Aging Influences the Efficiency of Attentional Maintenance in Verbal Working Memory

Aging Influences the Efficiency of Attentional Maintenance in Verbal Working Memory Abstract Objectives Numerous studies reported an age-related deficit in verbal working memory (WM). Beyond the well-established general factors of cognitive aging, the alteration of the specific WM maintenance mechanisms may account for this deficit. This paper aims to investigate the hypothesis that WM attentional maintenance is impaired with age. Method In a WM task adapted to individual short-term memory and processing speed, younger and older participants maintained letters while verbally responding to a concurrent processing task, in order to constrain the use of rehearsal. Critically, the opportunity to use attentional maintenance was manipulated by varying the cognitive load (CL) of the concurrent processing via its nature and pace. Results Younger participants outperformed older participants and, in both groups, recall performance decreased as the CL increased. Importantly, in line with our predictions, the CL effect was modulated by age. Older adults benefited less from free pauses that allowed participants to engage in attentional maintenance of WM traces. Discussion Although still effective in normal aging, WM attentional maintenance seems to be altered. It could therefore be a good candidate to account for WM age-related deficits. Cognitive aging, Complex span task, Maintenance mechanisms, Working memory Working memory (WM) is defined as the immediate memory system that allows maintenance and manipulation of information in the service of ongoing complex cognitive activities (e.g., Kane et al., 2004). Its functioning is commonly assessed with a complex span task (CST) that requires participants to maintain a series of to-be-remembered items while concurrently engage in other processing activities (for a methodological review of CSTs, see Conway et al., 2005). It is well documented that older adults are less efficient than younger adults in these CSTs (Bopp & Verhaeghen, 2005; Park et al., 2002). General factors of cognitive aging have been proposed to affect WM functioning (e.g., decline of processing resources, Craik & Byrd, 1982; decrease of processing speed, Salthouse, 1996; inefficient inhibition, Hasher & Zacks, 1988, see Park & Festini, 2017 for a review of theories). In addition, one obvious aspect of WM functioning that should account for age-related differences in WM is the efficiency of the mechanisms being used to maintain the information in WM. Following the seminal model of Baddeley and Hitch (1974), the maintenance of verbal information in WM is commonly assumed to be underpinned by rehearsal (Baddeley, Lewis, & Vallar, 1984). However, there is now a large literature suggesting that, in addition to rehearsal, WM maintenance also relies on attention (e.g., Barrouillet, Portrat, & Camos, 2011; Cowan, 1998; Tam, Jarrold, Baddeley, & Sabatos-DeVito, 2010; Vergauwe & Langerock, 2017). The present study aimed to investigate age-related deficits in attentional maintenance of information in verbal WM by examining its consequences for recall performance in a CST. Rehearsal is assumed to be based on language-production processes that involve covert or overt repetition of the phonological representation of the to-be-remembered information. Two specific effects related to verbal constraints of rehearsal are documented in WM tasks: worse recall for lists of long words than for lists of short words (word-length effect, e.g., Baddeley, Thomson, & Buchanan, 1975) and worse recall when subjects have to continuously recite irrelevant sounds (concurrent articulation effect; e.g., Richardson & Baddeley, 1975). Although the word-length and concurrent articulation effects observed in older adults were commensurate with those observed in young adults (Loaiza & McCabe, 2013; Peters et al., 2007), suggesting that rehearsal is preserved with age, other studies have revealed both qualitative (e.g., number of different items being rehearsed, Ward & Maylor, 2005) and quantitative age-related differences in rehearsal (e.g., slowed articulation rate, Kynette, Kemper, Norman, & Cheung, 1990). A fairly recent body of research has highlighted the importance of attention for the maintenance of verbal information in WM. Several attentional mechanisms have been proposed in the literature, such as memory search (Cowan, 1999; Vergauwe & Cowan, 2015), refreshing (Johnson, 1992; Raye, Johnson, Mitchell, Greene, & Johnson, 2007), focus switching (Basak & Verhaeghen, 2011; Verhaeghen & Hoyer, 2007), and attentional refreshing (Barrouillet, Bernardin, & Camos, 2004; Barrouillet et al., 2011). Whether or not these different concepts refer to a single mechanism remains an open question (see Camos et al., in press) and is outside the scope of the present study. However, there is agreement on the existence of attention-based maintenance of information, which prolongs and/or increases the activation of WM information by briefly focusing attention on it (Barrouillet et al., 2011; Cowan, 1999; Johnson, 1992). Data from behavioral and neuroimaging studies strongly suggest that this attention-based maintenance is distinct from articulatory rehearsal (Cowan, 1999; Raye et al., 2007; see Camos, 2015 for a review). Whereas rehearsal is exclusively dedicated to the maintenance of verbal information and is thought to rely on subvocal articulation (which barely requires attention after the articulatory sequence has been initiated), attention-based maintenance relies on attention and is thought to act on information from different sensory modalities (i.e., verbal, visual, and spatial modalities). Consequently, this attention-based