BRIEF REPORT

Context-dependent memory effects in two immersive virtual realityenvironments: On Mars and underwater

Yeon Soon Shin1& Rolando Masís-Obando1

& Neggin Keshavarzian1& Riya Dáve1 & Kenneth A. Norman1,2

Accepted: 13 October 2020# The Author(s) 2020

AbstractThe context-dependent memory effect, in which memory for an item is better when the retrieval context matches the originallearning context, has proved to be difficult to reproduce in a laboratory setting. In an effort to identify a set of features thatgenerate a robust context-dependent memory effect, we developed a paradigm in virtual reality using two semantically distinctvirtual contexts: underwater and Mars environments, each with a separate body of knowledge (schema) associated with it. Weshow that items are better recalled when retrieved in the same context as the study context; we also show that the size of the effectis larger for items deemed context-relevant at encoding, suggesting that context-dependent memory effects may depend on itemsbeing integrated into an active schema.

Keywords Context-dependent memory effect

Introduction

Returning to an alma mater for a reunion can bring back mem-ories from the past. Walking by campus may make it easier torecall past events that took place in the dorms, classrooms, anddining halls, evenwhen thosememories are not easily retrievableelsewhere. This flood of memories when returning to an oldenvironment is known as the environmental reinstatement effect(Smith, 1979). Research in episodic memory explains this effectwith the encoding-specificity hypothesis, which posits that in-creasing levels of overlap with the encoding context during re-trieval aids memory performance (Tulving & Thomson, 1973).However, the beneficial effect of context reinstatement in recallhas not been consistently supported in the memory literature (fora review, see Smith & Vela, 2001). Contexts have been manip-ulated in various ways such as background colors (Isarida &Isarida, 2007; Weiss & Margolius, 1954) and physical rooms(Eich, 1985; Fernandez & Glenberg, 1985), but these manipula-tions do not always lead to a context-reinstatement effect

(Fernandez & Glenberg, 1985; Isarida & Isarida, 2007; Wältiet al., 2019). The discrepancy between the strong anecdotal psy-chological experience and weak experimental evidence indicatesthat extant experimental paradigms are missing key features thatare responsible for evoking context-dependent memory in reallife. What, then, are these missing features?

One of the seminal studies that showed strong context-dependency used rich, real-world environments to manipulatethe congruency between encoding and retrieval contexts(Godden & Baddeley, 1975). They found that scuba diversrecalled learned words better when the retrieval context (under-water or land) matched the encoding context. It is worth noting,however, that subjectswere put into vastly different situations thatlikely activated different bodies of knowledge associated witheach environment (e.g., how to swim and breathe underwater).Similarly, Smith and Manzano (2010) showed a robust contextreinstatement effect in a study where contexts were manipulatedby video scenes showing situations that subjects were likely to bealready familiar with. Relatedly, a change in themental represen-tation of the current situation can reduce access to episodes thathappened before the change (for a review, see DuBrow et al.,2017). These studies suggest that, in order to demonstrate a robustcontext effect, subjects should mentally represent distinct situa-tions and activate distinct sets of knowledge while encoding andretrieving the items. Standard laboratory experiments that merelychange the physical environment or the color on a screen mayhave failed to elicit the effect because they failed tomake subjectsbelieve that they were in different situations.

Yeon Soon Shin and Rolando Masís-Obando are co-first authors

* Kenneth A. Normanknorman@princeton.edu

1 Princeton Neuroscience Institute, Princeton, NJ, USA2 Department of Psychology, Princeton University, Princeton, NJ,

USA

https://doi.org/10.3758/s13423-020-01835-3

/ Published online: 17 November 2020

Psychonomic Bulletin & Review (2021) 28:574–582

These ideas fit with prior work in cognitive psychology(Alba & Hasher, 1983; Bransford & Johnson, 1972) and cog-nitive neuroscience (Gilboa & Marlatte, 2017; Poppenk &Norman, 2012; Preston & Eichenbaum, 2013; Schlichting &Preston, 2015; Tse et al., 2007; van Kesteren et al., 2012;Whittington et al., 2019) showing that activation of relevantpre-existing knowledge (i.e., schemas) can facilitate newlearning by providing a “scaffold” onto which new informa-tion can be attached. Once information has been attached tothis contextual scaffold, reinstating the scaffold at test shouldfacilitate recall, and taking it away should hurt recall, therebyleading to a context change effect.

