Accepted Manuscript Does reactivation trigger episodic memory change? A meta-analysis Iiona D. Scully, Lucy E. Napper, Almut Hupbach PII: DOI: Reference:
S1074-7427(16)30404-X http://dx.doi.org/10.1016/j.nlm.2016.12.012 YNLME 6600
To appear in:
Neurobiology of Learning and Memory
Received Date: Revised Date: Accepted Date:
31 October 2016 16 December 2016 21 December 2016
Please cite this article as: Scully, I.D., Napper, L.E., Hupbach, A., Does reactivation trigger episodic memory change? A meta-analysis, Neurobiology of Learning and Memory (2016), doi: http://dx.doi.org/10.1016/j.nlm. 2016.12.012
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Does reactivation trigger episodic memory change? A meta-analysis Iiona D. Scully, Lucy E. Napper, and Almut Hupbach Department of Psychology Lehigh University
Keywords: memory reactivation, reconsolidation, episodic memory
Correspondence: Dr. Almut Hupbach Department of Psychology Lehigh University 17 Memorial Drive East Bethlehem, PA 18015
USA
phone: +1 610 758 6762 email:
[email protected]
Abstract According to the reconsolidation hypothesis, long-term memories return to a plastic state upon their reactivation, leaving them vulnerable to interference effects and requiring restorage processes or else these memories might be permanently lost. The present study used a meta-analytic approach to critically evaluate the evidence for reactivation-induced changes in human episodic memory. Results indicated that reactivation makes episodic memories susceptible to physiological and behavioral interference. When applied shortly after reactivation, interference manipulations altered the amount of information that could be retrieved from the original learning event. This effect was more pronounced for remote memories and memories of narrative structure. Additionally, new learning following reactivation reliably increased the number of intrusions from new information into the original memory. These findings support a dynamic view of long-term memory by showing that memories can be changed long after they were acquired.
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1. Introduction Shortly after encoding memories are fragile and highly susceptible to both physiological and behavioral interference. Over time, memories stabilize, and once this consolidation process is complete, memories are resistant to change and stored permanently (for a review, see McGaugh, 2000). According to this view, memory failures and instances of misremembering reflect temporary problems of accessibility or source confusions, rather than loss or alterations of stored representations. Throughout the years, researchers have questioned whether consolidation is a “one-way street” converting fragile memories into permanent traces (see Dudai, 2004; Riccio, Millin, & Bogart, 2006 for reviews of the history of consolidation and reconsolidation). Alternatively, it was proposed and empirically demonstrated that memories can return to a fragile state when they are reactivated (e.g., Misanin, Miller & Lewis, 1968), and if these memories were to survive, they needed to undergo another round of consolidation, a process which was later termed reconsolidation (Przybyslawski & Sara, 1997). This idea ultimately broke through in 2000 when Nader, Schafe and LeDoux showed that retrieval of a consolidated memory induces a transient state of plasticity which can lead to a radically altered memory. Specifically, blocking de novo protein synthesis in the basolateral amygdala after retrieval of a fear memory caused amnesic effects, that is, loss of the fear memory. This effect has been replicated numerous times, and modifications of consolidated memories have been obtained in other experimental paradigms using a variety of reactivation and post-reactivation treatments (for reviews, see Besnard, Jocelyne, & Serge, 2012; Nader & Hardt, 2009; Nader & Einarsson, 2010). Together, these findings support the view that reactivation transfers memories from an inactive to an active state re-opening a temporary window for memory
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modification. Reconsolidation processes are then needed to preserve memories and transfer them back to an inactive state (Lewis, 1979; Nader et al., 2000). Reconsolidation has most frequently been studied in laboratory animals, particularly rodents. The invasive interventions that are used to block re-storage processes in animals, such as the injection of protein-synthesis inhibitors into targeted brain areas (e.g., Nader et al., 2000) are not suitable for human use. Therefore, the study of reconsolidation process in humans has lagged behind considerably. Human studies either employ less invasive physiological treatments, such as stress manipulations, the administration of propranolol or glucose, or utilize behavioral interference. In behavioral interference studies, new information that often bears some resemblance to the original information is presented shortly after the memory is reactivated. Reconsolidation is inferred when the delayed retrieval of the original information is impaired or “contaminated” with new information in comparison to a condition in which learning of new information was not preceded by reactivation, and in comparison to a condition in which reactivation was not followed by new learning. Using these types of postreactivation treatments, human reconsolidation effects have been reported for amygdaladependent, procedural and episodic memories (for reviews, see Agren, 2014; Schiller & Phelps, 2011; Hupbach, Gomez, & Nadel, 2015). The mechanisms underlying reactivation-induced memory changes remain controversial. Inherent in the reconsolidation account is the assumption that reactivation destabilizes memories, and that post-reactivation interventions either directly interfere with restorage processes or lead to the incorporation of new elements into the original memory. Alternatively, reconsolidation effects could reflect temporary retrieval deficits that can be