maintenance should be affected by attentional constraints imposed in WM tasks. In line with this assumption, many studies have shown that the variation of the proportion of time during which attention is available in a CST, through the manipulation of the number of to-be-processed items, the difficulty of the processing task, or the total time allowed to perform it, affects recall performance (e.g., Barrouillet et al., 2011; Portrat, Camos, & Barrouillet, 2009, Vergauwe, Barrouillet, & Camos, 2010). These results prompted the generation of the Time-Based Resource-Sharing model (TBRS, Barrouillet & Camos, 2015) of WM. In this model, attentional maintenance is underpinned by a mechanism called attentional refreshing, which counteracts, during the short pauses following each distracting activity in CSTs, the loss of information caused by concurrent processing. In this framework, the proportion of time during which attention is distracted from refreshing during the processing phase of a WM task is referred to as the cognitive load (CL). The manipulation of CL in CSTs has proven to be fruitful for investigating the use of refreshing in young adults (Barrouillet & Camos, 2015, for a review) as well as the developmental differences in children (Gaillard, Barrouillet, Jarrold & Camos, 2011). More specifically, Gaillard and colleagues (2011) showed that these differences could be accounted for by a development of the efficiency of refreshing with age. Indeed, in their second experiment, they observed that for equated CL, younger children took less advantage from the same periods of free time than older children, suggesting that younger children may be less efficient in refreshing. Yet, CL effect has not been extensively tested in the context of aging: to the best of our knowledge, only two studies have investigated the hypothesis of an age-related impairment in refreshing from a CL perspective (Baumans, Adam, & Seron, 2012; Plancher, Boyer, Lemaire, & Portrat, 2017). In Plancher and colleagues (2017), younger and older adults performed a CST in which they had to memorize a series of images while reading aloud words. The pace of the to-be-read words was varied (slow vs fast) as well as the degree of interference induced by these words (repeated words vs all new words within a trial). While the recall performance of young participants elicited an easy-to-interpret pattern with a classical pace effect but no interference effect, older participants also performed better at slow pace than at fast pace but only when the amount of interference was low. The authors concluded that a decrease in WM performance with aging can be explained by a difficulty in taking advantage of WM maintenance opportunities, especially in conditions of high interference. In their study, Baumans and colleagues (2012) had younger and older adults perform a CST in which participants had to maintain series of letters, presented first, before performing a processing task that consisted of judging the color of digits. Then, participants had to recall the letters in the correct order. The pace of the digits was varied to manipulate the CL of the processing task. The results showed that while a small CL variation had no effect on older adults (Experiment 1), a large CL manipulation had the same detrimental effect on recall performance for both age groups (Experiment 2). As acknowledged by the authors themselves, these results preclude a “definitive” conclusion in term of refreshing. Although a small variation of CL has been shown to affect WM performance in younger adults (e.g., Barrouillet, Bernardin, Portrat, Vergauwe, & Camos, 2007), Baumans and colleagues did not find such a pattern in older adults (Experiment 1). This result could count as evidence in favor of a lower sensitivity of older adults to the CL effect and therefore in favor of an age-related deficit of refreshing. This interpretation would be in line with other studies suggesting such a deficit using different verbal memory tasks (delayed recognition test, Johnson, Reeder, Raye, & Mitchell, 2002; Johnson, Mitchell, Raye, & Greene, 2004; Raye, Mitchell, Reeder, Greene, & Johnson, 2008; delayed free recall, Loaiza & McCabe, 2013; Loaiza, Rhodes, & Anglin, 2015). However, as mentioned above, Baumans and colleagues (2012) also observed that equivalent large manipulations of CL across groups had a similar effect on recall performance for both age groups (Experiment 2), a result that goes against an age-related refreshing deficit. This result is at odd with the body of research developed by Johnson and colleagues but is in line with recent studies (Loaiza & Souza, in press; Souza, 2016). For instance, in her study, Souza (2016) found that older and younger adults benefited to the same extent from retro-cue displayed during the maintenance phase of a visual WM task. To summarize, the current literature does not offer clear evidence in favor of an age-related deficit in refreshing. The aim of the present study was therefore to further investigate this hypothesis by having younger and older adults performing an adapted computer-paced CST in which the CL of the processing task was varied through its nature (parity and location judgment) and pace (slow and fast). Moreover, participants had to perform this task under articulatory constraints in order to minimize the use of rehearsal. Indeed, the CL effects observed in Baumans’ study could be attributed, at least in part, to a different involvement of rehearsal across conditions since participants had to maintained letters in the face of a silent concurrent processing task. The WM task was adapted to control for possible age differences in short-term memory and processing speed. According to