Individual differences in retrieval-induced forgetting affect the impact of frontal dysfunction on retrieval-induced forgetting.

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Individual differences in retrieval-induced forgetting affect the impact of frontal dysfunction on retrieval-induced forgetting ab

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Jacqueline F.I. Anderson , Marie-Claire Davis , Paul B. Fitzgerald & Kate E. Hoy a

Melbourne School of Psychological Sciences, The University of Melbourne, VIC, Australia b

Department of Psychology, Alfred Health, Melbourne, VIC, Australia

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MAPrc Monash Alfred Psychiatry Research Centre, The Alfred and Monash University Central Clinical School, Melbourne, VIC, Australia Published online: 11 Feb 2015.

To cite this article: Jacqueline F.I. Anderson, Marie-Claire Davis, Paul B. Fitzgerald & Kate E. Hoy (2015) Individual differences in retrieval-induced forgetting affect the impact of frontal dysfunction on retrieval-induced forgetting, Journal of Clinical and Experimental Neuropsychology, 37:2, 140-151, DOI: 10.1080/13803395.2014.993307 To link to this article: http://dx.doi.org/10.1080/13803395.2014.993307

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Journal of Clinical and Experimental Neuropsychology, 2015 Vol. 37, No. 2, 140–151, http://dx.doi.org/10.1080/13803395.2014.993307

Individual differences in retrieval-induced forgetting affect the impact of frontal dysfunction on retrieval-induced forgetting Jacqueline F.I. Anderson1,2, Marie-Claire Davis1, Paul B. Fitzgerald3, and Kate E. Hoy3 1

Melbourne School of Psychological Sciences, The University of Melbourne, VIC, Australia Department of Psychology, Alfred Health, Melbourne, VIC, Australia 3 MAPrc Monash Alfred Psychiatry Research Centre, The Alfred and Monash University Central Clinical School, Melbourne, VIC, Australia 2

Downloaded by [134.117.10.200] at 16:49 08 May 2015

(Received 21 January 2014; accepted 25 November 2014) Introduction: Retrieval-induced forgetting (RIF) paradigms are used to investigate successful forgetting of irrelevant information. Responses to the RIF paradigm can vary substantially, but to date there has been limited investigation of the individual difference factors that contribute to RIF performances. This study investigated whether individual differences in baseline RIF ability impacted on RIF performance after temporarily induced frontal dysfunction. To examine this question, left dorsolateral prefrontal cortex (DLPFC) function was temporarily reduced using transcranial direct current stimulation (tDCS). Method: Fourteen individuals received tDCS (sham/active) on two separate occasions and completed a RIF paradigm within 30 minutes of receiving tDCS. Results: As expected, the group of individuals who demonstrated high levels of RIF after sham tDCS demonstrated a significant reduction in RIF performance after active tDCS. Unexpectedly, however, those individuals who demonstrated low or reverse RIF effects after sham tDCS showed a significant increase in RIF after active tDCS. Conclusions: This is the first study to show that individual differences in premorbid RIF affect RIF performance after temporary reduction in left DLPFC function. These findings suggest that premorbid RIF ability may be an important factor to consider when investigating the impact of frontal dysfunction on RIF in patient populations. Keywords: Retrieval-induced forgetting; Individual differences; Transcranial direct current stimulation; Frontal lobe function; Memory.

The ability to successfully forget information is an adaptive cognitive process, which enables more effective encoding and retrieval of relevant information (Storm, Bjork, & Bjork, 2007). Retrievalinduced forgetting (RIF) is one mechanism of successful forgetting, whereby retrieval of information reduces later retrieval of related information (Anderson, Bjork, & Bjork, 1994). An example of this can be seen within a typical experimental RIF paradigm. Participants are exposed to a series of items and then practice retrieving a subset of these

items. On a later recall trial, as expected, participants will successfully retrieve a practiced item (e.g., orange). They will have more difficulty, however, retrieving a related but unpracticed item (e.g., apple) than an unrelated and unpracticed item (e.g., glove). Retrieval of the practiced items (Rp+) provides a measure of learning, but it is the relative difficulty in retrieving related but unpracticed (Rp–) items compared to retrieving unrelated and unpracticed (Nrp) items that is known as the RIF effect. RIF has been associated

None of the authors have any financial interest or benefit arising from the direct application of this research. PBF is supported by a NHMRC Practitioner Fellowship [606907]. PBF has received equipment for research from MagVenture A/S, Medtronic Ltd, Cervel Neurotech, and Brainsway Ltd and funding for research from Cervel Neurotech. Address correspondence to: Jacqueline F. I. Anderson, Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, 3010, Australia (E‑mail: [email protected]).

