Developmental Psychology 2014, Vol. 50, No. 4, 1060 –1072

© 2013 American Psychological Association 0012-1649/14/$12.00 DOI: 10.1037/a0035231

Developmental Change in Proactive Interference Across the Life Span: Evidence From Two Working Memory Tasks Sandra V. Loosli

Benjamin Rahm and Josef M. Unterrainer

University Medical Center Freiburg, Freiburg, Germany, and University of Freiburg

University Medical Center Mainz, Mainz, Germany

Cornelius Weiller and Christoph P. Kaller This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

University Medical Center Freiburg, Freiburg, Germany, and University of Freiburg Working memory (WM) as the ability to temporarily maintain and manipulate various kinds of information is known to be affected by proactive interference (PI) from previously relevant contents, but studies on developmental changes in the susceptibility to PI are scarce. In the present study, we investigated life span development of item-specific PI. To this end, 92 individuals between the ages of 8 and 74 years completed a recent-probes task and an n-back task that both composed experimental manipulations of PI. Regarding global WM development, young adults had higher WM performance than children and older adults in both tasks. Significant PI ⫻ Age interactions revealed that susceptibility to PI changed over the life span in both tasks, whereas the developmental course of PI differed between the tasks: Children committed more PI-related errors than young adults in the recent-probes task but showed marginally less PI in the n-back task. Regarding reaction time costs, children did not differ from adults in the recent-probes task and were less affected than adults in the n-back. Older adults showed more PI-related errors than young adults in both tasks. Therefore, as expected, item-specific PI changed over the life span with the young adults being less susceptible to PI than children and older adults. The diverging developmental effects of PI across both tasks, especially in the children, are supposed to reflect different causes for the difficulties regarding resisting PI in children and older adults. These might concern differently developed underlying cognitive processes such as inhibition or recollection, or different responses to task demands across both tasks. Keywords: working memory, proactive interference, inhibition, cognitive development, life span Supplemental materials: http://dx.doi.org/10.1037/a0035231.supp

WM refers to the ability to temporarily maintain and manipulate various kinds of information (Baddeley, 1997). A current theoretical approach even defines WM as executive attention, which maintains memory representations in a highly active state in the presence of interference (Kane & Engle, 2002). In this respect, it was shown that PI may contribute to individual differences in WM capacity (e.g., Jonides & Nee, 2006; Kail, 2002; May, Hasher, & Kane, 1999) and that WM capacity may reciprocally also influence resistance to PI (Kane & Engle, 2000; Robert, Borella, Fagot, Lecerf, & de Ribaupierre, 2009; Rosen & Engle, 1998). Two types of PI can be differentiated: Item-nonspecific PI refers to interference from accumulating information that has been remembered in the course of the task but is no longer relevant in the current trial (e.g., in complex span tasks or the Brown-Peterson task; May et al., 1999; Wickens, 1970). In contrast, item-specific PI refers to interference induced by a probe of the current trial that has been a target in one of the immediately preceding trials but is not in the present trial (Postle et al., 2004), and thus reflects interference from a specific stimulus. In these instances, PI results in lower recall accuracy and longer reaction times for probe items (Jonides & Nee, 2006). In past studies, such “recent” trials regarding item-specific PI were mainly examined with a modified version of the Sternberg task or recent-probes task (Monsell, 1978;

In everyday life, it is important to distinguish currently relevant information from previous memory contents. For instance a waitress has to keep various orders in memory if she is taking orders from several tables consecutively without making notes. She must not confuse previous similar beverage orders with later ones. If she is mistaking a beverage from the second table for one of the first table, this may have occurred due to an impaired recall of the appropriate item due to proactive interference (PI) from previously relevant information in working memory (WM; Postle, Brush, & Nick, 2004).

This article was published Online First December 2, 2013. Sandra V. Loosli, Department of Neurology, University Medical Center Freiburg, and Freiburg Brain Imaging Center, University of Freiburg, Freiburg, Germany; Benjamin Rahm and Josef M. Unterrainer, Department of Medical Psychology and Medical Sociology, University Medical Center Mainz, Mainz, Germany; Cornelius Weiller and Christoph P. Kaller, Department of Neurology, University Medical Center Freiburg, and Freiburg Brain Imaging Center, University of Freiburg, Freiburg, Germany. Correspondence concerning this article should be addressed to Sandra V. Loosli, Department of Neurology, University Medical Center, Breisacher Strasse 64, 79106 Freiburg, Germany. E-mail: [email protected] 1060

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DEVELOPMENTAL CHANGE IN PROACTIVE INTERFERENCE

Sternberg, 1966; see Jonides & Nee, 2006, for a review) but also with n-back tasks including lure items (e.g., Gray, Chabris, & Braver, 2003; Schmiedek, Li, & Lindenberger, 2009). In sum, item-nonspecific PI may arise from any information presented previously and therefore is hard to discriminate from other processes evolving across a testing session such as fatigue, task practice, and the rise and fall of sustained attention, among others. This may be especially pertinent when comparing two or more groups that may differ with respect to these influences (Bowles & Salthouse, 2003). In contrast, item-specific PI refers specifically to one stimulus of one of the directly preceding trials. When PI is manipulated from trial to trial, PI and control trials are equally distributed from the beginning to the end of the task. In consequence, the estimate of PI is influenced to a lesser degree by other factors such as fatigue or practice effects. Therefore, item-specific PI seems more suitable for studying the underlying cognitive processes. From a developmental perspective, performance in WM tasks with additional executive demands reaches adult level later than performance in pure maintenance tasks (Gathercole, 1999). This has been shown by comparing performance in WM tasks with complex spans, which require simultaneous storage and processing (Daneman & Carpenter, 1980), to performance in WM tasks with simple spans, which require repeating digits or words. Moreover, there is evidence that age differences between young and old adults are larger in complex WM spans than in tasks that require storage only (Logie & Maylor, 2009; but see also Rose, Myerson, Sommers, & Hale, 2009), which suggests that in older adults, performance decreases more quickly in tasks with more executive demands compared with storage-only tasks. Likewise, susceptibility to item-nonspecific PI has been shown to be higher in children (Kail, 2002; Robert et al., 2009) and older adults (e.g., May et al., 1999) compared with younger adults. Most evidence regarding behavioral or neural correlates of itemspecific PI is based on studies with young adults, with only a few addressing item-specific PI at older age. Thus, while it is well established that WM capacity and resistance to item-nonspecific PI increases during childhood and adolescence until young adulthood and decreases thereafter with progressing age (e.g., Jenkins, Myerson, Hale, & Fry, 1999), relatively little is known about the developmental changes in the resistance to item-specific PI across the life span. As with item-nonspecific PI, also resistance to item-specific PI can be regarded as an executive control process (Friedman & Miyake, 2004). Therefore, like other cognitive control processes, it may be expected to be also less effective in children or older adults, compared with younger adults (Casey, Tottenham & Fossella, 2002; Craik & Bialystok, 2006). In this respect, older adults were found to be more susceptible to item-specific PI than younger adults, but it remains unclear whether the costs of PI affect reaction times (RT), accuracy, or both (cf. Jonides et al., 2000; McCabe & Hartman, 2008; Thompson-Schill et al., 2002). Furthermore, to our knowledge, item-specific PI was never studied in children before. Therefore, the first aim of the present study was to investigate the development of resistance to item-specific PI in WM across the life span by assessing four different age groups: younger and older children as well as younger and older adults. A recent-probes task and an n-back task were chosen as experimental WM tasks, as both tasks allow studying developmental changes in global WM as well