an age-related deficit in refreshing hypothesis, we predicted that older adults should be less affected by the manipulation of CL than younger adults. Indeed, if refreshing is less efficient with age, as suggested by several evidences in the literature, then older adults should benefit less from increased free time, thereby leading to greater differences between age groups as CL decreases. METHOD Participants Twenty-four undergraduate students (four males) aged between 18 and 28 years (M = 21.2, SD = 2.2) and 24 older adults (six males) aged between 60 and 84 years (M = 69.5, SD = 6.1) participated in the study, which was approved by an ethics committee (CERNI, IRB00010290, 2015-11-10-4). All participants were volunteers, were native French speakers, had normal or corrected-to-normal vision, had no neurological background, and provided written informed consent before taking part in the study. After the experimental session, older participants were screened to rule out dementia by means of the Mini-Mental State Examination (Kalafat, Hugonot-Diener, & Poitrenaud, 2003). Older participants were recruited either from social centers or from previous studies carried out in our laboratory. Students received partial course credit for participating. Materials and Procedure All tasks were displayed on a laptop by using E-Prime 2.0 software (Psychology Software Tools, Pittsburgh, PA). First, participants performed a short-term span task (Figure 1A) designed to calibrate the memory load in the subsequent WM task. The computer-paced series of consonants to be memorized were displayed on the computer screen. We used all the consonants except W, which is trisyllabic in French. The various consonants were displayed at approximately the same frequency throughout the task, after controlling for their position within the lists. Within a single series, a consonant was never repeated. Acronyms and alphabetically ordered series were avoided. Each trial began with a screen indicating the number of letters to be remembered. The first trial was set to two consonants. A central fixation point was then displayed on the screen for 500 ms, followed by the first letter of the sequence. Letters (in Courier New font) were displayed in the center of the screen for 700 ms, and then replaced after a 300 ms delay. Participants had to read each letter aloud. At the end of each sequence, the word “Rappel” (recall, in French) appeared on the screen; this indicated to the participant that he or she had to verbally recall the consonants in the correct order. The experimenter noted the participant’s recall, and then pressed the “Enter” key if all the consonants had been recalled in the correct order or any other key on the keyboard if not. There were two trials for each list length. The task ended when the participant failed to recall both trials of a given length. As conventionally assessed, the short-term span corresponded to the greatest length for which the participant had recalled at least one series in the correct order (see Wechsler, 2008, Longest Span Scores). Figure 1. View largeDownload slide (A) Illustration of the short-term memory span task. (B) Illustration of the processing speed tasks. Figure 1. View largeDownload slide (A) Illustration of the short-term memory span task. (B) Illustration of the processing speed tasks. Next, the participants’ processing speed was evaluated in a parity/location judgement task (Figure 1B). Two tasks (location and parity) were displayed at two paces (fast and slow), resulting in four conditions. The conditions were randomly presented. Each consisted of a block of twenty successive stimuli to be processed. The stimuli were digits ranging from “1” to “10”, and they were displayed on the screen randomly in either a lower or an upper position (80% and 20%, respectively of the screen’s Y-axis). In the location task, participants had to judge the position of the digits (saying “up” or “down”). In the parity task, they had to judge the parity of the digits (saying “even” or “odd”). Each trial began with a screen indicating the task to be performed (parity or location) and the pace (slow or fast). After the participant pressed a key on the keyboard, a central fixation point was displayed on the screen for 500 ms, followed by the first digit. In the fast-paced condition, digits were displayed for 700 ms and replaced after 350 ms. In the slow-paced condition, digits were displayed for 1,200 ms and followed by a 600 ms delay. Participants were given the full time period (presentation plus delay) to give their responses, which were recorded with a vocal key connected to a serial response box. The experimenter marked the participants’ responses. The mean reaction time for each condition was calculated after excluding reaction times below 200 ms. Lastly, participants had to perform a computer-paced CST that combined letters to be memorized with a digit processing task (Figure 2). The series of consonants to be maintained and stimuli to be processed had the same restrictive characteristics as in the short-term span task and the processing speed task, respectively. The CL was varied across four experimental conditions in which the type of processing (location or parity) and pace of processing (fast or slow) was manipulated. The various experimental conditions were presented in random order, and each consisted of five successive trials. Each trial began with a screen indicating the processing task (“L” for location or “P” for parity) and the pace (“S” for slow or “F” for fast). After the participant pressed a key on the keyboard, a central fixation point was displayed on the screen for 500 ms, followed by the first letter in the sequence. Letters were displayed at the