 0.033

Lateral parietal cortex [245, 271, 35] 246 276 38 5.67 <0.001

Retrosplenial cortex [3, 253, 6] 22 252 8 3.44 0.017

SVC, small volume correction, ROI, region-of-interest, MNI, montreal neurological institute.

FIGURE 6. Individual-subject SPMs from four representativesubjects. Results for the contrast associative encoding > feature-based encoding are projected onto a glass brain (transversal view,anterior on top, posterior at the bottom, left on the left). SPMswere thresholded at P < 0.025 (k > 50 voxels, uncorrected) for vis-ualization purposes. LPC, lateral parietal cortex; RSC, retrosplenialcortex; mPFC, medial prefrontal cortex.

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(see Table 3). Left LPC was activated in association trials andright LPC in feature trials. Also, different subregions of theprecuneus were activated in both conditions. In cannot beruled out that these effects are due to some degree of associa-tive processing also occurring in feature trials. On the otherhand, the detailed ROI analysis clearly shows that associationtrials but not feature trials showed activation in regions of thecontext network, raising the possibility that the right LPC andbilateral precuneus regions activated in the feature > associa-tion contrast may be functionally distinct from the context-network.

One limitation of this study is the fact that subsequentmemory contrasts could not be evaluated. A comparison of suc-cessfully and unsuccessfully encoded stimuli between associationand feature trials was not possible because of an insufficientnumber of misses at recognition. Therefore, this study high-lights neural mechanisms that support adopting an associativeor a feature-based memory encoding strategy, but further workis required to show whether the neural mechanisms that predictencoding success differ depending on this strategy. Nonetheless,the behavioral data show a differential effect of spontaneousassociations and feature-based encoding on subsequent recogni-tion memory. Future studies would benefit from a modifieddesign that may allow a comparison between subsequent mem-ory effects depending on adopting an associative or feature-based encoding strategy. Increasing the study-test delay, increas-ing the number of study items or using a modified set of stim-uli may all increase the number of forgotten items, whichshould allow the analysis of subsequent memory contrasts.Future studies may also benefit from scanning both the encod-ing and the recognition session, in order to investigate recapitu-lation effects specifically for items encoded using associations.

A further point that warrants discussion are the RT data.Association trials showed faster RTs than feature trials and itcould therefore be argued that subjects first attempted toretrieve an association, and only when failing to do so focusedon detecting a distinct stimulus feature. However, the findingthat slow association trials showed significantly slower RTs thanfast feature-trials argues against this possibility.

We did not show that those regions activated during the evo-cation of spontaneous associations overlap with default-networkactivity in these same subjects (using a conjunction analysis, forexample), as default-activity was not assessed. However, numer-ous studies have shown that the brain networks activated dur-ing rest are highly consistent both between studies and betweensubjects (e.g., Raichle et al., 2001; Vincent et al., 2006). Ouradditional ROI analysis furthermore shows significant activationduring association trials compared with feature trials in regionsof both a ‘‘task-negative network’’ (Fox et al., 2005) and thecontext-network (Bar and Aminoff, 2003).

Taken together, our findings confirm and extend previousobservations of activity related to the processing of contextualassociations in RSC, posterior MTL, and mPFC (Bar and Ami-noff, 2003; Bar et al., 2007a,b) by showing a comparable effectwhen subjective associations are considered. The behavioraldata further suggest that evoked associations fascilitate memory

formation, with the contextual processing network presumablysupporting the linkage of external stimuli with associated long-term memory representations.

Acknowledgments

The authors thank Peter Bayley, Christian Bellebaum, Ber-tram Opitz and Patrizia Thoma for helpful comments on anearlier version of this manuscript.

REFERENCES

Achim AM, Lepage M. 2005. Neural correlates of memory for itemsand for associations: An event-related functional magnetic reso-nance imaging study. J Cogn Neurosci 17:652–667.

Addis DR, McAndrews MP. 2006. Prefrontal and hippocampal contri-butions to the generation and binding of semantic associations dur-ing successful encoding. Neuroimage 33:1194–1206.

Addis DR, Wong AT, Schacter DL. 2007. Remembering the pastand imagining the future: Common and distinct neural substratesduring event construction and elaboration. Neuropsychologia 45:1363–1377.

