Working memory capacity is related to variations in the magnitude of an electrophysiological marker of recollection

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Working memory capacity is related to variations in the magnitude of an electrophysiological marker of recollection R.L. Elward⁎, E.L. Wilding Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales CF10 3AT, UK

A R T I C LE I N FO

AB S T R A C T

Article history:

The links between the resources available for cognitive control and the ability to recover and

Accepted 18 April 2010

maintain episodic content were investigated by contrasting an ERP index of recollection (the

Available online 25 April 2010

left-parietal ERP old/new effect) with a measure of working memory capacity (WMC). Participants were given the O-Span measure of WMC and completed a retrieval task in

Keywords:

which they had to make responses on one key to previously studied words (targets) and

Cognitive control

responses on a second key to words that were presented at retrieval on either one or two

Recollection

occasions (new words and non-targets, respectively). The size of the ERP index of

Working Memory Capacity (WMC)

recollection associated with correct responses to targets was correlated with WMC, a

Event-related potential (ERP)

finding consistent with the view that this ERP effect is linked to operations associated with

Memory retrieval

maintaining information on-line in service of task goals. In addition, the degree to which left-parietal ERP old/new effects for targets were larger than for non-targets increased as WMC increased. Larger left-parietal ERP old/new effects for targets than for non-targets have been interpreted as evidence of successful prioritisation of recollection of target information. The link with WMC reported here is consistent this view, in so far as WMC indexes the availability of resources that are necessary to exert cognitive control over memory retrieval. © 2010 Elsevier B.V. All rights reserved.

1.

Introduction

It is widely accepted that the ability to recover specific elements of information from memory from amongst many similar elements requires cognitive control operations (e.g. Burgess and Shallice, 1996; Schacter et al., 1998). It follows from this view that the degree to which control over what is recovered from memory can be exerted will vary with the availability of resources necessary to exert this control. This supposition is the basis for the work reported here, which comprises an investigation of the links between a marker of resource availability (working memory capacity: WMC) and

event-related potential (ERP) indices of one kind of successful episodic retrieval: recollection. Recollection is deemed to have occurred when contextual information associated with a prior event is recovered (Tulving, 1983). The left-parietal ERP old/new effect is linked to recollection and the strength of this link is impressive (for reviews, see Friedman and Johnson, 2000; Rugg and Allan, 2000). This ERP effect comprises a greater relative positivity for old than for new items that attract correct memory judgments. The effect is largest between 500 and 800 ms post-stimulus and has a posterior left-sided maximum, at least when verbal stimuli are employed (Wilding and Sharpe, 2003). A more specific function-

⁎ Corresponding author. Fax: + 44 2920874858. E-mail address: [email protected] (R.L. Elward). 0006-8993/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2010.04.040

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al interpretation of the left-parietal effect is that it reflects processes supporting the active maintenance of recollected information in working memory (Vilberg and Rugg, 2008). In particular, the effect may reflect certain operations of a system that Baddeley (2000) has termed the “episodic buffer”: “a limited capacity system that provides temporary storage of information held in a multimodal code, …” (Baddeley, 2000). This functional account of the left-parietal ERP old/new effect is supported by a series of careful demonstrations that its magnitude varies with the amount of contextual information that has been recovered (Vilberg et al., 2006; Vilberg and Rugg, 2009a,b; Wilding, 2000). Wilding (2000) demonstrated that the effect is larger when two (rather than one or no) forced-choice context judgments are made accurately (also see Wilding et al., 1995; Wilding and Rugg, 1996). Vilberg et al. (2006) demonstrated that the effect varied according to participant perceptions of the amount of contextual information that was recovered. In a follow-up study, they showed that the size of the effect varied with the amount of information participants could recall (Vilberg and Rugg, 2009a). These findings motivated the proposal that the leftparietal ERP old/new effect reflects the active (“on-line”) representation of recollected information (Vilberg and Rugg, 2008, 2009a,b). If this account is correct, then the magnitude of the leftparietal ERP old/new effect should vary according to the cognitive resources available to support such on-line representation. While this possibility has not been tested directly, there is some support for it. Dywan et al. (1998) asked participants to complete retrieval tasks requiring recollection under two conditions. In one, no other task was completed at the time of retrieval. In the other, participants completed the retrieval task and monitored concurrently a series of spoken numbers, indicating via key press when pre-specified sequences of numbers were heard. The left-parietal ERP old/ new effect was smaller in the dual- than in the single-task condition. This supports the functional interpretation of the left-parietal ERP old/new effect offered by Vilberg et al. (2006) in so far as: (i) the on-line maintenance of episodic information is a resource demanding process, and (ii) the resources available to support information representation were diminished in the dual-task condition because of the additional processing requirements during the test phase. This interpretation leads to the prediction that the size of the left-parietal ERP old/new effect will vary according to the availability of resources that are necessary to maintain information on-line. This prediction was tested here, by examining the correspondence between the magnitude of the left-parietal ERP old/new effect and an estimate of working memory capacity (WMC). A positive correlation between these behavioural and ERP measures would link strongly the leftparietal ERP old/new effect with processes that are involved in the active maintenance of episodic content. The retrieval task we employed was selected because previous studies have shown that it is one in which robust left-parietal ERP old/new effects can be elicited. The task comprised a version of the recognition memory exclusion task (Jacoby, 1991). In the most widely used version of this task, people make “old” responses to one class of previously presented items (these items are referred to as targets) and