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INDIVIDUAL DIFFERENCES IN RIF AND FRONTAL FUNCTION

with prefrontal regions and is thought to most likely rely on inhibitory processes (Bauml, Pastotter, & Hanslmayr, 2010; Johansson, Aslan, Bauml, Gabel, & Mecklinger, 2007; Wimber, Rutschmann, Greenlee, & Bauml, 2009). Specifically, it is argued that to prevent competition from the related unpracticed item (apple) impacting on retrieval of the practiced item (orange), inhibitory processes impede the retrieval of the related unpracticed item (apple) such that at later retrieval the related unpracticed item (apple) is more difficult to retrieve than the unrelated unpracticed item (glove; Anderson et al., 1994; Bauml et al., 2010; Storm et al., 2007). Noninhibitory mechanisms have also been put forward as explanations for the RIF effect. Proponents of alternative mechanisms largely argue that retrieval practice strengthens practiced items, and this strengthening interferes with the retrieval of nonpracticed items belonging to the same category (Storm & Levy, 2012). Although researchers accept that noninhibitory mechanisms may play a role in RIF, it is largely understood that inhibitory processes are integral in the RIF process (e.g., Mall & Morey, 2013; Storm & Levy, 2012; Wimber et al., 2009). Although RIF can be reliably demonstrated at a group level (Anderson et al., 1994; Storm et al., 2007), research shows that individuals differ in the extent to which they demonstrate the RIF effect (Levy & Anderson, 2008), with some individuals showing a strong RIF effect (i.e., Nrp > Rp–) and others demonstrating a low, absent, or reverse (i.e., Rp– ≥ Nrp) RIF effect (Aslan & Bauml, 2011). It is these normal variations in size of RIF, which exist between individuals, that are defined as individual differences in the RIF effect in this study. Individual differences in RIF performance can be related to performance in other cognitive domains. Aslan and Bauml (2011) found that working memory capacity (WMC) had a positive relationship with RIF, with high-WMC participants demonstrating more RIF than low-WMC participants. The authors argued that this finding supported an inhibitory executive-control account of the RIF effect that is mediated by the frontal lobes. Specifically, it has been shown that individuals with high levels of WMC are better able to inhibit distractors than individuals with low WMC (Redick, Heitz, & Engle, 2007). Similarly, Storm and Angello (2010) separated participants into high- and low-RIF groups to demonstrate that individuals with high RIF have a greater ability to overcome fixation during problem solving than individuals with low RIF. They argued that inhibition might be used in problem-solving tasks to overcome mental fixation to a previous, unsuccessful

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problem-solving approach and thereby facilitate the identification of a creative solution. The authors reported that their findings strongly supported an inhibitory explanation of the RIF effect, which indirectly implicates frontal lobe systems. Individual differences in RIF have also been demonstrated in functional neuroimaging, electrophysiological recording, and clinical studies. Functional magnetic resonance imaging (fMRI) studies have demonstrated that amount of frontal activity on fMRI is associated with the strength of the RIF effect (Kuhl, Wagner, Dudukovic, & Kahn, 2007; Wimber et al., 2008). Johansson and colleagues (2007) showed that sustained event-related potentials (ERPs) at prefrontal sites were related to the magnitude of the RIF effect. Individual differences in RIF have also been related to mood, with lower or absent RIF being demonstrated in clinically depressed and dysphoric individuals (Bauml & Kuhbandner, 2007; Groome & Sterkaj, 2010). A number of frontal regions have been associated with variations in the RIF effect in functional neuroimaging studies, including anterior cingulate cortex, dorsolateral (DLPFC) and ventrolateral prefrontal cortex (Kuhl et al., 2007; Wimber et al., 2008; Wimber et al., 2009). Further, a relationship between RIF performance and frontal regions has been suggested from clinical studies, with impairments in RIF reported in some populations thought to have frontal lobe dysfunction (Storm & White, 2010), although not in others (Conway & Fthenaki, 2000). To date, studies investigating whether frontal lobe dysfunction is associated with changes in RIF have focused on groups, who have typically been investigated after the development of a condition (Conway & Fthenaki, 2000; Moulin et al., 2002; Nestor et al., 2005). Although this approach provides information at the group level, it does not allow examination of whether individual differences in RIF prior to injury/disease impacts on RIF performance after the development of frontal impairment. To enable a better understanding of the impact of frontal dysfunction on RIF performance at the level of the individual, comparing an individual’s RIF performance when they have dysfunction to their performance when they do not have dysfunction would be useful. Transcranial direct current stimulation (tDCS) is one means of temporarily modulating cortical functioning in healthy individuals in order to create a “virtual lesion” (Nitsche & Fregni, 2007; Rossini, Rossini, & Ferreri, 2010; Vines, Schnider, & Schlaug, 2006). tDCS alters the resting membrane potential of neurons in either a de- or a hyperpolarizing direction; thus making them more or less likely to


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fire (Nitsche et al., 2008). Anodal stimulation has been consistently shown to increase the likelihood of neuronal firing, while cathodal stimulation generally results in a reduction in brain activity (Nitsche et al., 2008). The effects of a single 20minute stimulation session have been shown to last for approximately one hour (Nitsche et al., 2008). Cathodal tDCS therefore allows for the investigation of RIF performance following the induction of a temporary reduction in frontal lobe function. In the clinical setting it is important to have an understanding of an individual’s premorbid abilities so that changes in performance associated with disease or disorder can be interpreted appropriately. Understanding the individual differences associated with normal RIF performance and then investigating the consequences of frontal dysfunction on that individual’s performance will advance our ability to interpret RIF performance in clinical populations; this will be particularly beneficial for groups who can undergo a premorbid examination (e.g., presurgical) but it will also improve our understanding of the limitations of interpreting a patient’s performance in isolation from their premorbid abilities. The size of the RIF effect varies substantially in normal populations from inverse RIF effects (i.e., Rp– > Nrp) in some individuals to strong RIF effects (Rp– < Nrp) in others. The underlying cause of this variation in RIF effect within the normal population is not well understood. On the basis of our understanding of the RIF effect to date, it seems that the effect of a frontal lesion on RIF function might have at least two possible consequences. The literature showing an association between amount of frontal activity and the strength of the RIF effect (Kuhl et al., 2007; Wimber et al., 2008) could lead to the prediction that after frontal dysfunction, RIF effects will reduce for individuals who were premorbidly high in RIF, but reduce relatively little in those who had a small RIF effect premorbidly as the latter group would have been using frontal systems relatively little on the task premorbidly, and a further reduction in frontal function would therefore have limited impact on inhibitory processes during the task. Alternatively, on the basis of inhibition theory (Anderson et al., 1994; Anderson & Spellman, 1995), which argues that the RIF effect is due to inhibition of semantically related but irrelevant items, a different prediction would seem more likely. Individuals with small RIF effects premorbidly might actually develop an inverse RIF effect (Nrp < Rp–), with Nrp items remembered more poorly than Rp– items. This is because reduction in inhibitory processes during retrieval practice