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as in item-specific PI. The recent-probes task was chosen as it is the most frequently used measure of item-specific PI within WM. In contrast, the n-back is one of the most popular tasks in the WM neuroimaging literature but has seldom been used to assess PI. By using these two different tasks, we intended to investigate whether resistance to PI develops in a uniform manner, or whether it develops task-dependently. In both tasks, PI was calculated as difference between recent and nonrecent negative trials (see Method section). We hypothesized that compared with young adults, both children and old adults (a) would have lower global WM performance and (b) would be more susceptible to PI in both tasks, which would result in higher RTs and more errors in trials with versus without interference. More specifically, for the developmental course across different stages of childhood, we expected younger children to show decreased WM performance and more PI than older children. A second aim was to directly compare resistance to PI as well as its development between the two different WM tasks. Although both tasks are frequently applied, for instance, in functional neuroimaging experiments on the neural foundations of WM (Wager & Smith, 2003), the n-back is less often applied in behavioral studies in developmental contexts. In consequence, across-task comparisons were of interest here not only for PI effects but also for general WM performance. In most studies regarding PI, only one task is used, whereas across-studies comparisons of the PI effects in different WM paradigms are often hampered by methodical differences. It hence remains to be clarified whether manipulations of PI in different WM tasks involve the same cognitive processes, as the recent-probes task is a classical short-term memory task, whereas the n-back involves additional executive processes (Kiss, Watter, Heisz, & Shedden, 2007). In a recent study, within-subject comparisons of performance in a recent-probes task and a directed-forgetting task in an adult sample resulted only in a marginally significant relationship between PI-related errors and RT costs across both tasks (Nee, Jonides, & Berman, 2007). Furthermore, a divergence of PI-related cognitive processes across different WM tasks seems also indicated from the neuroimaging literature as PI-related brain activation patterns appear to differ considerably. In the recent-probes task, resistance to PI is consistently associated with activations in the prefrontal cortex (PFC), especially within the left inferior frontal gyrus (IFG; e.g., Badre & Wagner, 2005; Jonides, Smith, Marshuetz, Koeppe, & Reuter-Lorenz, 1998) but also within other (pre-)frontal regions (e.g., Badre & Wagner, 2005; Bunge, Ochsner, Desmond, Glover, & Gabrieli, 2001; Mecklinger, Weber, Gunter, & Engle, 2003), the occipital (Nee et al., 2007) and parietal (e.g., Mecklinger et al., 2003) lobes. Considering the n-back task, effects of PI are mainly associated with regions in the bilateral dorsolateral PFC (middle frontal gyrus) and parietal cortex (inferior parietal lobe) (Burgess, Gray, Conway, & Braver, 2011), and lure accuracy has been found to be positively associated with activity in the right middle frontal gyrus (Jacobs & D’Esposito, 2011). Thus, while most of the studies regarding the recent-probes task found activations in the left IFG, PI-related brain activations in the n-back task seem to appear in more dorsal PFC regions. But the different findings from neuroimaging studies have to be compared with caution, as the individual studies vary in many aspects (e.g., in the implementation of PI or in stimulus material). Regarding the latter, PI effects

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might be independent of content, although this issue has not been resolved until now and is discussed controversially (Jonides & Nee, 2006). Taken together, although the n-back and the recent-probes tasks do not seem to be associated with exactly the same brain regions and are not capturing exactly the same underlying cognitive processes, we hypothesized that both interference effects should be positively related, as both tasks are believed to measure itemspecific PI within WM.

screening tests for dementia, and results were considered normal in all participants. Older participants were also screened for depression with the Beck Depression Inventory (BDI–II; Beck et al., 2006) and the short form of the Geriatric Depression Scale (GDS; Yesavage, & Sheikh, 1986). All included participants scored between 1 and 15 in the BDI–II (M ⫽ 6.2, SD ⫽ 4.4) and between 0 and 6 in the GDS (M ⫽ 1.4, SD ⫽ 1.7).