Aminoff E, Gronau N, Bar M. 2007. The parahippocampal cortexmediates spatial and nonspatial associations. Cereb Cortex 17:1655–1665.

Bar M. 2007. The proactive brain: Using analogies and associations togenerate predictions. Trends Cogn Sci 11:280–289.

Bar M, Aminoff E. 2003. Cortical analysis of visual context. Neuron38:347–358.

Bar M, Aminoff E, Ishai A. 2007a. Famous faces activate contextualassociations in the parahippocampal cortex. Cereb Cortex 18:1233–1238.

Bar M, Aminoff E, Mason M, Fenske M. 2007b. The units ofthought. Hippocampus 17:420–428.

Binder JR, Westbury CF, McKiernan KA, Possing ET, Medler DA.2005. Distinct brain systems for processing concrete and abstractconcepts. J Cogn Neurosci 17:905–917.

Brett M, Anton JL, Valabregue R, Poline JB. 2002. Region of interestanalysis using an spm toolbox, Eighth International Conference onFunctional Mapping of the Human Brain. Neuroimage 16.

Buckner RL, Carroll DC. 2007. Self-projection and the brain. TrendsCogn Sci 11:49–57.

Burgess PW, Dumontheil I, Gilbert SJ. 2007. The gateway hypothesisof rostral prefrontal cortex (area 10) function. Trends Cogn Sci11:290–298.

Christoff K, Ream JM, Gabrieli JD. 2004. Neural basis of spontane-ous thought processes. Cortex 40:623–630.

Chua EF, Schacter DL, Rand-Giovannetti E, Sperling RA. 2007. Evi-dence for a specific role of the anterior hippocampal region in suc-cessful associative encoding. Hippocampus 17:1071–1080.

Craik FI. 2002. Levels of processing: Past, present, and future?Memory 10:305–318.

Daselaar SM, Fleck MS, Cabeza R. 2006. Triple dissociation in themedial temporal lobes: Recollection, familiarity, and novelty.J Neurophysiol 96:1902–1911.

Davachi L. 2006. Item, context and relational episodic encoding inhumans. Curr Opin Neurobiol 16:693–700.

Davachi L, Mitchell JP, Wagner AD. 2003. Multiple routes to mem-ory: Distinct medial temporal lobe processes build item and sourcememories. Proc Natl Acad Sci USA 100:2157–2162.

Eichenbaum H. 2004. Hippocampus: Cognitive processes and neuralrepresentations that underlie declarative memory. Neuron 44:109–120.

150 PETERS ET AL.

Hippocampus

Eichenbaum H, Yonelinas AR, Ranganath C. 2007. The medial tem-poral lobe and recognition memory. Annu Rev Neurosci 30:123–152.

Eldridge LL, Knowlton BJ, Furmanski CS, Bookheimer SY, Engel SA.2000. Remembering episodes: A selective role for the hippocampusduring retrieval. Nat Neurosci 3:1149–1152.

Epstein R, Kanwisher N. 1998. A cortical representation of the localvisual environment. Nature 392:598–601.

Fiebach CJ, Friederici AD. 2004. Processing concrete words: Fmri evi-dence against a specific right-hemisphere involvement. Neuropsy-chologia 42:62–70.

Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC,Raichle ME. 2005. The human brain is intrinsically organized intodynamic, anticorrelated networks. Proc Natl Acad Sci USA 102:9672–9678.

Genovese CR, Lazar NA, Nichols T. 2002. Thresholding of statisticalmaps in functional neuroimaging using the false discovery rate.Neuroimage 15:870–878.

Gilbert SJ, Spengler S, Simons JS, Steele JD, Lawrie SM, Frith CD,Burgess PW. 2006. Functional specialization within rostral prefron-tal cortex (area 10): A meta-analysis. J Cogn Neurosci 18:932–948.

Henke K, Weber B, Kneifel S, Wieser HG, Buck A. 1999. Humanhippocampus associates information in memory. Proc Natl AcadSci USA 96:5884–5889.

Kress T, Daum I. 2003. Event-related potentials reflect impaired facerecognition in patients with congenital prosopagnosia. NeurosciLett 352:133–136.