could result in enhancement in the recollection of items that are semantically related (Rp–) to the practiced items (Rp+). That is, in the absence of inhibition, practicing certain items (Rp+) will result in the item strength of semantically related items (Rp–) being increased in memory, and thereby these semantically related but unpracticed items (Rp–) will be more readily recalled during the retrieval phase resulting in a relative increase in Rp– compared to Nrp items (Anderson & Spellman, 1995). In contrast, individuals with large RIF effects premorbidly would be expected to demonstrate a reduction in RIF performance as the reduction in inhibitory processes during learning should merely reduce the inhibition of Rp– items. Due to the lack of clarity about the consequence of frontal dysfunction on the RIF effect in individuals with premorbidly distinct RIF levels, the aim of this study was to assess RIF in a group of individuals without a history of frontal lobe dysfunction and investigate the impact of temporary frontal dysfunction on those individuals’ RIF performance. Given the clear research evidence of an association between the strength of RIF performance and frontally mediated processes (Kuhl et al., 2007; Wimber et al., 2008), in the context of some ongoing discussion about the role of inhibitory processes in RIF (Storm & Levy, 2012) it was predicted that individuals with both high and low RIF after sham tDCS would show a reduction in RIF after active tDCS and that individuals with high RIF after sham tDCS should show a greater reduction in RIF performance after active tDCS than individuals with low (or absent) sham RIF.

METHOD Participants The fourteen eligible participants who responded to recruitment advertising took part in the study (males = 5; age range = 19–64 years; M = 40.0 years; SD = 15.34 years). Education ranged from 4 years of secondary schooling to currently undertaking tertiary studies. Four participants were from a non-English-speaking background, but all four were current tertiary students at an Englishspeaking Australian University, with excellent conversational English. Inclusion criteria were: aged between 18 and 65 years, good conversational English language skills, right-handed, and capacity to consent to participate. Exclusion criteria were: unstable medical condition, neurological disorder, psychiatric disorder, history of a seizure disorder, pregnant or lactating, metal in their cranium, a


pacemaker, cochlear implant, medication pump, or other electronic device in their body (Nitsche et al., 2008). Female premenopausal participants underwent a urine pregnancy test prior to their first session. Participants were reimbursed A$15 per session (A$30 in total) to cover travel expenses. The study protocol was approved by the Alfred Hospital, Monash University, and University of Melbourne Human Subjects Research and Ethics Committees.


Materials and procedure Each participant completed the RIF task after tDCS on two separate occasions. At each occasion either active or sham tDCS was administered. The order of administration of active versus sham tDCS was randomized and counterbalanced. A median split of the group was conducted on the basis of the sham tDCS performances, creating two groups: low-RIF (n = 7) and high-RIF (n = 7). Examination of stimulation administration after creation of the two groups showed that the groups had identical frequencies of stimulation order; that is, 57% of the low-RIF group and 57% of the highRIF group received active tDCS followed by sham tDCS, and the remaining participants in each group received the opposite sequence of tDCS. This meant that any order effects, which were minimized by using a counterbalanced presentation, did not differ between the groups. The participant and examiner were blind to tDCS condition. RIF Two groups of 72 category–exemplar pairs (i.e., 12 categories with six exemplars each) were used. To avoid practice effects across the two testing sessions, two different sets of stimuli for the RIF task were used. The category–exemplar pairs were taken from the Van Overschelde and colleagues category norms (Van Overschelde, Rawson, & Dunlosky, 2004). These authors ranked exemplars on the basis of how commonly they were provided by participants to a given category. In the present study, three high-ranked and three low-ranked exemplars were used for each stimuli set. To ensure that list order did not impact the results, the order of presentation of the two sets was counterbalanced across participants. For counterbalancing purposes, the same 12 categories were used for each stimuli set, with different exemplars in each set; the categories used for Rp+ versus Nrp items did not change between stimulus sets. Equivalent numbers of high- and low-ranked exemplars were

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used in the retrieval practice phase in both stimuli sets, and all participants received the same stimuli sets. In order to investigate the role of frontal lobe function on RIF performance, cathodal tDCS was given prior to cognitive assessment. There is growing research showing state-dependency effects of brain stimulation; as the aim of the current study was to mimic a temporary lesion effect on brain activity, stimulation was given to resting rather than active brain tissue (i.e., during a rest period prior to test administration; Silvanto, Muggleton, & Walsh, 2008). Following 20 min of either sham or active 2-mA cathodal tDCS, participants completed the task, which had three main components—learning phase, retrieval practice phase, and cued-recall phase. During the learning phase, participants were presented with each of the 72 test category–exemplar pairs for 5 seconds on a computer screen. Retrieval practice was carried out on half of the exemplars from half of the categories (i.e., 6 categories with 3 exemplars from each category); participants practiced retrieval three times on these 18 items (Rp+). At each occasion, participants were presented with the category and a two-letter exemplar cue (e.g., FRUIT Ap____) and were asked to recall aloud the exemplar being cued (e.g., apple). After retrieval practice, participants engaged in an 8-minute number-matching distractor task. During cued recall, participants were presented with the category and a one-letter exemplar cue for all 72 of the category– exemplar pairs presented in the learning phase (e.g., FRUIT A____) and were asked to recall aloud the exemplar being cued. The test was carried out in ≤27 min and was therefore complete within the 60-min window of tDCS effectiveness (Nitsche et al., 2008; Ohn et al., 2008). Sessions were completed at least one week apart to minimize interference effects across sessions. As there were two sessions, the cued-recall phase in the second session was considered vulnerable to participants increasing their efforts at remembering the unpracticed category–exemplar pairs in anticipation of later testing based on their experience in the first session. In order to reduce the likelihood of this occurring, participants were explicitly told after the retrieval practice phase in the second session that they would not have to recall the word-pairs later in the session. tDCS Stimulation was delivered using a programmable direct current stimulator manufactured by neuroConn GmbH. tDCS was administered via rubber electrodes (35cm2) covered in saline-soaked