In the present study, we aimed to develop an experimentalparadigm that can produce a strong context reinstatement ef-fect in a laboratory setting. First, we used two virtual reality(VR) environments that we predicted would activate distinc-tive pre-existing sets of knowledge (i.e., schemas) in the sub-jects, underwater (UW) and Mars planet (MP) environments.In other words, these two environments differed not only per-ceptually, but also in their prior conceptual associations.Furthermore, to maximize the difference between the two con-texts while expanding on their existing knowledge, we alsohad subjects perform context-specific actions that were phys-ically distinctive: subjects performed downward motions inUW and upward motions inMPwhen interacting with objectsto initiate each session (i.e., context-initiation action se-quences) and to discover to-be-remembered items (i.e., item-finding actions; Fig. 1b). Second, in order for subjects to havethese bodies of knowledge readily available at the time ofstudy and test, as was the case for the divers in Godden andBaddeley (1975), we familiarized subjects with the virtualenvironments in a foraging task where they collected objectsdispersed throughout each environment. This was followed bya practice of the associated sequences of actions (context-ini-tiation action sequences and item-finding actions) before theywent into the main task (Fig. 1c, top row).

Another key desideratum is that, during encoding, thesedistinct bodies of knowledge should be activated whenperforming the experimental tasks. If subjects are aware of afuture memory test, they may use mnemonic strategies unre-lated to the present context and ignore other inputs from theenvironment. Thus, to ensure contextual relevance duringencoding and to conceal the purpose of the study, we used asurprise memory test. Furthermore, a cover task for encodingforced subjects to deliberately integrate the memory items intothe given context (Eich, 1985). Specifically, we asked subjectsto judge whether a shown itemwas useful in the context whereit was found. We hoped that these judgment tasks that wereunique to each environment, paired with the item-finding andcontext-initiation action sequences (also unique to each envi-ronment), would foster the activation of context-unique asso-ciations during encoding. Additionally, we hypothesized thatitems that were affirmatively judged to be useful in the

encoding environment would show a stronger context-change effect – the idea being that schema-consistent itemswould be more strongly integrated into the active schema atencoding (Bransford & Johnson, 1972; Spalding et al., 2015;van Kesteren et al., 2013, 2018, 2020) and thus suffer more ifthat schema were not active at retrieval. The context-initiationaction sequences were also performed at the beginning of theretrieval session, making the encoding and retrieval sessionsmore similar for the “same” condition and more distinctive forthe “different” condition.

Lastly, we also manipulated the interval between encodingand retrieval. When items were encountered very recently,they may be retrievable without relying on contextual cues,and this may weaken context dependency (Smith & Vela,2001). To test this, we used two levels of encoding-retrievalintervals, where a longer interval (the “delay” condition) wasexpected to produce a stronger reinstatement effect than ashorter interval (the “immediate” condition).

In summary, our approach was to combine as many factorsas we could in the service of ensuring that participants acti-vated distinct bodies of knowledge (i.e., schemas) when learn-ing word lists in the two contexts. The benefit of this com-bined approach is to maximize effect size (if our hypothesis iscorrect), with the complementary drawback that – if we obtainan effect – we are not in a position to say which of the factorsare necessary and sufficient for driving the effect.

Methods

Participants

Seventy-two adults (50 female; 22 male) recruited fromPrinceton University and the university community participat-ed in our study. All but two participants were right-handed(one left-handed, one ambidextrous). Informed consent wasobtained from all participants in accordance with PrincetonInstitutional Review Board, and subjects were each providedwith monetary compensation or course credit for participatingin the study. With the exception of eight participants who didnot complete the study due to technical issues with the VRdevices and/or Unity (e.g., VIVE wireless disconnected orscreen froze during encoding), a total of 64 subjects wereincluded in the analyses. We decided the sample size bybootstrapping from our pilot data and choosing a number ofsubjects who satisfied all necessary counterbalancingconstraints.

Task and procedure

We used a 2 (study-test context congruency: same vs. differ-ent) × 2 (study-test interval: immediate vs. delay) between-subjects design (Fig. 1a). The experimental procedure was

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divided into three parts: a training phase with sessions in bothUW and MP (Fig. 1c, top row), two encoding sessions in oneof the two environments (Fig. 1c, middle row), and a retrievalsession either in the original encoding environment (the“same” condition) or in the other environment (the “different”condition; Fig. 1c, bottom row). In the “immediate” condition,encoding and retrieval occurred on the same day, while for the“delay” condition, retrieval took place the day after encoding.

Training

The training session is depicted in Fig. 1c, top row. Aftersigning consent and screening forms, subjects were handed apaper with a fictionalized mission statement outlining the taskto be performed in VR. Subjects were told that they werepioneers developing alternative places for humans to inhabitin the future and instructed to judge whether they should keepthe items they discover based on the usefulness and pertinence

to thriving in the environment they were in. This was meant toobscure the purpose of the study and the surprise memory testlater.