Lancaster JL, Woldorff MG, Parsons LM, Liotti M, Freitas CS, RaineyL, Kochunov PV, Nickerson D, Mikiten SA, Fox PT. 2000. Auto-mated talairach atlas labels for functional brain mapping. HumBrain Mapp 10:120–131.

Lavenex P, Amaral DG. 2000. Hippocampal-neocortical interaction: Ahierarchy of associativity. Hippocampus 10:420–430.

Mason MF, Norton MI, Van Horn JD, Wegner DM, Grafton ST,Macrae CN. 2007. Wandering minds: The default network andstimulus-independent thought. Science 315:393–395.

Mayes A, Montaldi D, Migo E. 2007. Associative memory and themedial temporal lobes. Trends Cogn Sci 11:126–135.

McGuire PK, Paulesu E, Frackowiak RS, Frith CD. 1996. Brain activ-ity during stimulus independent thought. Neuroreport 7:2095–2099.

Minnebusch DA, Suchan B, Ramon M, Daum I. 2007. Event-relatedpotentials reflect heterogeneity of developmental prosopagnosia.Eur J Neurosci 25:2234–2247.

Ojemann JG, Akbudak E, Snyder AZ, McKinstry RC, Raichle ME,Conturo TE. 1997. Anatomic localization and quantitative analysis

of gradient refocused echo-planar fmri susceptibility artifacts.Neuroimage 6:156–167.

Oldfield RC. 1971. The assessment and analysis of handedness: Theedinburgh inventory. Neuropsychologia 9:97–113.

Paivio A. 1991. Dual coding theory: Retrospect and current status.Can J Psychol 43:255–287.

Peters J, Suchan B, Koster O, Daum I. 2007. Domain-specific retrievalof source information in the medial temporal lobe. Eur J Neurosci26:1333–1343.

Poldrack RA. 2006. Can cognitive processes be inferred from neuroi-maging data? Trends Cogn Sci 10:59–63.

Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA,Shulman GL. 2001. A default mode of brain function. Proc NatlAcad Sci USA 98:676–682.

Ranganath C, Yonelinas AP, Cohen MX, Dy CJ, Tom SM, D’EspositoM. 2004. Dissociable correlates of recollection and familiaritywithin the medial temporal lobes. Neuropsychologia 42:2–13.

Schwanenflugel P, Shoben E. 1983. Differential context effects inthe comprehension of abstract and concrete verbal materials. J ExpPsychol Learn Mem Cogn 9:82–102.

Sperling R, Chua E, Cocchiarella A, Rand-Giovannetti E, Poldrack R,Schacter DL, Albert M. 2003. Putting names to faces: Successfulencoding of associative memories activates the anterior hippocam-pal formation. Neuroimage 20:1400–1410.

Suchan B, Gayk AE, Schmid G, Koster O, Daum I. 2008. Hippocam-pal involvement in recollection but not familiarity across time: Aprospective study. Hippocampus 18:92–98.

Talairach J, Tournoux P. 1988. Co-Planar Stereotaxic Atlas of theHuman Brain. Stuttgart: Thieme.

Uncapher MR, Rugg MD. 2005. Encoding and the durability ofepisodic memory: A functional magnetic resonance imaging study.J Neurosci 25:7260–7267.

Uncapher MR, Otten LJ, Rugg MD. 2006. Episodic encoding is morethan the sum of its parts: An fmri investigation of multifeaturalcontextual encoding. Neuron 52:547–556.

Vincent JL, Snyder AZ, Fox MD, Shannon BJ, Andrews JR, RaichleME, Buckner RL. 2006. Coherent spontaneous activity identifies ahippocampal-parietal memory network. J Neurophysiol 96:3517–3531.

Wagner AD, Shannon BJ, Kahn I, Buckner RL. 2005. Parietal lobecontributions to episodic memory retrieval. Trends Cogn Sci 9:445–453.

Wheeler ME, Buckner RL. 2003. Functional dissociation among com-ponents of remembering: Control, perceived oldness, and content.J Neurosci 23:3869–3880.

ASSOCIATIONS EVOKED DURING MEMORY ENCODING 151

Hippocampus