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sponges. In line with previous literature, which indicates left DLPFC involvement in RIF and also supports an association between the left DLPFC and verbal encoding more broadly (Buckner, 1999; Wimber et al., 2009), the cathodal electrode was positioned on the scalp above the left DLPFC or F3 as determined by the international 10–20 system of electrode placement (Fregni et al., 2005; Homan, Herman, & Purdy, 1987), and the anodal reference electrode was placed over the right supraorbital area, consistent with previous studies (Fregni et al., 2005; Zaghi, Acar, Hultgren, Boggio, & Fregni, 2010). Stimulation was provided for 20 minutes with fade in and out durations of 10 s. Participants attended for two sessions and received either active (2-mA cathodal) or sham stimulation. Sham stimulation was obtained by entering a “sham” rather than an “active” code into the stimulator, which triggered the software to cease stimulation after 30 s. This ensured that participants experienced the itching/tingling sensation and perceived that they were receiving active tDCS (Nitsche et al., 2008), without having lasting biological changes as there is no evidence to suggest that there are lasting biological effects of 30-s stimulation (Gandiga, Hummel, & Cohen, 2006; Nitsche et al., 2008). This methodology maintained blinding for participants and experimenter (M.C. D.) as stimulation codes were assigned by a researcher who was not involved in data collection (K.H.). A tDCS-free baseline RIF assessment was not conducted due to the nature of the RIF task. Specifically, the deception necessary for the second tDCS assessment would not have been credible if practiced a second time. This meant that it was only possible to validly assess RIF performance on two separate occasions. It was considered more methodologically rigorous to be able to make a sham versus active tDCS comparison, rather than a tDCS-free baseline versus active tDCS comparison. Therefore, no tDCS-free baseline RIF assessment was conducted; rather, the sham-tDCS condition was considered the best available proxy for a “normal”/premorbid performance. 3-Back task The 3-back task, which assesses working memory function, was administered at the sham assessment as an indicative measure of sham levels of executive function (Jaeggi, Buschkuehl, Perrig, & Meier, 2010) in all individuals. Participants were presented a sequence of letters on a computer screen. Successful performance comprised pressing

a key when the current letter on the screen was the same as the letter presented three items earlier. A total of 40 target items were presented during two assessment blocks of 3.5 minutes each.

Data analysis Following an initial examination of the equivalence of the stimulus sets, the baseline characteristics of the RIF effect in the current sample after sham tDCS are presented for the overall group as well as for the high-RIF and low-RIF groups. To investigate the role of individual differences (size of RIF effect after sham tDCS) on the RIF effect after active tDCS, a comparison of RIF performances on sham versus active tDCS is then reported for the high-RIF and low-RIF groups.

RESULTS Paired-samples t tests were used to investigate the equivalence of stimulus sets for each of the Rp+, Rp–, Nrp, and RIF variables. As shown in Table 1, no significant results were obtained, which indicated that performance on the two stimulus sets was equivalent. To separate the group into high- and low/absentRIF participants we conducted a median split on the basis of RIF performance (calculated as difference between Rp– and Nrp) on the sham tDCS assessment. The background characteristics of the resultant two groups of seven individuals (highRIF, low-RIF) are presented in Table 2. The size of the RIF effects after sham tDCS and after active tDCS are presented in Table 3 for the overall group as well as for the high-RIF and lowRIF groups. At a group level, after sham tDCS the low-RIF group showed a small RIF effect, but some individuals within the group did not demonstrate any RIF effect. TABLE 1 Means, standard deviations, and p-values of paired-samples t tests for comparison of stimulus sets

Variable

Stimulus Set 1 Mean (SD)

Stimulus Set 2 Mean (SD)

Rp+ Rp– Nrp RIF

84.07 46.00 58.64 12.64

87.29 44.29 56.79 12.50

(13.80) (17.59) (11.43) (14.46)

(11.02) (10.28) (13.89) (12.68)

p-value .316 .653 .613 .979

Note. Rp+ = retrieval practice items; Rp– = unpracticed items categorically related to Rp+ items; Nrp = unpracticed items that are unrelated to Rp+ items; RIF = Nrp – Rp–.