After reading the mission statement, subjects were famil-iarized with the VR software by entering a practice environ-ment. In this environment, subjects learned how to navigateand interact with objects that they would encounter in themain task. Subjects learned how to navigate by teleportationand how to find and judge items for the cover task (e.g.,bending down, reaching upwards, etc.). Experimenters com-municated with subjects during training via an intercom sys-tem connected to the head-mounted display audio-device.

Subjects were then introduced to the MP and UW environ-ments. The order of the environments was counterbalancedacross subjects. In each environment, subjects first performeda foraging task where subjects explored and collected 20 float-ing spheres scattered across the environment. This wasfollowed by a context-initiation action sequence (Fig. 1b,

Fig. 1 Methods pipeline. (a) Study design. We used a 2 (study-testcontext congruency: same vs. different) × 2 (study-test interval:immediate vs. delay) between-subjects design. Subjects were split be-tween getting tested in either the same environment where learning oc-curred or in the other environment. Dotted arrows indicate the "different"condition while solid arrows indicate the "same" condition. Subjects wentinto the free-recall session either immediately or approximately 24 h afterlearning of the items occurred. (b) Environment-specific gameplay me-chanics and stimuli. The Underwater (UW) and Mars planet (MP) envi-ronments each contained context-specific gameplay mechanics (top andmiddle rows), with distinct visual and auditory stimuli (bottom row). (c)Task procedure. Our paradigm consisted of three main phases (delineatedby the three rows). Subjects first read the cover story and were familiar-ized with each of the environments (top row) through the following tasks:(1) a foraging task, (2) the context-specific initiation sequence, and (3)

item-finding actions. Each practice run was followed by the two distractortasks. In the second phase (middle row), each subject went through twoencoding sessions in one of the two environments. Before encoding,subjects performed the context-initiation sequence specific to the envi-ronment. They then found to-be-remembered items by performing theenvironment-unique item-finding action and judged whether the itemwas useful or not for survival in the present environment. They did thisfor 24 items in a given session before proceeding to two distractor tasks(right-most middle row). The encoding session was performed twice inthe same environment with two non-overlapping sets of word items.Either immediately following the encoding session or after a 1-day delay(bottom row), subjects again performed the context-initiation sequencespecific to the retrieval environment, at which point they were asked torecall all the words they had judged during study (i.e., 48 words)

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top row), which subjects were required to perform at the be-ginning of each session. For this, subjects in UW needed tobend down to reach a key and insert it into the key-hole of alarge treasure chest in the center of the environment, whilesubjects in MP needed to reach upwards to grab a floppy-disk and insert it to the side of a podium near the center ofthe crater. After the context-initiation action sequence, sub-jects heard an audio instruction for the task they needed toperform in the session. The instruction guided subjects topractice item-finding actions and the judgment mechanics thatrequired reaching out and picking either a red or green cubewith their controller. The item-finding actions were alsounique to the environment. Subjects in UW found a to-be-remembered item by bending down and digging inside of achest, whereas MP subjects did so by reaching up to a floatingrock and scanning it while it was latched onto the scanner(Fig. 1b, middle row). After finding and judging four itemsin the environment, they were teleported out and asked toperform two types of distractor tasks. The first distractor taskwas a countdown task in which subjects were instructed tocount down from 100 to negative 300 by a randomly-generated single-digit number in an empty environment. Thesecond distractor task was a monster-smash task that requiredsubjects to hit as many monster heads off the ground as pos-sible. The countdown task and monster-smash task both lasted1 min and were always performed in succession via virtualtransportation from the countdown room to the monstersmashing platform. Subjects repeated these tasks when trainedin the second environment.

Encoding

After the training phase was completed, subjects weretransported to either MP or UW for the encoding sessions.There were two encoding sessions (Fig. 1c, middle row). Atthe beginning of the encoding session, subjects first performedthe context-initiation task that was specific to the environ-ment, after which they listened to the recorded instruction.Subjects then performed a cover task where they made judg-ments about whether the items they discovered should be keptin the environment based on their perceived usefulness forsurviving in that environment. There were 24 items in eachsession, and they were told that they should only keep roughlyhalf of the items. Immediately after the word disappeared, thejudgment cubes (green for useful, red for harmful) appeared infront of the subjects’ virtual visual field simultaneously andremained there for 6 s before disappearing. If no selection wasmade within the 6-s trial window, the judgment trial wascounted as missed.

After successfully discovering all 24 items in chests (inUW) or rocks (in MP), subjects performed distractor tasks(i.e., countdown and monster-smash tasks). Once bothdistractors were completed, subjects were virtually

transported back to the same encoding environment as the firstencoding session and initiated the second encoding session.The second encoding session was identical to the first exceptfor the to-be-remembered items (24 new words). After thesecond encoding session, subjects again performed the twodistractor tasks.