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alleviated by contextual reinstatement (Gisquet-Verrier et al., 2015; Riccio, Millin, & Bogart, 2006; Sederberg, Gershman, Polyn, & Norman, 2011). This debate resembles the old question as to whether forgetting reflects decay (i.e., loss of information) or interference (i.e., inaccessibility of information) which has been proven difficult to disentangle empirically because storage failure is almost impossible to demonstrate experimentally (Hardt, Nader, & Nadel, 2013; Miller & Matzel, 2006, Agren, 2014). Gisquet-Verrier and Riccio (2012) have advocated to consider the phenomenon of reactivation in its own right as an essential element contributing to the dynamic nature of memory, and several studies remain theoretically neutral as to whether reactivation-induced memory changes reflect storage or retrieval processes (e.g., Marin, Pilgrim, & Lupien, 2010; St. Jacques, Olm, & Schacter, 2013). In addition to the theoretical controversy, recent failures to replicate human reconsolidation effects have cast doubt on the ubiquity of reconsolidation effects and their reliability in humans (Hardwicke, Taqi, & Shanks, 2016). It is important to know whether and under which circumstances post-reactivation treatments are effective in altering what can be retrieved from an experience, as this knowledge has profound implications for the clinical (Schwabe, Nader, & Pruessner, 2014), educational (Bauer, 2011) and legal (Lacy & Stark, 2013) sectors. The aim of the present study was to critically evaluate the evidence for reactivationinduced long-term changes in human episodic memory. Most studies on this topic follow the same general procedure. Some prior learning experience is either reactivated or not reactivated before some physiological or behavioral interference manipulations are applied. The interference manipulations aim to impair or enhance the reactivated memory and/or to update
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it with new content. The effects of these manipulations are then tested after a delay. At the core of the reconsolidation account is the idea that long-term memories will only be susceptible to memory-modifying manipulations if they are reactivated prior to applying the manipulations. Therefore, we based our effect size calculation on a comparison between reactivation and noreactivation control groups. We used a meta-analytic approach in order to estimate the size of memory change and to evaluate several potential boundary conditions of this effect. Based on theoretical considerations, we included age of the memory, method of reactivation, type of study material, type of interference manipulation and the type of final memory test as potential moderators. (1) Age of memory. Dudai and Eisenberg (2004) proposed that consolidation progresses over longer time periods than originally assumed, reinterpreting reconsolidation as lingering consolidation effects. During the prolonged consolidation process, endogenous activation and retrieval stabilize the memory network, integrate it with other memories and help establish retrieval links, but also render memories susceptible to interference. According to the lingering consolidation hypothesis, post-reactivation treatments should affect recent memories more than remote memories that have had a chance to stabilize and can be accessed through multiple retrieval routes. We analyzed whether memories that were reactivated between 24 and 48 h after acquisition were more susceptible to post-reactivation effects than memories that were reactivated between 7 and 28 days after encoding. (2) Method of Reactivation. There is neural evidence that reactivation strength is related to memory change. Moderate reactivation of neural representations corresponding to specific items results in weakening of these representations and impaired recall of the corresponding
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items, whereas strong reactivation strengthens the representations and benefits subsequent retrieval (Detre, Natarajan, Gershman, & Norman, 2013; Norman, Newman & Detre, 2007). Similarly, retrieval practice that results in strong reactivation of learned material is one of the most effective ways to enhance memory and to promote long-term remembering (Roediger & Karpicke, 2006). Several studies further show that retrieval practice protects memories from proactive and retroactive interference (e.g., Halamish & Bjork, 2011; Potts & Shanks, 2012; Szpunar, McDermott, & Roediger, 2008). Based on these findings, we assessed whether memory changes were affected by the method of reactivation. We compared indirect reactivation methods that should elicit moderate levels of reactivation, such as contextual reinstatements, with direct reactivation methods that should elicit strong