INDIVIDUAL DIFFERENCES IN RIF AND FRONTAL FUNCTION TABLE 2 Demographic characteristics in the high-RIF and low-RIF groups High-RIF (n = 7) Low-RIF (n = 7) Age (years): mean (SD) N by age band 18–29 years 30–49 years 50–65 years Gender Female Male a English (NESB ) Education Tertiary Secondary

40.57 (14.85)

39.43 (16.98)

3 2 2

3 2 2

4 3 3

5 2 1

5 2

5 2

Note. RIF = retrieval-induced forgetting. Non-English-speaking background.


a

Baseline characterization of the RIF effect Analysis of variance (ANOVA), examining the effect of group (overall, high-RIF, low-RIF) on sham RIF performances revealed that a significant RIF effect existed for the overall group, F(1, 13) = 12.907, p = .003, η2 = .498, and also for the highRIF group, F(1, 6) = 64.610, p < .001, η2 = .915, but not for the low-RIF group, F(1, 6) = 0.568, p = .480. Multivariate ANOVA was used to investigate the effect of group membership (high-, low-RIF) on RIF variable performance (Rp+, Rp–, Nrp) at sham tDCS. It demonstrated that the low-RIF group was trending towards recalling significantly fewer Rp+ words than the high-RIF group, F(1, 12) = 4.420, p = .057, η2 = .269. The lowRIF group demonstrated significantly poorer ability to recall Nrp items than the high-RIF group, F(1, 12) = 18.141, p < .001, η2 = .602, but the two groups recalled similar numbers of Rp– items, F(1, 12) = 0.251, p = .626.

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Effect of individual differences on the RIF effect One-way ANOVA with the factors group (high-, low-RIF) and tDCS (sham, active) revealed that the low-RIF group demonstrated a significantly smaller RIF effect than the high-RIF group after sham tDCS, F(1, 12) = 35.401, p < .001, but after active tDCS the low-RIF and high-RIF groups had similar RIF effects, F(1, 12) = 1.487, p = .246. To illustrate the impact of active tDCS on the RIF effect, at the level of the individual, the RIF effect (Nrp minus Rp–) was plotted for each individual at both the sham and active tDCS conditions. Figure 1 shows the RIF effect for the highRIF individuals on the sham and active tDCS conditions, and Figure 2 shows the RIF effect for the low-RIF individuals on the sham and active tDCS conditions. Examination of Figures 1 and 2 reveal strikingly different patterns of response to active tDCS for the high- and low-RIF groups. Specifically, every individual who demonstrated high sham levels of RIF showed reduced levels of RIF after undergoing active tDCS (Figure 1). In contrast, every individual who demonstrated low sham levels of RIF showed increased levels of RIF after undergoing active tDCS (Figure 2). To investigate this surprising pattern of performances, a repeated measures ANOVA of the RIF effect with the factors group (high-, low-RIF) and tDCS (active, sham) was conducted and revealed a significant interaction between stimulation type and group, F(1, 12) = 50.865, p < .001, η2 = .809. As there was a significant interaction, and the pattern of performances indicated that it was not meaningful to interpret the main effects, these analyses are not reported. Post hoc analyses of the interaction showed that the high-RIF group demonstrated a significant reduction in the size of

TABLE 3 RIF performance of the overall, high-RIF, and low-RIF groups at sham tDCS and active tDCS

Group Sham

Active

High-RIF Low-RIF Overall High-RIF Low-RIF Overall

Rp+ Mean (SD)

Rp – Mean (SD)

Nrp Mean (SD)

RIF Mean (SD)

92.43 80.29 86.36 91.00 81.14 86.07

41.57 45.57 43.57 51.14 42.29 46.71

69.71 47.57 58.64 57.86 55.71 56.79

28.14 2.00 15.07 6.71 13.43 10.07

(8.68) (12.58) (12.14) (10.70) (7.40) (10.21)

(14.77) (15.11) (14.51) (17.52) (9.11) (14.18)

(8.90) (10.49) (14.81) (12.30) (8.48) (10.21)

(9.26) (7.02) (15.70) (13.45) (5.60) (10.49)

Note. Performance expressed as percentage correct. RIF = retrieval-induced forgetting; tDCS = transcranial direct current stimulation; Rp+ = retrieval practice items; Rp– = unpracticed items categorically related to Rp+ items; Nrp = unpracticed items that are unrelated to Rp+ items. High and low-RIF (n = 7); overall (n = 14). Rp+ = recalled Rp+ ÷ total Rp+ × 100; Rp– = recalled Rp– ÷ total Rp– × 100; Nrp = recalled Nrp ÷ total Nrp × 100; RIF = Nrp – Rp–.

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ANDERSON ET AL. TABLE 4 Effect of regression to the mean on sham RIF performances of the high- and low-RIF groups


Figure 1. Size of retrieval-induced forgetting (RIF) effect for sham and active transcranial direct current stimulation (tDCS) conditions for each individual in the high-RIF group. Nrp = unpracticed items that are unrelated to Rp+ items; Rp+ = retrieval practice items; Rp– = unpracticed items categorically related to Rp+ items.

Figure 2. Size of retrieval-induced forgetting (RIF) effect for sham and active transcranial direct current stimulation (tDCS) conditions for each individual in the low-RIF group. Nrp = unpracticed items that are unrelated to Rp+ items; Rp+ = retrieval practice items; Rp– = unpracticed items categorically related to Rp+ items.

the RIF effect after active tDCS relative to sham, t(6) = 5.83, p = .001, η2 = .85, whereas the lowRIF group demonstrated a significant increase in RIF after active tDCS, t(6) = –4.12, p = .006, η2 = .74. To examine the possibility that order of tDCS presentation (i.e., whether sham tDCS was given at Time 1 vs. Time 2) affected RIF performances in the sham and active tDCS groups, a multivariate ANOVA with the factors group (high-, low-RIF), tDCS (active, sham), and presentation order (sham Time 1, sham Time 2) was conducted. Consistent with Figures 1 and 2, analyses revealed a significant main effect of baseline RIF group (high vs. low), F(2, 9) = 30.223, p < .001. Importantly, however, no significant main effect of order of presentation was revealed [sham tDCS Time 1 (X = 12.43, SD = 18.06) vs. Time 2 (X = 17.71, SD = 13.83) or active tDCS Time 1 (X = 8.71, SD = 13.84) vs. Time 2 (X = 11.43, SD = 6.53)], F(2, 9)

Group

Sham tDCS RIF Mean (SD)

Reg to mean RIF Mean (SD)

Active tDCS RIF Mean (SD)

High-RIF Low-RIF

28.14 (9.26) 2.00 (7.02)

24.41 (6.62) 5.74 (5.02)

6.71 (13.45) 13.43 (5.60)

Note. Values expressed as percentage correct. RIF = retrieval-induced forgetting; tDCS = transcranial direct current stimulation; Reg to mean = regression to the mean. RIF = Nrp – Rp–, where Nrp = unpracticed items that are unrelated to Rp+ items; Rp+ = retrieval practice items; Rp– = unpracticed items categorically related to Rp+ items.