Retrieval

Following the encoding task, subjects were introduced to theretrieval session (Fig. 1c, bottom row). Subjects in the "imme-diate" condition continued to the retrieval task while subjectsin the "delay" condition were told to return the next day foradditional missions. Before the retrieval session, subjects inthe "delay" condition were re-familiarized with the retrievalenvironment and performed the two distractor tasks. Subjectsin the "immediate" condition were transported to the retrievalenvironment immediately after the distractor tasks that follow-ed the second encoding session.

The “same” condition subjects returned to the same envi-ronment in which encoding took place for retrieval (i.e., UW-UW or MP-MP), while the “different” condition subjectsfaced the surprise memory test in the environment that dif-fered from the encoding session (i.e., UW-MP or MP-UW).

Once subjects were virtually transported to the retrievalenvironment, subjects performed the corresponding context-initiation task after which they learned for the first time thatthere was a surprise memory test. Subjects were instructed toverbally recall all the words they had discovered from bothencoding sessions (i.e., 48 words), regardless of whetherwords were judged to be useful or not. The recall period lasted2 min.

Materials

Environments

Two distinctive VR environments were custom-built and ex-plored by subjects with a wireless head-mounted virtual real-ity display (HMD): underwater (UW) and Mars planet (MP).To maximize the difference between the two contexts, eachhad a different layout and a set of thematically correspondingspecific player actions, objects, and sounds (Fig. 1b). Soundeffects were obtained online or made in-house with AbletonLive software and instruction audios were created using a text-to-speech service (fromtexttospeech.com).

The UW environment resembled the ocean floor. The land-scape was tinted bluewith coral surrounding the play area, and3-Dmodels of shipwrecks, submarines, boats, and chests werescattered around the environment. The words were locatedinside small chests; to interact with the chests, subjects hadto bend down, lift the lid, and place their controller inside thechest to “dig” into the chest to reveal the word to judge. In

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addition to the bubble and underwater sounds, all instructionsin the UW context were given by a male voice.

The MP environment resembled science fiction depictionsof the planet Mars. The landscape was tinted orange withmountains far in the distance of a large crater, which servedas the play area. Models of spaceships, satellites, and floatingrocks were interspersed around the crater with additionalspaceships hovering in the sky. In MP, to interact with thefloating rocks, subjects had to lift the rocks with their control-ler and press the trigger button to “scan” them and reveal theword. To maximize immersion, coarse wind sounds played inthe background, and static sound effects were triggered withevery word discovery (e.g., “scanning rock”). All instructionsin the MP context were given by a female voice.

Words

Forty-eight concrete nounwords were used as encoding items.The same set of 48words was presented for bothMP and UW.To ensure that roughly half of the items were judged useful inboth environments, we normed the words using MechanicalTurk, where the context was given by a screenshot of thecorresponding VR environment and 180 words were judgedfor usefulness in the given environment. The mean probabilityof the chosen set of words being judged useful was 0.56 (SD =0.28) in MP and 0.48 (SD = 0.25) in UW.

Apparatus

All tasks were presented on a wireless HTC Vive Pro head-mounted display (1,440 × 1,600 resolution per eye, with a 90-Hz refresh rate, and built-in headphones and integrated micro-phone), which was wirelessly connected (with a HTCWireless Adapter) to a custom-built computer running 64-bitWindows 10 on an Intel Core i7-7800X CPU @ 3.50GHzwith 32GB RAM and an Nvidia GeForce RTX 2080 graphicscard.

All tasks were created and coded in Unity3D 2017.4.3, agame-development platform, with Virtual Reality Toolkit(VRTK; vrtk.com), a virtual-reality programming tool-kit forUnity3D. 3D models, textures, environments and other assetswere downloaded from the Unity Asset Store (assetstore.unity.com) and Turbosquid (turbosquid.com) and thenmodified or custom-built using Blender (blender.org).

Statistical analyses

We performed statistical analyses using a generalized linearmixed-effects model in R with the “lme4” package (Bateset al., 2015), treating subjects and word stimuli as randomeffects, and treating context congruency, encoding-retrievalinterval, and usefulness as fixed effects. For confidence

intervals, we performed bootstrapping, sampling different setsof subjects with replacement 5,000 times.

Results

Encoding

Overall, subjects spent 7.44 mins per encoding session (SD =0.92min, 95% bootstrap CI [7.23, 7.68]). Subjects spent moretime in MP (M = 7.89 min, SD = 0.99 min, 95% bootstrap CI[7.57, 8.25]) than in UW (M = 7.00 min, SD = 0.58 min, 95%bootstrap CI [6.80, 7.20]; t(49.83) = 4.380, p < 0.001),reflecting longer distance (in arbitrary units) traveled in MP(M = 6.13, SD = 0.49, 95% bootstrap CI [5.97, 6.31]) than inUW (M = 5.00, SD = 0.55, 95% bootstrap CI [4.81, 5.19]);t(61.29) = 8.714, p < 0.001).