reject items from a second class of studied items (non-targets) on the same key as unstudied (new) items. The two classes of studied items are distinguished by contextual elements, for example the encoding operations to which they were subjected (Herron and Rugg, 2003b), or the modalities in which they were presented at study (Jacoby, 1991; Jacoby and Kelley, 1992). In a slightly different version of the exclusion task (and the one employed in this study), there is only one class of items at study, but some test items are repeated during the test phase (e.g. Jennings and Jacoby, 1997). In this version, studied items are commonly designated as targets, and repeated test items as non-targets. A key assumption is that, for both versions of this task, recollection is necessary to distinguish between targets and non-targets (Jacoby, 1991), and in keeping with this assumption, reliable left-parietal ERP old/new effects are associated with targets in exclusion tasks (for the first report, see Wilding and Rugg, 1997). Consequently, if the left-parietal old/new effect indexes processes involved in the on-line maintenance of recovered information, the magnitude of the effect associated with targets will co-vary with a measure of the resources available to exert cognitive control. At a first pass, the same logic might appear to hold for the analysis of the left-parietal ERP old/new effects that are elicited by non-targets. In several studies, however, the left-parietal ERP old/new effect has been smaller for non-targets than for targets. Herron & Rugg (2003b) were the first to comment on this outcome in detail, suggesting that people might complete the exclusion task by prioritising recollection of targets over nontargets, and making the binary test judgment according to whether information about targets was or was not recollected. They argued that people will do this when the likelihood of recovering information about targets is high, because under these conditions this strategy will result in a high level of response accuracy. The effectiveness of this strategy declines, however, as the likelihood of recollecting information about targets decreases, and support for the role of target accuracy comes from the fact that the degree to which target left-parietal ERP old/new effects are larger than non-target effects has tracked the accuracy of target judgments in a number of studies where different materials and encoding conditions were used (Dzulkifli et al., 2006; Dzulkifli and Wilding, 2005; Herron and Rugg, 2003a; Wilding et al., 2005). An alternative account considered here, however, emphasises resource availability rather than target memorability. It is possible that, in more difficult test situations (when target accuracy is low), the greater demands imposed at the time of retrieval mean that there are fewer resources available to permit the prioritisation of recollection of targets over nontargets. The experiment described here permits a test of this account, because if it is correct, then individuals with greater resources available for cognitive control (as indexed by WMC) should be more likely to prioritise recollection of targets over non-targets than should individuals with fewer resources. The combination of the ERP exclusion task data and the WMC assessment therefore permits two predictions to be tested. First, the left-parietal ERP old/new effect elicited by targets will vary according to WMC. This outcome would be consistent with the view that the ERP effect reflects the operations associated with the episodic buffer (Vilberg and

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Rugg, 2008). Second, the degree to which parietal old/new effects elicited by non-targets are attenuated relative to target effects will also vary with WMC. This outcome would identify the resources available for cognitive control as an important factor for determining when (and to what degree) recollection of some kinds of memory content can be prioritised over other kinds.

2.

Results

2.1.

Behaviour

The range of O-span scores was 16–42, (mean = 26.3, sd = 6.4). In the following sections, the term “targets” refers to studied words, the term “non-targets” to repeated test words. Table 1 shows probabilities of correct responses and reaction times (RTs) for targets, non-targets and new items for all 36 participants. The likelihood of a correct response to a target was reliably greater than an incorrect response to a non-target (t(35) = 21.39, p < 0.001) and a new item (t(35) = 30.01, p < 0.001). A one-way ANOVA on RTs for correct responses revealed a main effect of stimulus type (F(2, 72) = 12.70, p < 0.01). Bonferronicorrected follow-up paired contrasts (corrected p = 0.017) revealed only that participants responded more quickly to new test words than to targets (t(35) = 4.70, p < 0.001).