= 0.252, p = .783, and there was no significant interaction between baseline group and order of presentation, F(2, 9) = 749, p = .500. To investigate whether the findings were a result of regression to the mean, the amount of regression between sham RIF values at the two assessment points was determined (r = –.714). A “regressed to the mean” value was calculated for each participant, representing the change to sham RIF that occurred purely as a result of regression to the mean. These data are presented in Table 4. Paired-samples t tests compared the groups’ RIF performances after active tDCS with the “regressed to the mean” RIF values. For both the high-RIF, t(6) = –4.640, p = .004, and low-RIF, t(6) = 3.328, p = .016, groups, RIF performances after active tDCS were significantly further from the regressed to the mean RIF performances. This indicated that, for both groups, active tDCS was significantly affecting RIF performances over and above the effect of regression to the mean. To investigate the assumption that RIF performance in the sham condition was associated with frontal lobe function, a Pearson’s correlation between reaction time on accurate responses to the 3-back task and RIF size after sham tDCS for the overall group was performed. Analysis revealed a significant negative correlation (r = –.61, p = .022) indicating that lower RIF performance after sham tDCS (see Table 3) was associated with slower responses on the 3-back task (X = 810.76 ms, SD = 117.12 ms). DISCUSSION The current study found that cathodal/active tDCS to the left DLPFC affects RIF performances. This directly supports the only previous study to investigate the effect of cathodal tDCS on RIF performance. Penolazzi and colleagues (Penolazzi,



Stramaccia, Braga, Mondini, & Galfano, 2014) demonstrated a clear effect of cathodal tDCS to the right DLPFC on RIF performances. Specifically, these authors demonstrated that cathodal tDCS caused a lack of RIF effect, whereas sham tDCS resulted in a strong RIF effect. These authors did not investigate the influence of individual differences in RIF (i.e., the influence of sham RIF performance on RIF performance after active RIF), but nevertheless provided clear evidence that active cathodal tDCS does cause a change in RIF performance relative to sham. It is noteworthy that in both the current study and in the Penolazzi et al. (2014) study, changes in both Nrp and Rp– contributed to the change in RIF effect after active tDCS (see Table 3). On the basis of inhibition theory it would seem logical to expect temporary frontal dysfunction (active tDCS) to only result in a change to Rp– performance, as Rp– is theoretically associated with inhibition of semantically related items in the RIF task, whereas Nrp is considered to be a control comparison for Rp– that is unaffected by inhibitory mechanisms (Storm & Levy, 2012). Although this aspect of the current finding is somewhat unexpected, it is not within the scope of this study to be able to explicate this finding. Given that it has been demonstrated in the only two studies to date that investigate the impact of active tDCS on RIF performance, however, it is worthy of future investigation. In addition to corroborating Penolazzi et al.’s (2014) finding that cathodal tDCS does affect RIF performance, the current study also demonstrated that level of RIF performance after sham tDCS influences the way in which RIF performances change after active tDCS. Specifically, and in contrast to expectations, this study showed that individuals with high versus low levels of RIF after sham tDCS had contrasting responses to a temporary reduction in neuronal firing of the left DLPFC. As would be predicted by current models of the RIF effect, individuals who demonstrated high levels of RIF after sham tDCS had a statistically significant reduction in RIF performance when left DLPFC function was reduced. In contrast, individuals who demonstrated little or no RIF effect after sham tDCS demonstrated significantly increased levels of RIF when experiencing a reduction in left DLPFC function. The current study found these significant results despite having a limited sample size. This was because, although the direction of the change in RIF effect differed between the groups, the effect size of the change in RIF performance was large for both groups—that is, η2 > .5 (high-RIF: η2 = .92; low-RIF: η2 = .77).

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This finding, that differences in the strength of RIF after sham stimulation cause variations in RIF performance after functional reduction of the left DLPFC, supports the notion that individual differences in normal RIF may be an important factor in understanding retrieval-induced forgetting performance after functional impairment of the left DLPFC. Previous research in the normal population has reported a positive linear relationship between left DLPFC function, as measured by fMRI, and the strength of the RIF effect (Wimber et al., 2009). One prediction that could be made from this type of research is that individuals who suffer left DLPFC impairment are likely to demonstrate a concomitant reduction in RIF performance. Interestingly, studies that have investigated the consequence of frontal impairment on RIF performance have been varied in their findings, with some studies finding no effect of frontal impairment on the RIF effect (Conway & Fthenaki, 2000) and others reporting the predicted reduction in RIF after frontal impairment (Storm & White, 2010). Storm and Levy (2012) argued that these variations in findings may be due to methodological differences in the RIF paradigms being used. The current findings suggest that another factor could also be contributing to the varied findings. Specifically, individuals who sustain some kind of functional insult to the left DLPFC might not show a linearly related reduction in RIF performance. Rather, RIF performance subsequent to a reduction in left DLPFC function might be influenced by individual differences in premorbid RIF abilities. That is, individuals with high premorbid RIF might demonstrate a reduction in RIF performance after left DLPFC functional impairment, but individuals with low or absent premorbid RIF might demonstrate an increase in RIF performance after left DLPFC functional impairment. This is the first study to suggest that frontal dysfunction might have a variable impact on RIF performance as a function of the individual’s premorbid levels of RIF. Given the somewhat unexpected nature of the current findings, some consideration should be given to possible explanations for the contrasting patterns of response to temporary left DLPFC dysfunction made by the high- and low-RIF groups in this study. As outlined above, active cathodal tDCS has been shown to result in a reduction in the likelihood of neurons firing in the area beneath the cathodal electrodes (Iyer et al., 2005; Nitsche & Fregni, 2007; Ukueberuwa & Wassermann, 2010). It is therefore straightforward to understand why a pattern of reduced RIF