For the decision task, 52% (SD = 9%, 95%CI [50%, 55%])of the items were judged as useful for the environment andhence kept. Mixed-effects logistic regression analysis showedthat there was no significant difference in the probability ofkeeping items between encoding environments (β = 0.098, SE= 0.107,Wald Z = 0.912, p = 0.362;M = 0.51, SD = 0.10, 95%bootstrap CI [0.48, 0.55]; UW M = 0.54, SD = 0.08, 95%bootstrap CI [0.51, 0.56]). Decision reaction times did notsignificantly differ between “Useful” (M = 793.25 ms, SD =271.27 ms, 95% bootstrap CI [728.18, 860.91]) and“Harmful” (M = 868.58 ms, SD = 267.64 ms, 95% bootstrapCI [805.36, 934.33]; t(125.98) = −1.582, p = 0.116) judg-ments, or between encoding environments (t(61.25) = 1.510,p = 0.136; MP M = 864.91 ms, SD = 223.25 ms, 95% boot-strap CI [787.01, 943.16]; UW M = 775.54 ms, SD = 249.55ms, 95% bootstrap CI [689.70, 864.36]).

Retrieval

Overall accuracy was 0.29 (SD = 0.12, 95% bootstrap CI[0.26, 0.32]). First, we tested the context reinstatement effect,the benefit in retrieving memory items in the same environ-ment as the encoding environment as opposed to a differentenvironment. Given that a mixed-effects logistic regressionmodel that controlled for a stimulus effect (i.e., word items)as a random effect showed a better fit (BIC = 3421.5) than amodel that did not (BIC = 3650.0), we used a model withsubjects and word items as random effects to predict whetheran item is recalled as a function of context congruency; themodel also included study-test interval and usefulness judg-ment as fixed effects. The mixed-effects model showed a sig-nificant benefit for the “same” condition (M = 0.32, SD = 0.11,95% bootstrap CI [0.28, 0.36]) compared to when recall wasin a different environment (M = 0.26, SD = 0.11, 95% boot-strap CI [0.22, 0.30]); β = 0.349, SE = 0.130, Wald Z = 2.690,p < 0.01; Fig. 2a), suggesting that retrieving items is easier

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when the retrieval environment matches the encodingenvironment.

To investigate additional factors that affect context rein-statement effect, we tested whether the effect depended onthe interval between encoding and retrieval. The interactionbetween context congruency and interval was not significant(β = 0.120, SE = 0.260, Wald Z = 0.462, p = 0.644) whentested using the mixed-effects logistic regression model; theeffect size (Cohen’s D) for the delay condition was 0.917, and

the effect size for the immediate condition was 0.599 (Fig.2b). There was a main effect of interval where delayed recallperformance was significantly worse than immediate recall (β= −0.790, SE = 0.130, Wald Z = −6.075, p < 0.001).

To further explore the mechanisms by which context rein-statement affects memory recall, we looked at the relationshipbetween the usefulness judgment and context congruency.The mixed-effects logistic regression model showed an inter-action between context congruency and usefulness judgment

(a)

(b) (c)

Fig. 2 Recall performance. (a) The context reinstatement effect. Subjectsrecalled significantly more words when the recall context was the same asthe encoding context (dark gray; N = 32) than when it was different (lightgray; N = 32). (b) Recall performance as a function of context congruencyand study-test interval. The interaction between context congruency andstudy-test interval was not significant. In the “delay” condition, there wasa significant benefit in recalling items in the same context (dark gray; N =16) compared to the different context (light gray; N = 16). This benefit

was not significant in the “immediate” condition (the “same” condition N= 16; the “different” condition N = 16). (c) Recall performance as afunction of context congruency and usefulness judgment. There was asignificant interaction between context congruency and usefulness judg-ment, where useful items showed a greater benefit from context congru-ency. Note: Dots indicate individual subjects. Error bars indicate 95%bootstrap confidence intervals. ∗∗ p < 0.01, ∗ p < 0.05, † p < 0.1, ˜ n.s.

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(β = 0.384, SE = 0.179, Wald Z = 2.137, p < 0.05), as well asmain effects of context congruency (β = 0.349, SE = 0.130,Wald Z = 2.690, p < 0.01) and usefulness judgment (β =0.362, SE = 0.100, Wald Z = 3.621, p < 0.001; Fig. 2c).Planned comparisons showed that the context reinstatementeffect was significant among the “useful” items (β = 0.521, SE= 0.180, Wald Z = 2.898, p < 0.01), but was not significantamong the “harmful” items (β = 0.177, SE = 0.193, Wald Z =0.918, p = 0.359). These results suggest that reinstating thecontext preferentially brings back memories for the contextu-ally relevant items, thereby boosting overall memoryperformance.