reactivations, such as re-exposing participants to stimuli or asking them to recall previously presented items. (3) Study material. Studies on human memory reconsolidation either use lists of items or material that has a narrative-like structure (e.g., videos, narrated slide shows, texts). Interference manipulations might have stronger effects for narrative-like materials, because reactivation of one component might trigger reactivation of the remaining elements. This might not be the case for unrelated items on a list. (4) Interference manipulation. The reviewed studies used two different types of postreactivation manipulations. Studies using physiological manipulations attempt to directly modulate re-storage processes by administering pharmacological agents that are known to affect memory consolidation or by subjecting people to stress, which causes hormonal changes that alter hippocampal and prefrontal functioning. In contrast, in behavioral interference paradigms, new information is presented after reactivation. This new information then
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becomes integrated into the reactivated memory or impairs it in a long-lasting manner. We included the interference manipulation as a moderator variable because these manipulations operate on fundamentally different levels: physiological manipulations target re-storage processes whereas behavioral interventions attempt to alter the content of the reactivated memory. (5) Retrieval test. Studies use either recall or recognition tests as a final memory assessment. While recognition can be based on familiarity alone, recall requires conscious recollection (Jacoby, Toth, & Yonelinas, 1993). Test-type dependent differences in reconsolidation effects could shed light onto the storage versus retrieval debate. The present meta-analysis focused exclusively on studies assessing reactivation-induced changes in episodic memory. Procedural or amygdala-dependent memories are supported by different brain systems and therefore were not considered in our analyses. We decided to compare reactivation to no-reactivation control conditions in our effect size calculations, because according to the reconsolidation account, only reactivated long-term memories should be susceptible to memory interfering treatments.
2. Materials and Methods Studies to be considered for the meta-analysis were collected by means of electronic searches of scientific publication databases including PsycInfo, PubMed, and Google Scholar. Searches were conducted using combinations of the following keyword(s): reconsolidation, episodic memory, and declarative memory. Studies printed in English and using human participants were reviewed. Additionally, reference lists of these studies were searched to
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identify additional studies that might have been missed by the database searches. In an effort to include unpublished data we contacted 24 researchers who had published studies on episodic memory reconsolidation.
2.2 Study inclusion criteria Studies were selected for inclusion based on five criteria: (1) encoding, reactivation/intervention, and retrieval took place in three separate sessions that were spaced at least 24 hours apart; (2) the design involved a comparison of a reactivation condition and a control condition in which memory was not reactivated; (3) after reactivation, a behavioral or physiological interference manipulation was implemented; (4) study participants were neither children or older adults (age > 60); (5) the necessary information for calculating an effect size was obtained. A total of 43 effect sizes were calculated (35 for changes in memory for the original information and 8 for changes in intrusion levels, see below) from 29 studies that had been conducted between 2007 and 2016.
2.3 Outcome Variables All of the included studies examined the number of items correctly retrieved from the original memory. Some studies using behavioral interventions (n = 7) additionally examined the number of intrusions from new information into original memories. Following recommendations against aggregating distinctly different studies (Lipsey & Wilson, 2001), we performed separate meta-analyses for these outcome variables. Because of the small number
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of studies examining enhancement of correctly retrieved items (n = 5), we ignored the direction of memory change, as long as both outcomes reflected anticipated memory changes. For instance, glucose administration is assumed to positively affect reconsolidation and should therefore increase the number of items that can be retrieved in the final memory test, whereas behavioral interference is always assumed to interfere with the reactivated memory, and should therefore reduce the number of items retrieved. When the change reported was contrary to the reconsolidation hypothesis, we coded the effect size as negative (e.g., when behavioral interference after reactivation resulted in an increase of items retrieved from the original memory in comparison to the control group). For the retrieval analysis, a positive effect size indicates that the reactivation group had greater change in the number of correctly retrieved items than the control group. For the intrusion analysis, a positive effect size indicates that reactivation resulted in more intrusions than the control condition.