2.2.

ERP analysis strategy

The analyses of the ERP data were restricted to parietal electrodes in the 500–800 ms epoch. These are the sites and the time period in which left-parietal ERP old/new effects are commonly observed and analysed. Support for this analysis decision is also provided by the spherical spline interpolated potential map in Fig. 1, which shows the focal left-lateralised parietal distribution of the target ERP old/new effect. The experiment predictions were tested via regression analyses. Left-parietal ERP old/new effect amplitudes for targets and for non-targets were calculated as the amplitude differences (averaged across sites P5, P3 and P1) between the ERPs elicited by correct responses to either targets or non-targets and those elicited by new test words. O-Span scores and the likelihood of a correct target response were used as predictors. For illustrative purposes, ERP target and non-target old/new effects for participants in the upper and lower tertiles of the WMC score distribution are shown in Fig. 2. Plots of WMC against the mean amplitudes of target and non-target leftparietal ERP old/new effects are shown in Fig. 3. For targets, O-span scores explained a significant proportion of the variance of the target old/new effects (R2 = 0.185, F(2, 33) = 3.76, p < 0.05). As O-span scores increased, so did the

Table 1 – Probabilities of correct responses to targets, non-targets and new test words, as well as reaction times (RTs) for these response categories. Standard deviations are given in brackets. Target p (Correct) RT

0.75 (0.13) 779 (157)

Non-Target 0.88 (0.11) 754 (158)

New 0.96 (0.05) 727 (156)

Fig. 1 – Topographic map showing the scalp potential distribution of the old/new effect associated with targets from 500 to 800 ms post-stimulus, scaled between the maxima (red, 5 μV) and minima (blue, 0 μV) depicted on the accompanying colour bar. The maps were computed using a spherical spline interpolation (Perrin et al., 1987; 1989).

magnitudes of the target old/new effects (β = 0.42, t = 2.66, p < 0.05). There was no reliable relationship between this target ERP effect and target accuracy (β = 0.10, t = 0.65). For nontargets, the regression analysis was not significant (R2 = 0.185, F(2, 33) = 2.15). While there was no reliable correlation with OSpan and the non-target old/new effect (β = 0.08, t = 0.50), the correlation between target accuracy and the non-target old/ new effect approached significance (β = 0.33, t = 2.0, p = 0.053). Final regression analyses were conducted on the difference measure obtained by subtracting the left-parietal old/new effects for non-targets from the effects for targets. O-Span and target accuracy were again entered as predictors. The regression was significant (R2 = 0.17, F(2, 33) = 3.37, p < 0.05). As Fig. 3 implies, there was a significant relationship between O-span score and this ERP difference measure (β = 0.41, t = 2.56, p < 0.05), but this relationship did not extend to target accuracy (β = 0.07, t = 0.44).

3.

Discussion

The experiment was designed to test two predictions, and the outcomes relevant to each are discussed in turn. The first prediction was generated by the proposal that the left-parietal ERP old/new effect indexes processes supporting the active maintenance of recollected information (Vilberg et al., 2006; Vilberg and Rugg, 2008), and may well reflect operations associated with the episodic buffer (Baddeley, 2000). To test this proposal, the magnitude of the left-parietal ERP old/new effect elicited by targets that attracted correct judgments was plotted against a measure of working memory capacity (WMC). There was a positive correlation between these measures. To our knowledge, the relationship between WMC and the left-parietal old/new effect has not been investigated directly before, and one possibility is that this correlation is a

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Fig. 2 – Grand average waveforms associated with correct responses to targets, non-targets and new items for participants falling into the upper and lower tertiles on the range of WMC scores (N = 12 per group). ERPs are shown for left- and right-parietal scalp sites (P5 and P6). direct reflection of differences in the availability of resources that enable task-relevant material to be maintained in service of task goals at the time of test. According to a competing explanation, however, the correlation is a reflection of the relationship between working memory capacity and the efficient deployment of memory encoding operations. In keeping with this notion, Oberauer & Lange (2009) suggested that people with high WMC are more efficient than participants with low WMC at binding context to content when information is encoded. EEG was not recorded at encoding in this experiment, so there is no electrophysiological data available that speaks to the issue of whether encoding operations differed according to WMC. Likewise, the absence of differences in response accuracies and reaction