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performance was seen after active tDCS in the high-RIF group. In line with previous research, which shows a positive linear relationship between left DLPFC function and the strength of the RIF effect (Wimber et al., 2009), a reduction in left DLPFC function would be expected to be associated with a reduction in the RIF effect. Indeed, this finding has recently been reported following cathodal tDCS to the right DLPFC (Penolazzi et al., 2014). Although the precise timing of the impact of the active tDCS on RIF performance (i.e., at initial item exposure and/or practice retrieval, etc.) cannot be delineated from this study, it does not affect the relevance of these findings. In both clinical populations and in the current study the DLPFC was affected prior to and throughout the RIF paradigm. Consequently, these findings are highly pertinent to patient groups with left dorsolateral prefrontal dysfunction. The explanation for an increase in RIF effect after left DLPFC dysfunction in individuals who demonstrated low levels of RIF after sham tDCS is less obvious. One possible reason is suggested by the work of Dockery and colleagues (Dockery, Hueckel-Weng, Birbaumer, & Plewnia, 2009) who investigated the effects of active tDCS on the left DLPFC in a problem solving task and argued that difficult tasks lead to excessive cortical activity during learning in this area. When this excessive cortical activity in the left DLPFC is dampened by cathodal tDCS, increased learning efficiency occurs. It is possible that the low-RIF group found the task more difficult than the high-RIF group, resulting in excessive left DLPFC activity for the low-RIF group during sham testing. The effect of tDCS-stimulated dampening of the excess cortical excitability in the left DLPFC would be improved learning efficiency, as indicated by an increased RIF performance after active tDCS for the low-RIF group. There is some support for the notion that the low-RIF group found the RIF task more difficult than the high-RIF group as the lowRIF group was significantly poorer at recalling Nrp items than the high-RIF group and were trending towards having significantly more difficulty recalling Rp+ items than the high-RIF group in the sham condition (p = .057). If increased learning efficiency does underlie the increase in RIF after active tDCS in the low-RIF group it is noteworthy that it was not evident in an improvement in Rp+ performance (see Table 3). Rather, on the basis of the current findings it seems that if an increase in learning efficiency did occur, it caused an improvement in learning the control Nrp items after active tDCS. Although we have outlined some support for the notion that changes

in learning efficiency may underlie the low-RIF results, this study cannot directly test the validity of this explanation. In particular, given that tDCS affects brain function at all stages of the RIF paradigm, any aspect of the RIF paradigm may have been affected. This means that other processes (e.g., item integration) may have been influenced by active tDCS. Of note, this same lack of clarity regarding the precise timing of the effect of cortical dysfunction on RIF performance is also relevant for clinical populations. In future studies it will be highly informative to investigate at what points in the RIF process the effect of active tDCS is playing an influential role. On the basis of the inhibitory account it would be predicted that it is reduction in inhibition during the retrieval practice phase that would be most influential on RIF performance. Investigating this will provide important insights into the relative contribution of different cognitive systems to the different stages of the RIF process and thereby improve our understanding of normal (and abnormal) RIF performances. That is, investigation of the mechanism underpinning individual differences in RIF performance will enhance our understanding of RIF itself. It could be argued that the pattern of findings was not due to the effects of active tDCS, but was rather due to “presentation order effects.” This is because the sequence of tDCS type differed between participants (i.e., 50% had sham then active tDCS, and 50% had active then sham tDCS). Examination of the method and results does not provide support for this idea, however. Both the high- and the low-RIF groups underwent the same order of counterbalanced stimulation, with 4 of the 7 participants in each group undergoing active stimulation at the first session and sham stimulation at the second session and the remaining 3 participants in each group receiving the opposite order of tDCS stimulation. Counterbalanced stimulation addresses many possible sources of bias in the results, but it does not compensate for the post hoc categorization method that was used to derive the high- and low-RIF groups. That is, half of the participants were categorized into high- versus low-RIF on the basis of their Time 1 assessment (T1) and half of the sample on the basis of their Time 2 assessment (T2). To determine whether this variation in time of undergoing sham tDCS affected the group differences in sham versus active RIF performances, it is necessary to investigate whether presentation order (i.e., whether sham was given at T1 vs. T2) influenced RIF performances. Analyses revealed that order of tDCS presentation did not independently affect RIF performance. There was also no interaction