2.4 Method of Analysis All statistical data (i.e., standardized mean difference, means and standard deviations, means and standard errors, t-statistics, and F-statistics) on the comparison between a reactivation condition and a no reactivation condition were extracted from each article and converted to the standardized mean difference (d; Cohen, 1988). A sample size bias correction (Hedges, 1981) was performed on each effect size in order to correct for upward bias with small sample sizes. Before calculation of the mean effect size, studies were examined for possible outliers (Lipsey & Wilson, 2001). One study (Sandrini et al., 2013) provided an effect size for the number
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of correctly retrieved items that was more three standard deviations above the mean. This study was the only one using transcranial magnetic stimulation as a means to modulate reconsolidation, and none of the other studies used methods that directly altered neuronal processing. Consequently, this study was excluded from further analysis. The final set t included 42 effect sizes (34 for changes in memory for the original information and 8 for changes in intrusion levels). For each analysis, forest plots depicting effect sizes along with their 95% Confidence Interval (CI) are presented. Based on recommendations from Field & Gillett (2010), randomeffects meta-analyses were performed and mixed models (MetaF; Lipsey & Wilson, 2001) were conducted for moderator analyses using the restricted maximum likelihood estimator (Viechtbauer, 2005). This approach allows the results of the current meta-analysis to be generalized beyond the studies included in the current analysis (Field & Gillett, 2010). Z tests were performed to examine the statistical significance of estimated effect sizes. To examine variance in effect sizes across studies, a homogeneity (Cochran’s Q) statistic was calculated (Rosenthal, 1991; Lipsey & Wilson, 2001). Variation among study effect sizes is unavoidable (Higgins, Thompson, Deeks, Altman, 2003) and a significant Q statistic indicates that the observed variance is greater than would be expected by chance if all studies came from a common population of effect sizes. Given problems in this test’s ability to detect true heterogeneity in effect sizes (Higgins, 2003), I2 was also calculated in order to quantify any inconsistencies in study results. I2 values of 25%, 50%, and 75% indicate low, moderate, and high heterogeneity (Higgins et al. 2003). When effect sizes are heterogeneous, it can be
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appropriate to explore whether a moderator variable helps explain the variability in effect sizes (Lipsey & Wilson, 2001). Using multiple effect sizes from the same study can disproportionally affect the estimated population effect size (Lipsey & Wilson, 2001), therefore, only one effect size per study was included in each analysis. The aim of this analysis was to compare the effects of interference on reactivated versus non-reactivated memories. Studies that reported multiple effects often included different types of reactivation. For studies that included more than one reactivation condition we chose to include the reactivation condition that most closely resembled the reactivation conditions used in the earliest episodic reconsolidation studies by Forcato, Argibay, Pedreira, and Maldonado (2007) and Hupbach, Gomez, Hardt, and Nadel (2007) to reduce between-study variability. Several studies reported effect sizes for both emotional and neutral memories (Bos, Schuijer, Lodenstijin, Beckers, & Kindt, 2014; James et al., 2015; Marin et al., 2010; Schwabe & Wolf, 2009, 2010; Schwabe, Nader, Wolf, Beaudry, & Pruessner, 2012; van Schie, van Veen, van der Hout, & Engelhard, 2016; Wichert, Wolf, & Schwabe, 2011, 2013, 2013; Wirkner, Löw, Hamm, & Weymar, 2015; Zhao et al., 2011; Zhao, Zhang, Shi, Epstein, & Lu, 2009). If the intervention or reactivation procedure specifically targeted emotional memories, we included effect sizes for emotional memories only. This was the case for two studies that used beta-adrenergic blocking agents (Schwabe et al., 2012; Zhao et al., 2011), and for one study that used rapid serial visual presentation as a reactivation procedure (Wirkner et al., 2015). If effects were reported separately for positive and negative material (Schwabe et al., 2012; Zhao et al., 2011; but Wirkner et al. reported only combined effects), we selected effects for negative material to enhance consistency with another study
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that used negative material exclusively (James et al., 2015). For all other studies reporting effects for both neutral and emotional material, we only included effect sizes for neutral memories, because our meta-analysis did not specifically target episodic memories of emotional content.
2.5 Publication bias The results of a meta-analysis may be influenced by the fact that the majority of effect sizes come from published studies. This bias may inflate effect size estimates in favor of significance (Rosenthal, 1979). In order to examine this bias, Rosenthal's (1979) fail-safe N was calculated. This sampling bias measure provides an estimate of the number of null results needed to nullify a significant mean effect size. In addition, funnel plots (Light & Pillemer, 1984) were create to examine sample size bias. Funnel plots present each study’s effect size plotted against the study’s measure of standard error. For smaller studies, the effect sizes should be shattered at the base of the funnel, while the effect sizes of larger studies should be more narrowly distributed at the top of the funnel (Egger, Davey Smith, Schneider & Minder, 1997). An asymmetrical funnel plot indicates potential publication bias, as well as other potential issues such as heterogeneity of effect sizes (Egger et al., 1997).