times according to WMC provides no clear insights into the question of the locus at which WMC acts to influence the processes indexed by the left-parietal ERP old/new effect. One source of evidence that is germane to these competing accounts is the fact that the magnitudes of the left-parietal ERP old/new effects for non-targets attracting correct judgments were uncorrelated with WMC. This outcome indicates that an appeal to encoding efficiency to explain the correlation between target old/new effect amplitudes and WMC scores must include the context in which targets and non-targets were encoded: one would need to argue that (i) the context in which targets were encountered at study enabled efficient encoding operations (as indexed by WMC) to be mobilised, and (ii) this was not the case for the context in which non-targets were encountered. The relationship between the magnitudes of the target and non-target ERP old/new effects in this experiment is also relevant to the second prediction motivating this study1. This prediction was that participants with high WMC would be more likely to engage in a selective recollection strategy than would low WMC participants. Evidence for selective recollection (see Introduction) has been inferred from the extent to which the magnitudes of target left-parietal ERP old/new effects exceed those for non-targets. The assumption is that the size of this difference is an indicator of the degree to which recollection of targets has been prioritised over recollection of

1

Fig. 3 – Correlations between O-Span score and the magnitudes of left-parietal ERP old/new effects (averaged across P5, P3 and P1) for targets and for non-targets.

There is a probability imbalance across stimuli in this experiment: targets comprise a smaller proportion of test stimuli than do non-targets and new test words. ERPs are sensitive to response probability, and the stimulus category associated with the lower probability of occurrence is often associated with a midline maximum greater relative positivity over posterior scalp sites (Donchin, 1981). This observation raises the possibility that some of the parietally distributed differences reported here are a consequence of this probability imbalance. Critically, however, the distribution of stimulus-types is the same for all participants, so cannot explain changes in parietally distributed effects with WMC scores. Likewise, the absence of a link between response accuracy and the parietally distributed effects of interest argues against an appeal to subjective probability (Donchin & Coles, 1988) as an account for the differences we report.

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non-targets. Presumably this kind of prioritisation requires cognitive control, and this assumption leads to the link between WMC and ERP evidence for selective recollection, because WMC has been interpreted as an index of the availability of resources that are necessary to exert control. If this account is correct, then support for the second prediction stems from the correlation between WMC and the difference between the sizes of the target and non-target old/new effects. Larger parietal old/new effects for targets than non-targets have been reported in several papers (Czernochowski et al., 2005; Dywan et al., 1998; 2001; 2002; Dzulkifli et al., 2006; Dzulkifli and Wilding, 2005; Fraser et al., 2007; Herron and Rugg, 2003a,b; Herron and Wilding, 2005), with the preferred interpretation being that the different sizes of the effects are a consequence of a strategy of relying on recollection of information about targets to a greater degree than information about non-targets. Support for this argument has been adduced from the fact that the degree to which target effects exceed non-target effects increases as the likelihood of recollecting information about targets increases (Wilding and Herron, 2006). In this experiment, by contrast, WMC predicted the size of the differences between the target and non-target ERP old/new effects, but the accuracy of responses to targets did not. This finding suggests, therefore, that the adoption of a selective retrieval strategy is not a consequence of the likelihood of recollection. Rather, it is a strategy adopted–at least in exclusion tasks–when the resources necessary to implement it are available. This account accommodates the documented links between the accuracy of target responses and the degree to which nontargets are attenuated relative to targets, if it is assumed that (i) task difficulty increases as response accuracy decreases, and (ii) difficult tasks place greater demands on the resources necessary for exerting cognitive control (see Introduction). It can also accommodate the finding that, when young adults are asked to complete a second task alongside an exclusion task, amplitudes of parietal old/new effects are more similar for targets and nontargets than when there is no dual-task requirement (Dywan et al., 1998). It seems likely that the addition of a second cognitive task would impact negatively on working memory resources, thereby making control over recollection more difficult. In keeping with this account, older adults showed little evidence for control over recollection in the same exclusion task even when there was no dual-task requirement at retrieval (Dywan et al., 1998; 2002). WMC decreases with advancing age (Park et al., 1996), and some older adults may lack the resources necessary for successful engagement of some classes of controlled retrieval processes. The absence of a direct measure of WMC in the studies of Dywan et al. means, of course, that these observations can be made only tentatively, and the interpretation of their findings remains ambiguous in light of the fact that response accuracy decreased with age, and was also lower in the “dual” than the “single” task condition. Changes in response accuracy across age groups in exclusion tasks where ERPs were acquired have also been reported by two other research teams. In a study by Czernochowski et al. (2005), children were poorer at the target/ non-target discriminations than were adults, but the degree to which non-target old/new effects were attenuated appeared to be greater for the children, although this was not tested directly. de Chastelaine et al. (2007) also reported a target/non-target