Method

Recent-probes task. In the recent-probes task (cf. Monsell, 1978), stimuli consisted of 12 animal pictures that could be named with one-syllable words in German. Pictures (Snodgrass & Vanderwart, 1980) constituted noncolored line drawings of comparable complexity, familiarity, and name agreement (Cycowicz, Friedman, Rothstein, & Snodgrass, 1997). In each trial, four pictures were displayed as a target for 2,000 ms in a 2 ⫻ 2 array; then, after a delay of 2,400 ms during which only a fixation cross was shown, a single animal was presented centrally as a probe for 1,800 ms (see Figure 1, Panel A). If the probe was part of the target set in the present trial, the left button of a three-button computer mouse had to be pressed (positive trial), and if it was not part of the present target set, the middle button had to be pressed (negative trial). Participants were instructed to answer as quickly and accurately as possible. There was a time limit for responding (i.e., a response was only possible as long as the probe was presented). The mean duration of intertrial intervals, in which again a fixation cross was shown, was 1,800 ms and varied between 1,000 and 2,600 ms. Stimuli were presented using Presentation software (Version 12.2; Neurobehavioral Systems). The task constituted a 2 ⫻ 2 design: the factor recency reflected whether the probe was part of the target set in the previous trial (recent) or not (nonrecent); the factor probe type indicated the kind of response that should be given (positive or negative; i.e., whether the probe matched one of the items in the target set in the current trial or not). Notably, only recent negative trials elicit PI (Badre & Wagner, 2005). Both factors were pseudo-randomized, and each combination of conditions represented 25% of all trials. As in Badre and Wagner (2005), in each target set, two animals from the previous target set were repeated in order to prevent a confound between PI and familiarity. Participants were not aware of the manipulation of the factor recency. The whole test comprised 64 trials. Accuracy and RTs were recorded. To assess participants’ global WM performance, we used only nonrecent trials. Measures of sensitivity (d=) and response bias (c) were calculated, as the proportion of correct responses can be biased by tendencies toward “yes” or “no” answers. A higher value in d= reflects a better ability to discriminate between positive and negative trials. Response bias c reflects a participant’s tendency to respond that a given stimulus is positive or negative. A positive value reflects a tendency to press “no” (conservative bias), whereas a negative value reflects a tendency towards “yes” (liberal bias; Stanislaw & Todorov, 1999). PI was calculated as the difference between recent negative and nonrecent negative trials. N-back task. To increase similarity, we used identical stimulus material across both tasks. The animal pictures were presented serially every 3,000 ms, one at a time, for 500 ms each. The time window for the response was hence 2,500 ms at maximum and, therefore, limited, as in the recent-probes task. Individual picture

Participants A total of 106 individuals aged 8 –75 years were included in the study. They were recruited from four age distributions: forty-nine children between 8.0 and 10.0 years (n ⫽ 27) and between 11.9 and 14.2 years (n ⫽ 22), 37 young adults between 19.0 and 31.1 years, and 20 older adults between 66.4 and 75.8 years. Note that the youngest age group’s lower margin of 8 years has been determined in pilot studies. Furthermore, the inclusion of a second children group at the early adolescence age has been chosen as performance in WM tasks with executive components has not reached adultlike performance in this age range already (Gathercole, 1999). All participants were right-handed and had normal or corrected-to-normal vision. Exclusion criteria on subject level were (a) psychiatric, neurological, or developmental disorders, (b) an incomplete data set due to technical or motivational reasons, or (c) extreme outliers in the data. Adult participants or a parent of each participating child gave written informed consent prior to participation. Children agreed orally to take part in the study after the procedure was explained. The study protocol was approved by the local ethics committee. All participants were paid 30 euro for participation. Following data acquisition, 14 participants were excluded (13.1% of all participants): One child of the youngest age group was excluded due to suspicion of neurological abnormalities; one older adult due to an increased overall score in the Beck Depression Inventory (Beck, Steer, & Brown, 2006); five children, four young adults, and two older adults due to incomplete data sets because of technical or motivational reasons; and one child of the older age group due to low performance. Taken together, the final sample consisted of 92 participants: 22 younger children (8.0 –10.0 years, M ⫽ 9.0, SD ⫽ 0.6; 12 girls), 20 older children (11.9 –14.2 years, M ⫽ 13.1, SD ⫽ 0.7; 10 girls), 33 young adults (19.0 –31.1 years, M ⫽ 23.7, SD ⫽ 3.2; 14 women), and 17 older adults (66.4 –74.3 years, M ⫽ 69.9, SD ⫽ 2.7; 10 women). Parents completed a questionnaire on the educational background of the children as well as on possible psychiatric, neurological, or developmental disorders. All included children were considered as normal in all of these aspects. In the adult samples, a German vocabulary test (Mehrfachwahl Wortschatz Test [MWT], Versions A and B; Lehrl, 1999; Lehrl, Merz, Burkhard & Fischer, 1991) was administered to ensure a minimum average level of crystallized intelligence. All scores were within normal range or above average (25th–100th percentile). In the oldest age group, the Mini-Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975; all ⱖ 28) and the Clock Drawing Test (CDT; Shulman, Shedletsky, & Silver, 1986) were applied as

Experimental Tasks and Design

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Figure 1. A recent-probes task and an n-back task were used to elicit item-specific proactive interference (PI). In the recent-probes task (Panel A), the participant had to encode four animals (target set), to hold them in mind, and, when a probe with a single animal appeared, to decide whether this animal was part of the four animals shown before (left mouse button) or not (right mouse button). The recent-probes task comprised four conditions: recent positive, recent negative (PI), nonrecent positive, and nonrecent negative. In the n-back task (Panel B), the participant had to press the left mouse button if the present animal was the same as two positions before; otherwise, the right mouse button had to be pressed. The n-back task comprised three conditions: targets, lures (PI), and nones.

presentations constituted separate trials. The participant’s task was to indicate whether the animal in the current trial matched the one presented two trials before. If this was the case, the left button of a three-button computer mouse had to be pressed (positive); otherwise, the middle button had to be pressed (negative). Participants were instructed to answer as quickly and accurately as possible. Targets replicated the same stimuli as two trials before and re-

quired a “yes” answer. Lure trials were stimuli already presented three trials before, thus elicited PI and required a “no” answer. In trials with nones, the animal was presented longer than six trials before, hence requiring a “no” answer (see Figure 1, Panel B). Participants were not aware of lure trials. In total, the task consisted of 149 trials with 30 targets (20%) and 30 lures (20%). Stimuli were presented with Presentation software, and accuracy

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and RTs were recorded. Only trials without interference (i.e., targets and nones) were used to calculate global WM performance, d= and c, as in the recent-probes task. PI was calculated as the difference between lures and nones.

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General Procedure Participants attended two sessions that were approximately 1 week apart. In Session 1, the recent-probes task was administered as described earlier. Subsequently, additional runs of this task were accomplished with functional magnetic resonance imaging. These data will be reported elsewhere. In Session 2, the n-back task as well as other tasks not reported here were administered. Additionally, older adults were given the MMSE, the CDT, the GDS and the BDI in Session 2. Session 1 lasted 90 –120 min; Session 2 lasted 60 –90 min.