3. Results This meta-analysis examined 28 studies reporting on 42 effect sizes collected from 1085 participants. Published studies were published between 2007 and 2016. We also included
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unpublished work (n = 3) conducted during this time period (see Appendix for a complete list of studies).
3.1 Effects of Reactivation on Number of Items Correctly Retrieved Meta-analytic Results. A meta-analysis was conducted for the 34 effect sizes examining the effect of reactivation-induced memory change on the number of items correctly retrieved from the original memory. This analysis produced a significant weighted mean effect size of d = 0.29 (95% CI: 0.12, 0.46; Z = 3.39, p < .001; see Figure 1 for a forest plot of the effect sizes from each study and the overall effect size). The results of the Q test was significant, Q(33) = 73.85, p < .001, with moderate between-study variability (I2 = 55%).
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Figure 1. Forest plot of effect sizes and 95% confidence intervals for the retrieval meta-analysis. A positive effect size indicates that the reactivation group had greater change in memory than the control group.
Moderator Variables. The moderator analysis revealed a marginally significant effect of the study material (narratives vs. lists) on reactivation-induced memory change, Q(1) = 3.45, p = .06. Examining the mean effect sizes for each category revealed that memories for narratives (n = 5) showed significant changes and a moderate effect size (d = 0.62; 95% CI: 0.24, 1.01; Z =
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3.15, p = .001), and memories for lists (n = 29) also showed significant changes but a small effect size (d = 0.22; 95% CI: 0.04, 0.39; Z = 2.38, p = .02). The moderator analysis examining the delay from encoding to reactivation revealed a marginally significant effect of age of memory, Q(1) = 3.55, p = .06. Examining the mean effect sizes for the studies with a short delay between encoding and reactivation revealed a marginally significant effect size (n = 22; d = 0.19; 95% CI: -0.01, 0.38; Z =1.85, p = .06). In contrast, studies with long delays (n = 12) showed significant reactivation-induced changes (d = 0.53; 95% CI: 0.23, 0.83; Z = 3.49, p < .001). Additional moderator analyses examining the effects of reactivation method, interference manipulation, and test type were all non-significant (p ≥ .29), indicating that the effects of reactivation were consistent across these different research designs. Publication Bias. In order to examine how publication bias may affect this meta-analysis on the effect of reactivation on retrieval, we examined the fail-safe N (Rosenthal, 1979) and created a funnel plot (see Figure 2). The fail-safe N test indicated that 195 additional studies with an effect size of zero would be required to bring the estimated mean effect size to a nonsignificant value. Examination of the funnel plot shows that the effect sizes appear to be distributed symmetrically around the weighted mean effect size, providing further evidence against publication bias. The variation of the points for the studies with larger standard error is larger than expected and is consistent with our decision to use a random effects, rather than a fixed-effect, analysis.
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Figure 2. Funnel plot examining publication bias for studies that examined reactivation induced changed measured in retrieval of the original memory.
3.2 Effects of Reactivation on Number of Intrusions Meta-Analytic Results. A meta-analysis was conducted for the eight effect sizes examining the effect of reactivation induced memory change for intrusions. This analysis produced a weighted mean effect size of d = 1.03 (95% CI: 0.75, 1.31; Z = 7.24, p < .001). Figure 3 presents a forest plot of the effect sizes from each study and the overall effect size. The intrusion effect sizes were homogeneous, Q(7) = 4.64, p = .70, I2 = 0%. Given the lack of heterogeneity and the fact that the designs of studies assessing intrusions were extremely similar (i.e., all studies used lists, short delays, and indirect reactivation) moderator analyses were not conducted. 17
Publication Bias. As expected given the small number of studies, examination of the funnel plot (see Figure 4) suggested possible asymmetry (i.e., a lack of studies with high precision and effect sizes below the mean of d = 1.03). However, the fail-safe N indicated that 102 additional studies with an effect size of zero would be required to bring the mean effect size to a non-significant value.
Figure 3. Forrest plot examining intrusions.
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Figure 4. Funnel plot examining intrusions.