Discussion

In this study, we investigated the environmental context-dependent memory effect in virtual reality, with a designintended to activate distinct bodies of context-specific knowl-edge. Subjects studied items either underwater (UW) or onMars planet (MP), under a cover story in which they judgedusefulness of items for the given context, and took a surprisefree recall test in either the same or different context as thestudy context. We showed that the items were better recalledwhen retrieved in the same context as the study context.Importantly, these context-dependent memory effects wereonly obtained for items that were judged to be useful for sur-vival in the encoding environment.

Circling back to our central motivation, why has it been sodifficult to replicate context-dependent memory effects in thelaboratory? In the introduction, we hypothesized that the key toobtaining context-dependent memory effects was to integrateitems into different schemas (bodies of knowledge) in the twocontexts at encoding. The interaction we observed between“usefulness” and context-congruency is consistent with thisidea: in our study, the items marked useful at encoding (i.e.,items that could be meaningfully integrated into the activeschema) were the ones that suffered when the schema activeat encoding was not active at recall. Note that this interactioneffect cannot be solely explained by deeper encoding of usefulitems (e.g., survival-related items, Soderstrom & McCabe,2011) – depth of encoding can explain the main effect of use-fulness but not the benefit of reinstating context. Having saidthis, our study did not directly manipulate schema-integration,so we need to temper our conclusions about the role of schema-integration in driving these effects.

Relating this to the literature more broadly, a potential rea-son why the seminal Godden and Baddeley (1975) studyfound such robust effects could be that their subjects werewell-familiarized with the sequence of actions of underwaterdiving as well as those of being on land; consequently, theyhad “underwater” and “out of the water” schemas that theycould use to scaffold knowledge at encoding. Our findings

also resonate with prior work showing the importance of in-tegrating items with context (Eich, 1985; Murnane et al.,1999). Eich (1985) showed a larger reinstatement effect in freerecall when subjects integrated items into physical contexts(i.e., distinct rooms) by imagining them in the study environ-ment. Similarly, Murnane et al. (1999) found larger context-change effects on recognition sensitivity when items could beintegrated into a familiar situation (e.g., when words wereshown on a picture of a blackboard in a classroom) versuswhen they could not (e.g., when the context was defined bycombinations of word color, background color, and location).Our usefulness-judgment results extend this idea by showingthat simply having a meaningful context (i.e., one that acti-vates an existing schema) is not sufficient to yield context-dependent memory; rather, subjects have to actually succeedin integrating the item into the encoding context (i.e., the itemhas to be judged to be “useful” in that context) to get an effectof context congruency for that item at recall.

Our study used VR in order to provide both perceptuallyand semantically rich experiences. The immersive nature ofVR makes it a potentially useful tool for studying context-dependent memory (Dunsmoor et al., 2014; Reggente et al.,2018). However, the use of VR does not guarantee a context-dependent memory effect. For instance, a recent study thatalso used VR did not find the context-reinstatement effect(Wälti et al., 2019). In their study, Wälti and colleaguesasked subjects to remember a list of words presented on abackground image, following the study by Isarida andIsarida (2007) where contexts were manipulated using thebackground color for studied words. On each trial, a wordwas presented on a context image (i.e., a background color,a landscape picture, a virtual background, or backgroundflickering) for 3 s, and the context was pseudorandomly se-lected on each trial such that the same context did not appearfor more than three words in a row.

While we also used VR, our study significantly differsfrom the Wälti et al. (2019) study. Wälti and colleagues usedVR to present backgrounds and did not allow direct interac-tion with these backgrounds; by contrast, we used highly in-teractive virtual environments to encourage activation of dis-tinct schemas in the two environments. Moreover, our studyused a surprise memory test to prevent participants from usingother strategies that could potentially suppress processing ofcontext information. Lastly, the frequency of context switcheswas higher in the Wälti study – there were at least sevencontext shifts during encoding. This context manipulationmay have been ineffective because the rate of context switchwas too rapid to match the human prior for a context change.For instance, it is unlikely that the room where we read emailschanges as quickly as the switch of tabs on a browser or appson a phone. In other words, it may be that contexts shift athierarchically different timescales (Collins & Frank, 2013;Kurby & Zacks, 2008; Zacks et al., 2001). If the two

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alternating contexts form a higher-level context in which thereis an alternation between the two background images withcertain transition probabilities, then what is designated as the“change” or “different context” condition may not actuallyinvolve a context change (since subjects continue with samehigher-level mental context active in mind). Another implica-tion of the idea that changes in the internal context represen-tation drive memory effects (more so than changes in sensoryinput) is that asking participants to mentally reinstate theencoding context should reduce the size of the context-dependent memory effect as in Smith (1979); this is a prom-ising direction for future work.