Data and Outlier Analysis For both tasks, sensitivity (d=) and bias (c) measures were calculated according to Stanislaw and Todorov (1999). Based on d=, outliers were identified at the subject level relative to the respective age group and excluded from the study. For each group, quartiles (Q) and interquartile ranges (IQR) were calculated for d= in both tasks. Participants with a d= less than Q1 ⫺ 1.5 ⫻ IQR in their respective age group were excluded (Tukey, 1977). As a result, one child of the older age group was excluded due to low performance in the n-back. The first two trials of the n-back task were discarded from RT and accuracy analyses because no picture appeared two positions back. In the recent-probes task, trials in which participants answered before stimulus presentation were excluded from data analysis. Only correct trials were included for RT data. To control for outliers, we z-transformed RTs for single trials. The reference for this transformation was based on age group, trial condition, and, for the recent-probes task, also the spatial position of the probe in the recent target set (i.e. one trial back). Trials with z ⬎ 3 or ⬍ ⫺3 were excluded from further processing (1.5% of all trials in the recent-probes task and 1.8% of the trials in the n-back task). Remaining trials were then aggregated, and the median RT and mean accuracy were calculated for each condition and subject. In the recent-probes task, first, a median RT or mean accuracy score per spatial position in the recent negative and recent positive trials was calculated. A mean value was then calculated out of these four position values and was then further processed with the other data. This procedure was chosen to adjust for effects of possibly disproportionally distributed spatial positions of targets in the recent trials. Data were analyzed with SPSS Statistics, Version 20.0. All statistical tests were based on a significance level of ␣ ⫽ .05. Developmental effects were calculated using univariate analyses of variance (ANOVA). Greenhouse–Geisser corrections were used where appropriate, and ␩p2 was calculated as a measure of effect size. Developmental effects were analyzed in two steps: First, an ANOVA with three age groups (children, younger and older adults) was conducted. Planned a priori contrasts were then used to investigate the developmental effects of WM and PI. In detail, a

reversed U-shaped pattern was hypothesized concerning accuracy measures, with the younger adults performing better than children or older adults. The reverse pattern was expected for RT measures. In a second step, the two groups of younger and older children were compared with additional ANOVAs or t tests to investigate more specific developmental effects. Here, it was expected that older children were less susceptible to PI than younger children. Finally, to compare global WM performance and PI measures of both tasks, we calculated bivariate correlation analyses for each age group separately.

Results Results are reported in three sections: First, we address developmental effects of global WM in both tasks. Second, results concerning susceptibility to PI are reported and finally are followed by correlation analyses to investigate the relationship between performance in both tasks. An overview on descriptive measures is provided in Table 1.

Development of WM Performance The analyses in this section include only nonrecent trials. ANOVAs including age group (children, younger adults, older adults) as between-subjects factor were conducted. Recent-probes. ANOVAs revealed significant effects of age group on sensitivity measure d=, F(2, 91) ⫽ 14.81, p ⬍ .001, ␩p2 ⫽ .25; see Figure 2, Panel A. Planned pairwise contrasts showed that children and older adults were less able to discriminate between both probe types than younger adults (p ⬍ .01 for both contrasts). Subsequent t tests revealed that younger children were less accurate than older children, t(40) ⫽ ⫺6.28, p ⬍ .001. There were no effects of age group on bias measure c, F(2, 91) ⫽ 0.10, p ⫽ .91. ␩p2 ⫽ .00. However, younger children showed marginally stronger bias than older children, t(40) ⫽ 1.39, p ⫽ .084. N-back. ANOVAs revealed effects of age group on sensitivity d=, F(2, 91) ⫽ 37.95, p ⬍ .001, ␩p2 ⫽ .46, and on response bias c, F(2, 91) ⫽ 4.06, p ⬍ .05, ␩p2 ⫽ .08 (see Figure 2). Planned pairwise contrasts showed that children and older adults were less able to discriminate between both probe types than young adults (p ⬍ .01 for both contrasts). Subsequent t tests revealed that younger children were less accurate than older children, t(40) ⫽ ⫺4.09, p ⬍ .001. Response bias c decreased linearly with progressing age (see Figure 2, Panel B) and was marginally lower in older adults than in younger adults (p ⫽ .057) and marginally lower in younger adults than in children (p ⫽ .069). Subsequent t tests showed no significant difference in response bias regarding both groups of children, t(40) ⫽ 0.63, p ⫽ .268. In sum, sensitivity followed an inverted U-shaped pattern in both tasks (see Figure 2, Panel A). Values of c were all in the positive range, thus indicating a conservative response pattern (i.e., a tendency to press “no”), especially for the children in the n-back task (see Figure 2, Panel B). Additional analyses regarding the development of global WM performance (i.e., effects of probe type as well as interactions between probe type and age group in proportion of corrects and RT data) can be found in the online supplementary material.

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Table 1 Proportion of Corrects, Reaction Times and Sensitivity Measures in the Recent-Probes Task and the N-Back Task for Each Age Group Younger children 8 –9 years

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Task/measure Recent probes Accuracy (% correct) Recent positive Nonrecent positive Recent negative Nonrecent negative d= c Reaction time (ms) Recent positive Nonrecent positive Recent negative Nonrecent negative N-back Accuracy (% correct) Targets Lures Nones d= c Reaction time (ms) Targets Lures Nones

Mean

64.9 58.0 70.7 83.1 1.27 0.41 1124 1151 1216 1135 37.3 77.9 84.7 0.93 0.85 835 678 664

SD

16.4 17.1 18.2 11.4 0.59 0.37 185 193 213 196 20.0 13.2 11.8 0.76 0.48 306 242 202

Older children 12–13 year Mean

78.2 80.0 76.6 92.0 2.33 0.27 950 919 1003 947 57.0 77.7 91.3 1.90 0.77 661 724 654

Younger adults 19 –31 years

SD

Mean

SD

13.6 10.6 18.8 7.0 0.50 0.30

85.9 81.6 90.3 96.0 2.63 0.34

14.8 12.1 8.0 5.6 0.59 0.24

152 158 154 154 19.4 13.7 7.7 0.78 0.35 224 320 241

783 790 887 789 76.8 82.6 97.3 3.03 0.69 625 698 590

125 160 150 129 15.7 11.0 3.4 0.71 0.31 170 195 121

Older adults 66 –75 years Mean

78.2 75.6 76.8 89.7 2.08 0.30 1124 1067 1328 1171 66.3 50.4 87.6 1.90 0.50 801 861 792

SD

12.1 12.1 13.0 10.0 0.58 0.32 176 214 192 198 11.8 18.9 11.0 0.73 0.40 183 234 152

Note. d= ⫽ sensitivity; c ⫽ response bias; d= and c ⫽ only nonrecent trials and trials without proactive interference.