4. Discussion The meta-analyses provided clear evidence that reactivation triggers episodic memory change. Specifically, reactivation renders episodic memories susceptible to physiological and behavioral interference manipulations. Post-reactivation manipulations induce changes that alter the amount of information that can be later retrieved from the original memory. For this effect several moderator variables were examined. Reactivation induces large and reliable changes in the number of intrusions from new information into original memory, an effect that has previously been interpreted as reflecting an updating mechanism (Hupbach et al., 2007) essential for maintaining a memory’s relevance (e.g., Lee, 2009). Because of the small number
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of studies and their homogeneous designs, it was not possible to isolate factors that moderate this intrusion effect. Reactivation induced a small but fairly consistent change in the amount of information that could be recalled from the original memory. This effect was moderated by the age of the reactivated memory and the type of study material. Reactivation-induced changes were more pronounced for narrative-type materials than list memories. This could be due to differences in the extent by which narratives and lists are reactivated by reminders. Because of the cohesive nature of narratives, reactivation of one story component might easily spread to other story elements, reactivating the memory as a whole and making it broadly susceptible to physiological or behavioral manipulations. In contrast, the lists used in the reviewed studies were largely comprised of unrelated items, thus reactivation of one item might not as easily spread to the remaining items on the list. Moreover, when items were presented repeatedly, the order of presentation was often randomized. Therefore, reactivation might be more comprehensive for narratives than for lists. This post-hoc explanation should be carefully examined in future studies by manipulating presentation order and list cohesiveness as well as manipulating which parts of a list are represented during reactivation or explicitly tested. The age of the reactivated memory moderated the amount of information that could be retrieved from the original memory. According to the lingering consolidation hypothesis (Dudai & Eisenberg, 2004), post-reactivation treatments should have stronger impacts on younger than older memories, because the latter had a chance to stabilize, form connections with other memories, and establish several retrieval routes. We did not find evidence for this hypothesis. Instead, reactivation only moderately affected memories that were between 24 and 48 h old,
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but triggered significant changes in memories that were between 1 and 4 weeks old. It could be the case that 24 to 48 h old memories were indeed not yet fully consolidated, and thus, manipulations sometimes affected both reactivated and non-reactivated memories. Because effect size calculations were based on the comparison between reactivation and noreactivation conditions, and not between intervention and no-intervention conditions, we might have obtained a smaller overall effect size in the shorter delay condition. Importantly however, and contrary to the lingering consolidation hypothesis, reactivation affected remote memories, supporting the view that reactivation returns consolidated memories to a plastic state (Nader et al., 2000). Based on prior findings that testing safeguards memories against interference (e.g., Halamish & Bjork, 2011; Potts & Shanks, 2012; Szpunar et al., 2008) and that strong reactivations strengthen neural representations (Detre, et al., 2013; Norman et al., 2007), we had assumed that direct reactivations should induce less memory change than indirect reactivations. The meta-analysis did not confirm this prediction; effects sizes were not moderated by reactivation method. However, directed reactivation studies differ considerably in their method of reactivation as reflected by significant inter-study variability, and systematic studies evaluating how method and strength of reactivation interact with post-reminder treatments are needed to assess under which conditions direct reactivations induce versus prevent memory modifications. For instance, in behavioral interference studies reactivation strength might interact with whether new information contradicts the original information or can co-exist with the original information (cf. Hupbach, 2011). If the new information contradicts the previously learned information, strong reactivation might trigger a
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hypercorrection effect (Butterfield & Metcalf, 2001; Fazio & Marsh, 2009), that is, strong reactivation could result in more forgetting of the original and updating with new information than moderate reactivation (e.g., retrieval-enhanced suggestibility, e.g., Chan & LaPaglia, 2013). Both physiological and behavioral interference manipulations were effective in altering the amount of information that could be retrieved from reactivated memories. This is not to say that these manipulations operate on the same underlying process. While physiological manipulations are assumed to directly intervene with re-storage processes, behavioral manipulations attempt to alter the content of the reactivated memory. The meta-analysis shows that both manipulations can be effective in altering what can be recalled from a prior experience. Thus, both types of interference manipulations could be explored when thinking about ways to achieve long-term memory changes in applied settings. The type of memory test that was used to assess the delayed retrieval of the original memory (recall versus recognition) did not moderate the magnitude of the reactivated-induced memory change. Recognition, particularly when lures are not highly similar to previously studied targets, can be achieved by relying on familiarity alone, whereas recall commonly involves the generation of possible retrieval candidates, a process that requires recollection. An accessibility problem is often inferred when items can be recognized but not recalled; that is, items are still available in memory, but difficult to access (Tulving & Pearlstone, 1966). If items can be neither recognized nor recalled, it might mean that they are unavailable. However, as stated in the introduction, (re-)storage failure is difficult to prove empirically (Agren, 2014), and even recognition failures can be based on temporary inaccessibility (e.g., Guerin, Robbins, Gilmore, & Schacter, 2012). Consequently, the meta-analysis does not provide a simple answer
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to the question as to whether reconsolidation reflects accessibility or availability problems, but we cautiously conclude that reconsolidation does not seem to reflect a problem of accessibility alone. Previous studies have identified neural signatures of memories that are remembered, inaccessible, or forgotten (e.g., Habib, Nyberg, & Nilsson, 2007; Sadeh, Ozubko, Winocur, & Moscovitch, 2014), and reconsolidation studies would benefit from a similar examination of neural signatures during reactivation and retrieval. Such an analysis could identify whether post-reactivation manipulations can selectively weaken or strengthen reactivated memory representations.