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discrimination advantage for adults in comparison to children. Parietal old/new effects were larger for children, but the degree to which the non-target effects were attenuated was roughly equal for children and adults. If children have lower WMC than adults, these outcomes are a challenge to the WMC account for when non-target effects will be attenuated relative to target effects, although the reasons why the findings across these two studies do not converge also need to be addressed. The data points in the two studies with children were obtained in versions of the exclusion task where study items were encountered in different contexts, and items from one study context were denoted as targets at test. One reason for selecting the variant on this exclusion procedure that was used here (where non-targets were repeated test items) was because this variant was first introduced as one that is well suited for use with different populations and participants of different ages. Jennings & Jacoby (1997) argued that the use of the test repetitions provided a key benefit when comparing performance across different populations. They noted that by comparing response accuracy for non-targets at short repetition lags (for which most responses should be correct) it is possible to assess whether all participants understood the task instructions equally well. This was one reason for employing this task in this experiment, thereby providing baseline information about the links between ERP signatures of recollection and estimates of WMC in a young adult population, with a view to extending this research subsequently to populations for whom WMC and cognitive control may be compromised. It is also worth considering the possibility that control over recollection was not employed in this task, and that, for all participants, small non-target left-parietal ERP old/new effects are due simply to non-targets being encoded poorly. In this design, non-targets are first encountered as new (distracter) items in the test phase, with the majority of them attracting correct “new” responses. As a result, it is possible that the processing given these words is comparable to that associated with a relatively shallow encoding task, which might give rise to little or no recollection for these words when they are presented for a second time at test. There is no means of assessing this possibility within this experiment, but Fraser et al. (2007) reported large (∼7 µV) parietal old/new effects for repeated test words when they were designated as targets and studied words were designated as non-targets in a task that was otherwise highly similar to the one described here. In addition, Bridson et al. (2006) found that repeated test words were associated with robust parietal effects (∼5 µV) when “old” responses at test were to be made to both studied and repeated test words. Moreover, Yonelinas & Levy (2002) demonstrated that, at lags between presentation and re-presentation similar to those employed on this task, recollection made a marked contribution to test responses. In combination, these data points argue against the view that there is little evidence for strategic recollection in the ERP data reported here. A stronger within experiment demonstration, however, would stem from a replication of these findings under conditions where the categories of items associated with the target/non-target designation are varied across participants, or across study-test runs for the same participants. In both of these designs, an estimate of the memorability of items when encountered as non-targets would be available.

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Finally, under the assumption that the link between WMC and the control of recollection is a reasonable interpretation of the data reported here, the association between WMC and performance on tasks thought to require inhibition is worthy of comment. Conway & Engle (1994) presented a “Resource Model of Inhibition,” conceptualising inhibition as an active, resource-demanding process. In support of this, working memory capacity has been associated with performance in a number of paradigms assumed to require inhibition, including negative priming and dichotic listening tasks, flanker tasks, paired associates task, the anti-saccade task and the Brown– Peterson Stroop task (for review, see Redick et al., 2007). The possibility that inhibition is the mechanism responsible for the attenuation of non-target left-parietal ERP old/new effects relative to target effects in exclusion tasks has been considered elsewhere (Dzulkifli et al., 2006; Dzulkifli and Wilding, 2005; Herron and Rugg, 2003b), but the association with WMC described here is arguably the strongest evidence to date that can be considered consistent with this account. WMC also predicts performance on tasks for which inhibition is unlikely to contribute, however, and a goal in subsequent studies will be to narrow the range of competing explanations for the links that have been documented here.

4.

Experimental procedures

4.1.

Participants

These were 40 undergraduate psychology students (14 male) at Cardiff University. All were between 18 and 30 years of age, righthanded, spoke English as their first language, had normal or corrected to normal vision, reported that they did not have a diagnosis of dyslexia and were not taking psychoactive medication at the time of testing. Data from 4 participants (2 males) were excluded due to excessive artefacts in the EEG data. Approval for this study was given by the Ethics Committee in the School of Psychology at Cardiff University.

4.2.

Materials

4.2.1.