Development of Resistance to Proactive Interference In the following analyses on susceptibility to PI, only negative trials were considered. Thus, recent against nonrecent negatives were compared in the recent-probes task, and lures versus nones in the n-back task. First, four t tests for dependent samples assessed whether PI effects existed in each of the four age groups. There were significant performance decrements in interference relative to noninterference negative trials in both tasks for accuracy and RT in each individual age group (p ⬍ .05, one-tailed), with one exception: In the younger children, the PI effect considering RT was nonsignificant in the n-back task (p ⫽ .160). Development of the performance in the negative trials is displayed in Figure 3 and development of PI-scores is displayed in Figure 4. Accuracy. Recent-probes. A repeated-measurements ANOVA with the between-subjects factor age group (children, younger adults, older adults) and the within-subjects factor recency (recent vs. nonrecent negatives) showed main effects of recency, F(1, 89) ⫽ 47.64, p ⬍ .001, ␩p2 ⫽ .35, and of age group, F(2, 89) ⫽ 16.01, p ⬍ .001, ␩p2 ⫽ .27. There was a significant interaction between recency and age group, F(2, 89) ⫽ 3.38, p ⬍ .05, ␩p2 ⫽ .07, showing that susceptibility to PI changes across the life span. Recent trials were answered less accurately than nonrecent trials, and planned contrasts revealed that, in general, younger adults were more accurate than older adults (p ⬍ .01) or children (p ⬍ .001). In detail, planned contrasts with the PI-difference scores (difference between recent and nonrecent negatives) showed that young adults

were less affected by PI than children (p ⬍ .01) or older adults (p ⬍ .05). A subsequent ANOVA with the two children groups showed a main effect of recency, F(1, 40) ⫽ 27.53, p ⬍ .001, ␩p2 ⫽ .41; a marginal significant effect of age group, F(1, 40) ⫽ 4.03, p ⫽ .051, ␩p2 ⫽ .09; but no interaction, F(1, 40) ⫽ .34, p ⫽ .563, ␩p2 ⫽ .01. Although recent trials were answered less accurately than nonrecent trials, indicating a PI effect also in the children sample, PI susceptibility did not change from 8 –9 years to 12–13 years. N-back. A repeated-measurements ANOVA with age group (children, younger adults, older adults) as the between-subjects factor and recency (lures vs. nones) as the within-subject factor revealed main effects of recency, F(2, 89) ⫽ 192.05, p ⬍ .001, ␩p2 ⫽ .68, and age group, F(2, 89) ⫽ 28.04, p ⬍ .001, ␩p2 ⫽ .39, and a significant interaction between recency and age group (F(2, 89) ⫽ 25.73, p ⬍ .001, ␩p2 ⫽ .37. Nones were answered more accurately than lures; thus, also in the n-back, PI occurred. In general, young adults were more accurate than older adults or children (both p ⬍ .001). Planned contrasts with the PI-scores (difference between lures and nones) revealed that older adults showed more PI than younger adults (p ⬍ .001), but children surprisingly showed marginally less PI than young adults (p ⫽ .060). Regarding the development of PI within the children sample, a repeated-measurements ANOVA showed a significant effect of recency, F(1, 40) ⫽ 19.50, p ⬍ .001, ␩p2 ⫽ .33, but no main effect of age group, F(1, 40) ⫽ 1.27, p ⫽ .267, ␩p2 ⫽ .03, and no

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slower answers for recent than for nonrecent trials. Older children responded faster than younger children, F(1, 40) ⫽ 15.84, p ⬍ .001, ␩p2 ⫽ .28. However, there was no interaction between recency and age group, F(1, 40) ⫽ .24, p ⫽ .630, ␩p2 ⫽ .01, indicating that PI-related RT costs in this task do not change during development. N-back. A repeated-measurements ANOVA with age group (children, younger adults, older adults) as the between-subjects factor and recency (lures vs. nones) as the within-subject factor revealed main effects of recency, F(1, 89) ⫽ 35.81, p ⬍ .001, ␩p2 ⫽ .29, and of age group, F(2, 89) ⫽ 4.55, p ⬍ .05, ␩p2 ⫽ .09, and a significant interaction, F(2, 89) ⫽ 3.59, p ⬍ .05, ␩p2 ⫽ .08. Lures were answered slower than nones, and planned contrasts revealed that, in general, young adults responded faster than older adults (p ⬍ .01) but did not differ significantly from children (p ⫽ .233). Children were less susceptible to PI than younger adults (p ⬍ .01) but older and younger adults did not differ significantly (p ⫽ .150). Comparing both children groups, a further repeatedmeasurements ANOVA revealed a significant main effect of recency, F(1, 40) ⫽ 8.87, p ⬍ .01, ␩p2 ⫽ .18, showing that lures were

Figure 2. Mean sensitivity (d=; Panel A) and response bias (c; Panel B) in the recent-probes and n-back tasks for each age group. Error bars reflect standard errors of the mean.