between tDCS presentation order and RIF performance (high vs. low) at sham tDCS. This indicates that the fact that half of the participants were categorized into the high-RIF versus low-RIF groups at the first assessment, whereas half were categorized into these groups at the second assessment, did not affect RIF performances and also did not cause the change in RIF performance between the sham and active tDCS conditions. As the presentation order analyses are limited by small sample size, future researchers would benefit from using a larger sample size and an alternative methodological approach that incorporates a sham– sham group as well as a sham–active group to eliminate any possible influence of presentation order. It is also unlikely that the changes in RIF performance after active tDCS were due to a regression towards the mean. Regression to the mean in the current samples was calculated, and RIF performance after active tDCS was compared to the RIF value that was obtained by calculating “sham tDCS RIF + regression to the mean.” Analyses revealed that, for both the high- (p = .004) and the low-RIF (p = .016) groups, RIF performances after active tDCS were statistically significantly more extreme than the “sham + regression to the mean” RIF performances. That is, active RIF performances could not be accounted for by regression to the mean alone. There is also no evidence to suggest that there were higher levels of frontal lobe function in the low-RIF group, which may have resulted in their being relatively resistant to the inhibitory effects of active tDCS. Indeed, a significant correlation between performance on a working memory measure (the 3-back task) that relies on frontal lobe function (Tsuchida & Fellows, 2009) and sham tDCS RIF performance in the combined samples indicated the opposite. Lower RIF abilities after sham were significantly associated with poorer performance on the 3-back task, showing that in the sham condition individuals with smaller RIF effects demonstrated relatively reduced frontal lobe functioning compared to individuals with larger RIF effects. This finding is consistent with previous literature, which has demonstrated that amount of frontal activity is positively related to the size of the RIF effect (Johansson et al., 2007; Kuhl et al., 2007; Wimber et al., 2008). Previous researchers have demonstrated that clinical levels of depression and dysphoria are associated with impaired RIF performance (Bauml & Kuhbandner, 2007; Groome & Sterkaj, 2010). It could therefore be argued that lowered mood may have affected the current results. Given that

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participants were excluded if they had a psychiatric illness (including depression), and participants were randomly allocated to whether they received sham or active tDCS at the first or second assessment, it seems extremely unlikely that all high-RIF individuals had lowered mood during active tDCS but not during sham tDCS or that all low-RIF individuals had lowered mood during sham tDCS but not during active tDCS. Nevertheless, mood was not formally examined at each assessment in the current study, and so some effect of lowered mood cannot be categorically ruled out. Future research in this area should incorporate formal assessment of mood to address this issue. The groups had relatively wide ranges of age and education, and, given the small sample sizes, the lack of homogeneity within the groups is noteworthy. Of relevance, however, on both of these variables the low- and high-RIF groups were evenly matched, which suggests that any bias caused by the wide range of these variables would have affected both samples equally and would not have caused a systematic bias that influenced only one group. Certainly in future research of individual differences in RIF it would be preferable to have samples that were more homogeneous, but there is no evidence to suggest that these factors biased the results in the current study. A characteristic that did vary between the groups was English language status. Twenty-eight percent of the whole group spoke sufficiently good English to be educated in English at a tertiary level, but did not have English as their first language. Of these individuals, three participants were in the high-RIF group, and one participant was in the low-RIF group. Given that the RIF task was a verbal memory task, it is possible that English language status could have biased test performance for these participants. This is an unlikely explanation for the current pattern of results, however, as this design was a repeated measures design, such that each individual’s active tDCS RIF performance was compared to their sham RIF performance. Therefore, any effects of language status would have affected RIF performance in the same way after sham and after active tDCS. That is, there is no reason to believe that English language status would have affected an individual’s change in RIF performance between the sham and active tDCS conditions. It has been reported that the RIF effect does not show good test retest reliability unless precisely the same stimuli are used at both assessment points (Potts, Law, Golding, & Groome, 2012). It could therefore be argued that the current pattern of results may have been influenced by the fact that


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participants were exposed to different stimuli sets at sham and active tDCS trials. Participants in the current study were randomly allocated to the ordering of sham and active tDCS trials (i.e., whether sham vs. active tDCS was given at T1 vs. T2), and exposure to each stimulus set was counterbalanced across sessions. Therefore, a lack of test–retest reliability cannot explain the current pattern of findings as the low- and high-RIF groups experienced similar combinations of stimulus set order and order of tDCS. It could also be argued that participants may have undertaken the task in a different manner at the second session because they knew they were going to be tested on all items at the end of the task, despite being deceptively told this was not the case. Given that the same pattern of changes in RIF were observed across both tDCS conditions and stimulus sets for both groups, whether the session included deception (second session) or not (first session), it seems unlikely that this aspect of the methodology introduced a bias in the results. The current findings support the notion that premorbid levels of RIF performance might be an important factor when investigating the effect of frontal dysfunction on RIF performance. Although it is tempting to suggest that individuals with pathological lesions involving the left DLPFC would show similar patterns of performance to those shown in this study, it is important to note that the current findings occurred in the context of a process (active tDCS) that resulted in temporary dysfunction of the left DLPFC, without structural neuronal damage. This is not equivalent to pathological processes such as dementia, stroke, epilepsy, head injury, and so on, which have underlying structural as well as functional pathology causing neuronal dysfunction either permanently or for substantially longer than 60 minutes. Therefore, further work in patient populations should be conducted before the current findings can be considered equivalent to those from patient populations with left DLPFC dysfunction. In summary, this study is the first to show that levels of RIF performance in a sham condition affect changes in RIF performance after cathodal active tDCS to the left DLPFC in normal adults. Specifically, high levels of sham RIF were associated with significantly reduced RIF performance after active tDCS and low levels of sham RIF were associated with significantly increased levels of RIF after active tDCS. The changes in performance after active tDCS had large effect sizes for both the high- and the low-RIF groups, indicating that they were functionally as well as statistically significant for both groups. This study suggests

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