Lastly, in addition to the factors outlined above, we manip-ulated study-test delay: There were two delay conditions, onein which subjects were tested immediately after encoding andanother after a 1-day delay. Our data show that the benefit ofcontext reinstatement for the 1-day delay was numerically (butnot significantly) larger than that of immediate recall.Increasing the delay might boost context-dependent memoryeffects by boosting the extent to which participants rely onhippocampally-mediated episodic memory (Chen et al.,2016) instead of activemaintenance of items in workingmem-ory (for a review, see Richmond & Zacks, 2017).Hippocampal codes are known to be highly context-dependent (Eichenbaum, 2004), so it follows that anythingthat increases reliance on the hippocampus should increasecontext-dependence. Additionally, studies have found thatschema-consistent information undergoes accelerated consol-idation into neocortex, mediated by interactions between hip-pocampus and medial prefrontal cortex (Gilboa & Marlatte,2017; Wang & Morris, 2010); an extra day of consolidationcould boost context-dependent memory effects by fosteringadditional integration of schema-consistent items with theircontext. Future studies can use neuroimaging to test the roleof hippocampal engagement and hippocampal-neocortical in-teractions in driving the context-dependent recall effects ob-served here.

In summary, we showed a context reinstatement effectusing environments that were designed to activate pre-existing schemas (i.e., underwater and outer-space planet en-vironments), and schema-consistent items were most likely toshow context-dependent memory effects. These results sug-gest that integration of items into active schemas plays a keyrole in driving context-dependent recall effects. However,identifying the exact features of our paradigm that were nec-essary and sufficient for obtaining these effects will requireadditional research.

Acknowledgements This work was supported by ONR MURI grantN00014-17-1-2961 to KAN.

Open Practices Statement The data and analyses codes are available athttps://osf.io/5t9mv.

Open Access This article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing, adap-tation, distribution and reproduction in any medium or format, as long asyou give appropriate credit to the original author(s) and the source, pro-vide a link to the Creative Commons licence, and indicate if changes weremade. The images or other third party material in this article are includedin the article's Creative Commons licence, unless indicated otherwise in acredit line to the material. If material is not included in the article'sCreative Commons licence and your intended use is not permitted bystatutory regulation or exceeds the permitted use, you will need to obtainpermission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/.

References

Alba, J. W. and Hasher, L. (1983) Is memory schematic? PsychologicalBulletin, 93, 203–231.

Bates, D., Mächler, M., Bolker, B. and Walker, S. (2015) Fitting linearmixed-effects models using lme4. Journal of Statistical Software,67.

Bransford, J. D. and Johnson, M. K. (1972) Contextual prerequisites forunderstanding: some investigations of comprehension and recall.Journal of Verbal Learning and Verbal Behavior, 11, 717–726.

Chen, J., Honey, C. J., Simony, E., Arcaro, M. J., Norman, K. A. andHasson, U. (2016) Accessing real-life episodic information fromminutes versus hours earlier modulates hippocampal and high-order cortical dynamics. Cerebral Cortex, 26, 3428–3441.

Collins, A. G. E. and Frank,M. J. (2013) Cognitive control over learning:creating, clustering, and generalizing task-set structure.Psychological Review, 120, 190–229.

DuBrow, S., Rouhani, N., Niv, Y. and Norman, K. A. (2017) Doesmental context drift or shift? Current Opinion in BehavioralSciences, 17, 141–146.

Dunsmoor, J. E., Ahs, F., Zielinski, D. J. and LaBar, K. S. (2014)Extinction in multiple virtual reality contexts diminishes fear rein-statement in humans. Neurobiology of Learning and Memory, 113,157–164.

Eich, E. (1985) Context, memory, and integrated item/context imagery.Journal of Experimental Psychology: Learning, Memory, andCognition, 11, 764–770.

Eichenbaum, H. (2004) Hippocampus: cognitive processes and neuralrepresentations that underlie declarative memory. Neuron, 44,109–120.

Fernandez, A. and Glenberg, A. M. (1985) Changing environmental con-text does not reliably affect memory. Memory & Cognition, 13,333–345.

Gilboa, A. and Marlatte, H. (2017) Neurobiology of schemas andschema-mediated memory. Trends in Cognitive Sciences, 21, 618–631.

Godden, D. R. and Baddeley, A. D. (1975) Context-dependent memoryin two natural environments: on land and underwater. BritishJournal of Psychology, 66, 325–331.

Isarida, T. and Isarida, T. K. (2007) Environmental context effects ofbackground color in free recall. Memory and Cognition, 35, 1620–1629.

Kurby, C. A. and Zacks, J. M. (2008) Segmentation in the perception andmemory of events. Trends in Cognitive Sciences, 12, 72–79.