interaction, F(1, 40) ⫽ 2.18, p ⫽ .148, ␩p2 ⫽ .05. Thus, while there was evidence of PI in this subsample, resistance to PI did not change in the developmental course. Further analyses regarding interactions between recency, probe type, and age group can be found in the supplementary online material. Reaction times. Recent-probes. A repeated-measurements ANOVA with age group (children, younger adults, older adults) as between-subjects factor and recency (recent vs. nonrecent negatives) as withinsubjects factor resulted in a main effect of recency, F(1, 89) ⫽ 50.01, p ⬍ .001, ␩p2 ⫽ .36; a main effect of age group, F(2, 89) ⫽ 36.89, p ⬍ .001, ␩p2 ⫽ .45; and a marginally significant interaction between recency and age group, F(2, 89) ⫽ 2.50, p ⫽ .088, ␩p2 ⫽ .05. Planned contrasts revealed that young adults answered more quickly than children or older adults (p ⬍ .001) and that recent trials were answered slower than nonrecent trials. Concerning developmental change, older adults showed a trend to being more susceptible to PI (p ⫽ .071), whereas children and younger adults did not differ significantly (p ⫽ .166). A subsequent ANOVA within children samples also showed a main effect of recency, F(1, 40) ⫽ 7.49, p ⬍ .01, ␩p2 ⫽ .16, with

Figure 3. Effects of proactive interference (PI) in the recent-probes and the n-back tasks in children (C), younger adults (YA), and older adults (OA). Displayed are means for interference (recents or lures) and noninterference (nonrecents or nones) trials for accuracy (proportion of correct responses) and reaction times (RT) in milliseconds. The difference between both constitutes PI. Error bars reflect standard errors of the mean.

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Figure 4. Susceptibility to proactive interference (PI) in the recent-probes and the n-back tasks for each age group. PI was calculated as the difference between interference and noninterference negative trials regarding accuracy (proportion of correct responses) and reaction times (RT) in milliseconds. Displayed are means of the difference scores. A higher score reflects more PI. Error bars reflect standard errors of the mean.

answered slower than nones. No significant main effect of age group, F(1, 40) ⫽ .05, p ⫽ .818, ␩p2 ⫽ .00, was observed, but a marginally significant interaction between recency and age group, F(1, 40) ⫽ 3.97, p ⫽ .053, ␩p2 ⫽ .09, indicated that older children had higher PI-related RT costs than younger children. Further analyses regarding interactions between recency, probe type and age group can be found in the supplementary material.

Relationship Between PI in Both Tasks A first exploration of the data considering bivariate correlations between the different measures of PI revealed that these were not comparable in the different age groups, nor did they clearly increase or fall in a linear manner across groups. Therefore, we computed bivariate correlations for each age group separately. As the n is very small in some of the groups and group sizes are

unequal, the analyses should be considered as exploratory and interpreted with caution. Results are reported in Tables 2 and 3. First, we investigated whether WM performance (i.e., overall proportion of correct responses and RT in the nonrecent trials, as well as d= and c) correlated between both tasks. Table 2 shows that there are small to medium relationships between both tasks in overall proportion of corrects, RT and d= in all groups except for the older children. Regarding c, a relationship between both tasks was found only for the older children. These results show that performance in both tasks— except for bias—is related to some degree. Correlations between PI difference scores are reported in Table 3. Significant relationships were found between PI in the recentprobes and in the n-back tasks concerning errors in the older adults (r ⫽ .56) and between PI in terms of errors and RT-costs regarding

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Table 2 Correlations Between Working Memory Scores of Both Tasks Age group

Accuracy (%)

d=

c

Reaction time (ms)

8–9 years 12–13 years Younger adults Older adults

0.35 0.01 0.60 0.47

0.28 0.00 0.44 0.24

0.02 0.53 0.23 ⫺0.16

0.46 0.29 0.59 0.47

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Note. Coefficients printed in bold are significant at the p ⬍ .05 level. Coefficients printed in bold and italics reflect a trend at p ⬍ .10 (both two-tailed). All scores include only trials without proactive interference or recency. d= ⫽ sensitivity; c ⫽ response bias.

the n-back in the 12- to 13-year-old children (r ⫽ .52). The correlations between PI-related errors and PI-related RT costs within the same task were mainly positive (more PI in accuracy results in more PI in RT); therefore, there was no evidence of a possible speed-accuracy–tradeoff in both tasks. We further calculated two PI-composite scores for each participant, one for each task. First, we calculated z scores for all four PI-difference scores (RT and accuracy for both tasks). Then, we calculated a mean score of the scores of each task (e.g., in the n-back, the composite score was calculated as the mean of the z score for PI-related errors and the z score of PI-related RT). There was only a marginal significant correlation between these composites in the older adults (r ⫽ .43), whereas in the other age groups, r was around zero. Taken together, PI scores do not seem to be closely related across both tasks. Finally, we tested whether PI-composite scores were related to WM performance (d=) and response bias (c) in the same task. Table 3 shows that, surprisingly, all correlation coefficients between d= and PI implied a positive relationship between WM and PI. Better sensitivity, and therefore better WM, seemed to go along with more PI. Further, the relation between PI and d= in the recentprobes task increased from childhood to young adulthood, whereas PI and d= in the n-back were highly correlated in the children samples, but not in the adult samples. There was no relationship between PI and response bias.

Discussion The main aims of this study were to investigate the development of WM across the life span and, more specifically, to examine age

differences in item-specific PI within two different WM paradigms, a recent-probes task and an n-back task. Another objective was to determine whether PI effects of both tasks were related. Results regarding these questions are summarized and discussed in the following sections.

Global Development of WM Performance Consistent with our hypotheses, we found better WM performance in younger adults compared with children or older adults in both tasks. Regarding development during childhood, older children performed better than younger children, confirming that the development of WM follows an inverted U-shaped pattern (e.g., Cowan, Naveh-Benjamin, Kilb, & Saults, 2006; Jenkins et al., 1999). Present results also extend findings from studies that investigated WM development using n-back or recent-probes tasks from childhood to young adulthood (e.g., Satterthwaite et al., 2012; Schleepen & Jonkman, 2010; Thomason et al., 2009) or from younger to older adult age (e.g., Reuter-Lorenz et al., 2000; Schmiedek et al., 2009; Thompson-Schill et al., 2002), since to our knowledge, this is the first study in which performance in these two tasks has been directly compared across the life span. Development of sensitivity (d=) showed the same inverted U-shaped pattern as the overall proportion of correct responses in both tasks (see supplemental online material). Concerning response bias (c), all age groups performed similarly in the recentprobes task, while in the n-back, c was the highest in the youngest children and the lowest in the older adults, which indicates a more conservative response pattern for the children. Cowan et al. (2006) also found an inverted U-shaped pattern regarding d= in a life span study with a visual WM task, with older adults showing the largest response bias compared with children and younger adults. Two studies with an n-back task also found better discrimination from childhood to young adulthood (Satterthwaite et al., 2012; Schleepen & Jonkman, 2010). However, there were no age-related differences regarding response bias (Satterthwaite et al., 2012). In older adults, Oberauer (2005) did not find any age differences between older and younger adults concerning d= in an n-back task. In sum, the relationship between d= and c and their development across the life span are not yet fully understood. While in our study, the development of d= ran quite in parallel for both tasks, the different development of c in both tasks might reflect different tasks demands or different underlying cognitive processes.