5. Limitations The reconsolidation account assumes that reactivation returns memories to a malleable state in which they are susceptible to behavioral and physiological interference. Thus, without reactivation, interference manipulations should be ineffective. Based on this tenet, effects sizes were calculated as differential effects of interference manipulations on reactivated versus nonreactivated memories. Alternatively, we could have compared how interference in comparison to control manipulations affect reactivated memories. Such an analysis could yield different conclusions because not all studies implement both a no-interference control manipulation and a no-reactivation control condition. The meta-analysis revealed that reactivation predisposes memories to intrusions from new information. We could identify only seven studies assessing intrusion effects, and all of these studies used very similar designs, that is, a list of items was presented during study, after a 24-48 h delay memory was indirectly reactivated, followed by the presentation of a new list.
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Because of the small number of studies and their homogeneous methodologies, moderator analysis was not warranted. The meta-analysis evaluating the change in number of items that could be retrieved from the original memory revealed significant moderation by age of memory. However, studies were rather arbitrarily divided into two categories: one category comprised memories that were between 24-48 h old and the other category captured memories that were between 7 and 28 days. Consolidation is a continuous process lasting for days, weeks, months or even years (Dudai & Eisenberg, 2004), but because none of the reviewed studies assessed memories that were between 48h and 7 days old, and because overall fewer studies assessed 7 to 28 day old memories, it was not possible to treat age as a continuous moderator variable. Furthermore, age of memory was partially confounded with delay between reactivation and final test in that studies implementing longer delays between encoding and reactivation often implement longer time delays between reactivation and test. Although there is no a priori reason why delaying retrieval should increase the observed difference between reactivated and control memories, the finding that older memories were more susceptible to change should be interpreted with caution. We focused our meta-analysis on reactivation-induced changes of neutral episodic memories. To increase consistency within the set of studies, we selected effects sizes for neutral memories when studies reported effects for both emotional and neutral memories, unless the reactivation procedure or the intervention specifically targeted emotional memories. Because we only included a small subset of emotional effects in our meta-analysis, we did not analyze emotionality as a moderator variable. Once the number of available studies increases, a
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direct comparison between reconsolidation of emotional and neutral memories becomes important, as it has direct implications for theory and therapeutic practice. It would have been interesting to evaluate the effectiveness of different reminders. However, since most of the reviewed studies implemented only one no-reactivation control condition, we were limited in our choice of reminders to include in the effect size calculations. In order to limit between-study variability, for studies reporting more than one reactivation condition, we selected the one that was most comparable to the ones used in the other studies. For indirect reactivation conditions, these were multi-component reminders including contextual reinstatements and reminder questions, and for studies using direct reactivation, participants were re-exposed to or tested on the study material. Additionally, several studies had to be excluded from our analyses, because no-reactivation control conditions were missing. We limited our analyses to adult samples due to the small number of studies that have examined reactivation-induced memory changes in other age groups, such as children or older adults. So far, memory updating seems fully functional by the age of 5 (Hupbach et al., 2011), but there is little evidence for reactivation-induced memory change in older adults (Jones et al, 2015; Sandrini et al., 2014; Vargus, 2009). More studies are needed to fully flesh out the developmental trajectory of reactivation-induced memory changes.
6. Conclusion The present meta-analyses show that reactivation reliably triggers episodic memory changes. Reactivating long-term memories makes them susceptible to both behavioral and physiological interference. Learning new information increases the number of intrusions from that information into the original memory. Physiological and behavioral interference 25
manipulations affect the amount of information that can be retrieved from the original memory. The latter effect is more pronounced for remote memories and for memories of narrative structure. These findings highlight the dynamic nature of memory by showing that memories can be altered long after they were acquired. This has important implications for educational (Bauer, 2009), legal (Lacy & Stark, 2013) and clinical practice. For instance, Lane, Ryan, Nadel and Greenberg (2015) proposed that reconsolidation mechanisms are the basis for psychotherapeutic change in a variety of therapeutic approaches, with different approaches targeting different memory components for reconsolidation. Furthermore, promising preliminary results have been obtained for reconsolidation-based interventions that aim to reduce the emotional intensity with which traumatic experiences are remembered by patients suffering from posttraumatic stress disorder (e.g., Brunet et al., 2008; 2011; Pundja, Sanche, Tremblay, & Brunet, 2012). Large scale reactivation- and placebo-controlled clinical studies are needed to test whether the present findings with neutral memories and non-clinical populations transfer to therapeutic settings.