Murnane, K., Phelps, M. P. andMalmberg, K. (1999) Context-dependentrecognition memory: The ICE theory. Journal of ExperimentalPsychology: General, 128, 403–415.

Poppenk, J. L. and Norman, K. A. (2012) Mechanisms supporting supe-rior source memory for familiar items: a multi-voxel pattern analysisstudy. Neuropsychologia, 50, 3015–3026.

581Psychon Bull Rev (2021) 28:574–582

Preston, A. R. and Eichenbaum, H. (2013) Interplay of hippocampus andprefrontal cortex in memory. Current Biology, 23, R764–R773.

Reggente, N., Essoe, J. K.-Y., Aghajan, Z. M., Tavakoli, A. V., McGuire,J. F., Suthana, N. A. and Rissman, J. (2018) Enhancing the ecolog-ical validity of fMRI memory research using virtual reality.Frontiers in Neuroscience, 12, 408.

Richmond, L. L. and Zacks, J. M. (2017) Constructing experience: eventmodels from perception to action. Trends in Cognitive Sciences, 21,962–980.

Schlichting, M. L. and Preston, A. R. (2015) Memory integration: neuralmechanisms and implications for behavior. Current Opinion inBehavioral Sciences, 1, 1–8.

Smith, S. M. (1979) Remembering in and out of context. Journal ofExperimental Psychology: Human Learning and Memory, 5, 460–471.

Smith, S. M. and Manzano, I. (2010) Video context-dependent recall.Behavior Research Methods, 42, 292–301.

Smith, S. M. and Vela, E. (2001) Environmental context-dependentmemory: a review and meta-analysis. Psychonomic Bulletin &Review, 8, 203–220.

Soderstrom, N. C. and McCabe, D. P. (2011) Are survival processingmemory advantages based on ancestral priorities? PsychonomicBulletin & Review, 18, 564–569.

Spalding, K. N., Jones, S. H., Duff, M. C., Tranel, D. and Warren, D. E.(2015) Investigating the Neural Correlates of Schemas:Ventromedial Prefrontal Cortex Is Necessary for NormalSchematic Influence on Memory. Journal of Neuroscience, 35,15746–15751.

Tse, D., Langston, R. F., Kakeyama, M., Bethus, I., Spooner, P. A.,Wood, E. R., Witter, M. P. and Morris, R. G. M. (2007) Schemasand memory consolidation. Science, 316, 76–82.

Tulving, E. and Thomson, D.M. (1973) Encoding specificity and retriev-al processes in episodic memory. Psychological Review, 80, 352–373.

van Kesteren,M. T. R., Beul, S. F., Takashima, A., Henson, R. N., Ruiter,D. J. and Fernández, G. (2013) Differential roles for medial prefron-tal and medial temporal cortices in schema-dependent encoding:from congruent to incongruent. Neuropsychologia, 51, 2352–2359.

van Kesteren, M. T. R., Krabbendam, L. and Meeter, M. (2018)Integrating educational knowledge: reactivation of prior knowledgeduring educational learning enhances memory integration. npjScience of Learning, 3, 1–8.

van Kesteren, M. T. R., Rignanese, P., Gianferrara, P. G., Krabbendam,L. and Meeter, M. (2020) Congruency and reactivation aid memoryintegration through reinstatement of prior knowledge. ScientificReports, 10, 4776.

van Kesteren, M. T. R., Ruiter, D. J., Fernández, G. and Henson, R. N.(2012) How schema and novelty augment memory formation.Trends in Neurosciences, 35, 211–219.

Wälti, M. J., Woolley, D. G. and Wenderoth, N. (2019) Reinstating ver-bal memories with virtual contexts: Myth or reality? PLOSONE, 14,e0214540.

Wang, S.-H. and Morris, R. G. M. (2010) Hippocampal-neocortical in-teractions in memory formation, consolidation, and reconsolidation.Annual Review of Psychology, 61, 49–79, C1–4.

Weiss, W. and Margolius, G. (1954) The effect of context stimuli onlearning and retention. Journal of Experimental Psychology, 48,318–322.

Whittington, J. C., Muller, T. H., Mark, S., Chen, G., Barry, C., Burgess,N. and Behrens, T. E. (2019) The Tolman-Eichenbaum machine:unifying space and relational memory through generalisation in thehippocampal formation. bioRxiv, 770495.

Zacks, J. M., Tversky, B. and Iyer, G. (2001) Perceiving, remembering,and communicating structure in events. Journal of ExperimentalPsychology: General, 130, 29–58.

Publisher’s note Springer Nature remains neutral with regard to jurisdic-tional claims in published maps and institutional affiliations.

582 Psychon Bull Rev (2021) 28:574–582