Table 3 Correlations Between Proactive Interference (PI) Difference Scores, PI Composites, and Working Memory (WM) PI composites

PI difference scores

WM and PI composites

Age group

RP_Acc NB_Acc

RP_RT NB_RT

RP_Acc RP_RT

NB_Acc NB_RT

RP_Comp NB_Comp

RP_Comp RP_d=

NB_Comp NB_d=

RP_Comp RP_c

NB_Comp NB_c

8–9 years 12–13 years Younger adults Older adults

⫺0.09 0.09 0.0 0.56

⫺0.22 0.05 ⫺0.10 0.16

0.15 ⫺0.08 0.19 0.06

0.13 0.52 0.15 0.29

⫺0.02 0.04 0.01 0.43

0.29 0.39 0.53 0.09

0.82 0.56 0.17 0.36

⫺0.14 ⫺0.14 0.04 0.12

⫺0.21 ⫺0.16 ⫺0.14 ⫺0.17

Note. Coefficients printed in bold are significant at the p ⬍ .05 level. Coefficients printed in bold and italic reflect a trend at p ⬍ .10 (both two-tailed). PI difference scores reflect differences between interference and noninterference negative trials; a higher score reflects more PI. RP ⫽ recent-probes task; NB ⫽ n-back task; Acc ⫽ difference score related to accuracy; RT ⫽ difference score related to reaction times; Comp ⫽ composite score of PI in accuracy and reaction times. d= ⫽ sensitivity; c ⫽ response bias. d= and c include only trials without PI or recency.

DEVELOPMENTAL CHANGE IN PROACTIVE INTERFERENCE

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Development of Resistance to PI Within WM Present results show a change in susceptibility to PI over the life span. As expected, older adults committed more PI-related errors than younger adults in both tasks. This result is supported by a trend towards more PI-related RT costs in older than in younger adults in the recent-probes task. We hence replicate findings from previous studies that have shown more susceptibility to itemspecific PI in older compared with younger adults within these tasks (e.g., Jonides et al., 2000; McCabe & Hartman, 2008; Schmiedek et al., 2009). PI development from childhood to young adulthood differed across both tasks. In the recent-probes task, children committed more PI-related errors, but an equal amount of PI was evident in the RT data. In the n-back task, however, there was a trend towards less PI-related errors than in younger adults, and PI-related RTcosts were smaller. Older and younger children did not differ in the recent-probes task, but younger children showed a trend to even less PI-related RT costs in the n-back, although there were no differences regarding PI-related errors in this task. In general, while the results in the recent-probes task show more PI in children than in young adults and an equal susceptibility to PI between the ages of 8 and 13 years, we observed a trend towards less PI in children than in younger adults in the n-back and even less PI in younger than in older children. To our knowledge, no previous studies exist regarding itemspecific PI during childhood or across the life span. Most studies investigating item-nonspecific PI have shown a decrease of PI susceptibility in the developmental course (see Kail, 2002, for a meta-analysis). Considering this but also the fact that the ability to inhibit interfering information in general improves with ongoing development (Huizinga, Dolan, & van der Molen, 2006), one would expect also susceptibility to item-specific PI to decline in both tasks instead of the different developmental course in both tasks found here. A theoretical approach that may provide an interpretation for the diverging results across both tasks was developed by Cowan (1988) and later extended by Oberauer (2001, 2005). A central component of their WM model is the focus of attention (FoA), renamed later to region of direct access by Oberauer and contains those representations that an individual is aware of at a particular moment (Oberauer, 2001). It builds associations between item and contextual information through binding in using temporal, positional, or item-specific information (McCabe & Hartman, 2008; Oberauer, 2005). Two dissociable and – in the case of PI – conflicting sources of information, familiarity and recollection, have been described to occur in WM tasks (Oberauer, 2001, 2005; Oberauer & Lange, 2009; Szmalec, Verbruggen, Vandierendonck, & Kemps, 2011): Familiarity arises automatically from activations from previous items not present in the FoA and may cue a “yes” response (i.e., the probe was part of the actual target set), while recollection may lead to a “no” response (i.e., the probe was not in the target set). Recollection starts later, is more controlled, and provides stronger evidence; therefore, familiar information on which probe is not part of the target set will be rejected if recollection works well (Oberauer, 2005). To overcome PI, one must either inhibit familiarity that comes from the interference trials, or one must recollect the fact that the probe was not one of the questioned targets (Oberauer, 2001, 2005). An explanation for