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Appendix Table 1: Studies Included in the Meta-Analysis Studies
Study Material
Age of Memory
Reactivation Type
Interference Manipulation
Final Test
Bos et al. (2014) E1 Bos et al. (2014) E2 Chan & LaPaglia (2012) Catallini (2010)* Coccoz et al. (2013) E1a Coccoz et al. (2013) E1b Coccoz et al. (2013) E2 a Dongaonkar et al. (2013) Exp. 1 Dongaonkar et al. (2013) Exp. 2a Focato et al. (2009) Zhao et al. (2009) Hupbach (2015)a Hupbach & Dorskind (2014) Hupbach et al. (2007)a James et al. (2015)b Jones et al. (2015)a Marin et al. (2010) Potts and Shanks (2012) Schwabe et al. (2012)b
Lists Lists Narrative Lists Lists Lists Lists Lists Lists Lists Lists Lists Lists Lists Narrative Lists Narrative Lists Lists
Short Short Short Short Long Long Long Short Short Short Short Short Short Short Short Short Short Short Short
Indirect Indirect Direct Indirect Indirect Direct Indirect Indirect Indirect Direct Direct Indirect Indirect Indirect Direct Indirect Direct Direct Direct
Physiological: Socially Evaluated Cold Pressor Test Physiological: Socially Evaluated Cold Pressor Test Behavioral: Misinformation Narrative Behavioral: Object List Physiological: Cold Pressor Stress Physiological: Cold Pressor Stress Physiological: Glucose Behavioral: Object List Behavioral: Object List Behavioral: Cue-Response Syllables Physiological: Trier Social Stress Test Behavioral: Object List Physiological: Cold Pressor Stress Behavioral: Object List Behavioral: Tetris Behavioral: Object List Physiological: Trier Social Stress Test Behavioral: English-Finnish Word List Physiological: Propranolol
Recognition Recognition Recognition Recall Recall Recall Recall Recall Recall Recall Recall Recall Recall Recall Recognition Recall Recall Recall Recognition
Schwabe & Wolf (2009) Schwabe & Wolf (2010) Wichert er al. (2011) Exp. 1a Wichert er al. (2011) Exp. 1b Wichert er al. (2011) Exp. 1c Wichert et al. (2013a) Exp. 1a
Narrative Narrative Lists Lists Lists Lists
Long Long Short Long Long Long
Direct Direct Direct Direct Direct Direct
Behavioral: War of the Ghosts Story Physiological: Socially Evaluated Cold Pressor Test Behavioral: IAPS Pictures Behavioral: IAPS Pictures Behavioral: IAPS Pictures Behavioral: IAPS Pictures
Recall Recall Recall Recall Recall Recognition
Wichert et al. (2013a) Exp. 1b Wichert et al. (2013b)
Lists Lists
Long Long
Direct Direct
Behavioral: IAPS Pictures Behavioral: IAPS Pictures
Recognition Recognition
b
Wirkner et al. (2015) Lists Hardwicke et al.,(2016) Lists b Zhao et al. (2011) Lists Zhu et al. (2016) Lists van Schie et al. (2016) Lists a Capelo et al. (2016) Lists a Studies included in the intrusion analysis. b Effect sizes based on emotional material.
Short Short Long Short Long Short
Direct Direct Direct Direct Direct Indirect
Behavioral: IAPS Pictures Behavioral: Number Sequences Physiological: Propranolol Behavioral: Word Pairs Behavioral: IAPS Pictures Behavioral: Object List
Recognition Recall Recall Recall Recognition Recall
39
Highlights
Meta-analyses revealed reliable reconsolidation effects for episodic memories.
Reactivation makes episodic memories susceptible to physiological and behavioral interference.
Effects are more pronounced for remote memories and memories of narrative structure.
New information presented after reactivation intrudes into the original memory.
Findings support a dynamic view of long-term memory.
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