O-span

This task is used widely for measuring WMC (Turner and Engle, 1989). Participants are presented with compound stimuli such as “(3×2)+4=11? DOG.” They are instructed to read each equation aloud, indicate whether the solution is correct, and then read the word aloud. Participants are informed that they will be asked to recall the words at a later point in time. The number of compound stimuli that are presented before recall is required (the ‘fan’) increases from 2 to 5, and this procedure is repeated 3 times at each fan. One point is awarded for every word recalled in the correct serial position on trials where participants give the correct answer for the mathematical equation. The maximum possible score is 42.

4.2.2.

Exclusion task

412 words were selected from the MRC psycholinguistic database (www.psy.uwa.edu.au/MRCDatabase/uwa_mrc. htm). They had a frequency range of 1–7/million, and ranged from 4 to 9 letters in length. They were presented in white on a

black background on a computer monitor placed 1 m from participants. The images subtended up to 5˚ of visual angle horizontally and 0.6° vertically.

4.3.

Design

400 words were split into 16 equal groups (25 words per group). These were allocated randomly to four study-test cycles, each comprising four groups of words. These four were combined in each study-test cycle as follows. One of the four groups in each section was designated as the study word list. All four groups in each section were employed at test, where each item was presented once, with the exception of one group (not the one containing study list words) for which words were presented twice at test, with an average lag of 8 intervening words (range = 7–9) between first and second presentation. Thus each test list in each study-test cycle comprised 125 stimulus presentations: 25 studied words, and 75 words presented at test for the first time, of which 25 were re-presented. One complete task list comprised four study-test cycles, and the word groups designated as study words, new words and repeated test words were rotated, resulting in the development of three complete task lists. A further three task lists were generated by changing the lag between presentation and re-presentation of test words from an average of 8 to an average of 16 (range = 15–17). The task thus comprised short and long lag versions. For the long lag lists, an extra 3 filler items were placed in each test sequence towards the end of the lists to ensure that first and second presentations of test items were distributed relatively evenly throughout the test lists. Thus for these lists, 25 words were shown at study and 103 words (128 stimulus presentations) were shown at test within each study-test cycle. The lag manipulation was introduced with the intention of measuring changes in ERP effects of interest in the same task as response accuracy declined. There were, however, no behavioural and concomitant ERP differences according to the lag between presentation and re-presentation of test words. All behavioural and ERP data reported are collapsed across lag.

4.4.

Procedure

4.4.1.

Study phase

Participants were told that 25 words would be presented one at a time on the screen and that their memories for these words would be assessed subsequently. Participants were asked to read each word aloud. Each study trial started with an asterisk presented at fixation (500 ms duration), which was removed from the screen 100 ms prior to presentation of a study word (1000 ms duration). The next trial started 1000 ms later.

4.4.2.

Test phase

Participants made a binary response on each test trial, pressing one key for words they had read aloud in the study phase and another key for all other words. They were informed before testing that some new (unstudied) test words would repeat, but to always press the “new” key for those words. An equal number of participants (N=18) completed “short” and “long” lag lists. The hand with which responses to each type of stimulus were required was counterbalanced across participants and lists.

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There was a short (self-paced) break between each study-test cycle.

4.4.3.

Electroencephalogram (EEG)

This was recorded from 25 silver/silver chloride electrodes housed in an elasticated cap. The sites were located at midline (Fz, Cz, Pz) as well as left and right hemisphere locations (FP1/ FP2, F7/F8, F5/F6, F3/F4, T3/T4, C5/C6, C3/C4, T5/T6, P5/P6, P3/ P4, O1/O2: Jasper, 1958). Additional electrodes were placed on the left and right mastoid processes. Vertical and horizontal EOG were recorded bipolarly from electrodes placed above and below the right eye, and on the outer canthi. EEG was recorded continuously (range 0.03–40 Hz; sampling rate 200 Hz) with Fz as the reference electrode and was re-referenced off-line to the average signal at the left and right mastoids. The Fz data were reinstated. Data were epoched off-line into 1280 ms (256 point) epochs, with a 100-ms pre-stimulus baseline, relative to which all mean amplitude measures were computed. A 7point smoothing filter (∼ 22 Hz) was applied prior to analysis. Trials containing large EOG artefact and those containing A/D saturation or baseline drift exceeding ±80 µV were rejected. Other EOG blink artefacts were corrected using a linear regression estimate (Semlitsch et al., 1986).

Acknowledgments This research was supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC) in the form of a research studentship (RLE) and a project grant (ELW). Both researchers were also supported by the Wales Institute of Cognitive Neuroscience (WICN). REFERENCES

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