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the present developmental effects regarding PI might therefore be that the ability either to inhibit a response based on familiarity or to use recollection processes differs across the life span. In young adults, PI seems to depend on the strength of bindings in WM (Szmalec et al., 2011), which affects recollection (Oberauer, 2005). By comparing familiarity and recollection, Oberauer (2005) has shown that age differences in PI between younger and older adults may most likely come from a deficit in bindings between context and content and not from a deficit in inhibiting familiarity-induced information. While children also have difficulties in binding information in WM (Cowan et al., 2006) compared with processes of cognitive control like inhibition, binding nevertheless seems to be relatively mature (Sander, Lindenberger, & Werkle-Bergner, 2012). However, there are no studies comparing familiarity and recollection directly in PI tasks in children. Although poor recollection might provide an explanation for the developmental effects from younger to older adulthood in both tasks as well as from childhood to adulthood in the recent-probes task, it cannot account for the n-back results in the children. Nonetheless, different interactions between familiarity and recollection in the four age groups might account for the diverging development of PI susceptibility across both tasks, as binding and cognitive control have been shown to be differently related to WM capacity across the life span (Sander et al., 2012). In contrast to recollection, deficient inhibition processes could provide an explanation for the developmental effects in both tasks. In the recent-probes task, higher susceptibility to PI in children compared with young adults may be a result of poorer inhibition processes, as they immediately pressed the “yes” button when they encountered familiar information. Deficient inhibition processes also could explain the results in the n-back task. These cannot be explained with overreacting on familiarity, since PI-effects tended to be smaller in children than in younger adults. Rather, the specific task structure of the n-back with 80% negative trials might have posed high demands on inhibition processes also when interference trials are not accounted for, because the default negative answer pattern had to be disrupted when a positive target appeared. As this ability to withhold a prepotent response has been shown to be reduced in children (Casey et al., 2002), the automatic response pattern, which resulted in predominantly fast “no” answers and increased response bias in young children, might also have hampered possible familiarity effects, which should have elicited PI. The inhibition account is also supported by the fast reactions and therefore equal or even lower PI-related RT costs in children compared with young adults in both tasks. In sum, deficient inhibition processes could account for the developmental effects regarding childhood in both tasks, but for different reasons. In older adults, poorer inhibition might also be an explanation for the increased PI effects in both tasks; however, we suggest that responding to familiarity is the underlying cause in both tasks, as response bias is equal for both tasks in older adults. A third explanation, especially for the diverging effects between both tasks during development in childhood, might come from different task demands supposed to be involved in both tasks. More excessive demands of the n-back task compared with the recent-probes task require additional attention and executive processes (Kiss et al., 2007). Therefore, the n-back task, compared with the recent-probes task, might have been more difficult for children than for adults, because their executive functions are not

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yet fully developed (Prencipe et al., 2011). Performance in the target condition of the n-back, which measures WM capacity, showed that especially the younger children had difficulties remembering the animal two positions back (see Figure S2 in the online supplementary material). Remembering the animal three positions back (i.e., the lure position, which should elicit PI) would have been even more difficult. However, to be susceptible to PI, one has to either remember the information that was in the PI condition or to perceive at least familiarity about this information. If WM capacity is overloaded or too small, the content of the lure trial might already be out of WM again, and no PI occurs. This is also supported by the correlation analyses reported in Table 3, where correlations between WM capacity (d=) and PI were medium to high for older and younger children, respectively. Although it has been shown that in contrast to recollection, familiarity is capacity-independent (Oberauer & Lange, 2009) and also should occur in low-capacity individuals, familiarity from lure items in an n-back task was also shown to decrease the further back from n the lure items are presented (Schmiedek et al., 2009; Szmalec et al., 2011). This decrement may be enhanced if overall WM capacity—including “executive capacity”—is overloaded during encoding or delay and can therefore lead to less familiarity and therefore less PI. Differing task demands might additionally have caused differences in RTs across tasks, as responses in the n-back were faster than those in the recent-probes (see Figure 3). However, as PI was calculated as the difference between recent and nonrecent negatives, group and task differences in global RTs should not necessarily blur developmental effects regarding PI. In sum, PI-susceptibility seems not only to change quantitatively over the life span, but there also seem to be qualitatively different processes and demands involved across age groups and tasks. We observed a change in resistance to PI over the life span, but there is probably also a change in being susceptible to PI at all.

Relationship Between Both Tasks Correlation analyses revealed only two significant relationships between PI scores: In the aging sample, PI-related errors of both tasks were positively correlated, and in the older children, there was a positive correlation between PI-related errors and PI-related RT costs in the n-back task. In addition, a (marginally significant) relationship between composites of both tasks was present in the older adults. The assumption that both tasks measure PI in a similar way therefore only holds—if anything—for the older adults. Methodological reasons might account for this missing relationship between the PI measures. For instance, sample sizes were partly small and imbalanced. Further, there was a relatively high variability in the PI-scores across participants, which was also observed in other studies investigating PI (Bunge et al., 2001; Wolf, Walter, & Vasic, 2010). In addition, difference scores have been described as to be sometimes of low reliability (see, e.g., Friedman & Miyake, 2004). In the present study, we also found only small to medium correlations between overall measures of both tasks (i.e., scores without interference trials). This implies that different cognitive processes are involved in both tasks, probably due to a different task structure, as discussed previously. The recent-probes task is a prototypical maintenance task, while the n-back additionally requires the manipulation of the to-be-remembered memory content

(Veltman, Rombouts, & Dolan, 2003). According to Smith and Jonides (1997), the n-back task requires encoding of a stimulus, matching it to a representation of an item n positions back, responding on the basis of this comparison, updating the memory contents, storing these items and their temporal code, and rehearsing these items and codes. All these processes happen simultaneously. The stimuli are presented in a continuous stream, often of an uncertain length, and therefore, permanent updating is required (Conway et al., 2005). In contrast, in the recent-probes task, encoding and retrieval do not occur simultaneously, although memory contents also have to be updated each time a new target set is presented. Further, due to the task structure, there might be more opportunity for rehearsal, which also can influence familiarity, and hence PI (Szmalec et al., 2011). Actually, there is an ongoing debate in the current WM literature if different tasks such as complex or simple spans but also dynamic WM tasks like the n-back really measure the same underlying construct (Conway et al., 2005; Kane, Conway, Miura, & Colflesh, 2007; Oberauer, 2005). Especially the validity of the n-back as a WM task has repeatedly been questioned, as correlations to other WM tasks seem to be weak (see, e.g., Kane et al., 2007).

Conclusion Our results provide empirical evidence that besides an inverted U-shaped development of WM performance in the recent-probes and n-back task over the life span, there is also a change in item-specific PI over the life span in these tasks. However, differential effects of PI between both tasks were found, especially in children, whereas PI in older adults converged in the two tasks. We therefore suggest that the difficulties regarding resisting previously relevant information observed in children and in older adults have different causes (e.g., differently developed inhibition or recollection processes across the samples). The inverted U-shaped development should hence not be interpreted as older adults returning to childlike performance. From a practical point of view, the recentprobes task may be better suited for assessing WM and PI in children samples, as it involves fewer executive demands.

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Received December 10, 2012 Revision received October 17, 2013 Accepted October 23, 2013 䡲