center of the screen for 1,200 ms, and participants had to read them aloud. After a 300 ms delay, four digits appeared randomly on the lower or upper part of the screen. After the last delay following the last digit, the second letter appeared, and so on until the end of the sequence. Throughout the session, the length of the series to be remembered was set to the short-term span of each participant. At the end of each sequence, the word “Rappel” (recall) appeared on the screen—indicating that the participant had to verbally recall the consonants in the correct order. The experimenter marked participants’ responses and then pressed a key on the keyboard to continue to the next trial. Figure 2. View largeDownload slide Illustration of the time course of two trials in the working memory span task: a “location” trial in the slow-paced condition (L/S, upper panel), and a “parity” trial in the fast-paced condition (P/F, lower panel). Td refers to the time delay following each distractor, and pT refers to the distractor presentation time. Figure 2. View largeDownload slide Illustration of the time course of two trials in the working memory span task: a “location” trial in the slow-paced condition (L/S, upper panel), and a “parity” trial in the fast-paced condition (P/F, lower panel). Td refers to the time delay following each distractor, and pT refers to the distractor presentation time. In the fast-paced and slow-paced conditions, digits were displayed for 700 ms and 1,200 ms, respectively. The delay between two digits (denoted as “Td” in the figure) was specific for each participant, in order to standardize the CL across individuals. Indeed, the CL correspond to CL =a/(pT + Td) where a is the time during which a distractor captures attention, pT is the distractor presentation time (700 and 1,200 ms for fast- and slow-paced conditions, respectively), and Td is the duration of the delay following the distractor. Thus, it is possible to find the specific value of Td if one knows the values of the other parameters (Td = a/CL-pT). Given that we were testing for an interaction between age group and CL, we wanted to achieve a high degree of variation in the CL. However, the task also had to be manageable for the participants. Thus, we wanted the most difficult condition to elicit a CL of around 0.65 and the easiest condition to elicit a CL of around 0.25. On the basis of the literature (e.g., Barrouillet et al., 2007) and a pilot study, we expected the parity judgement to elicit longer RTs. Thus, in the fast-paced conditions, parameter a corresponded to the mean reaction time of the participant in the parity tasks (slow and fast) measured beforehand in the processing speed tasks. In the slow-paced conditions, parameter a corresponded to the participant’s mean reaction time in the location tasks. Thus, the fast and slow paces were adjusted for each participant. Participants were given the full time period (presentation plus delay) to give their responses, which were recorded with a vocal key connected to a serial response box. The use of rehearsal was constrained by asking participant to verbally respond to the processing task. Accuracy and reaction times for the processing tasks were recorded, together with the number of letters recalled in the correct order. The measured CL in each condition was calculated by dividing the mean reaction time for a correct response in the processing task by the total available response time (i.e., presentation plus delay). The experimental session was preceded by a training phase in which participants performed two random CST trials (parity/fast and location/slow). Data Analysis Statistical analyses were conducted by using RStudio version 1.0.143 for Windows (RStudio Team, 2016) with the R package lme4 (Bates, Maechler, Bolker, & Walker, 2015). To obtain the p values from multilevel models, we used the Satterthwaite approximation of degrees of freedom, which is implemented in the lmerTest package (Kuznetsova, Brockhoff, & Christensen, 2016). Our main analysis was focused on the memory performance on the WM task; therefore, we computed the number of letters recalled in correct position in each condition for each participant. Moreover, we computed the mean reaction time to respond to the processing component of the WM task in each of the four conditions by taking into account correct responses only. These mean reaction times for each condition were computed for each participant, thus we were able to compute the measured CL elicited by our experimental manipulations for each participant using the equation: CL = reaction time/(presentation time + delay). RESULTS Short-term Span Task There was no difference in short-term spans between the two groups (t < 1), with performance ranging from 4 to 7 for both young (M = 5.42, SD = 0.93) and older adults (M = 5.42, SD = 0.72). Processing Speed Task Reaction times below 200 ms were disregarded for this analysis (accounting for 10% and 8% of the data for older and younger adults, respectively). Reaction times were analyzed by fitting a mixed effect linear model including Group (younger vs older adults), Task (Parity vs Location) and Pace (Slow vs Fast) as fixed effects and Participant as a random factor (accounting for the multiple response measures per participant). The results of the analyses (see Table 1) revealed significant effects of Task (t(137.9) = 28.81, p < .001) and Pace (t(137.9) = 4.94, p < .001). All other effects were not significant (p > .1). Table 1. Mean Reaction Times and Accuracy in the Processing Speed Task (95% within-subject confidence intervals) As a Function of Experimental Conditions and Groups Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) View Large Table 1. Mean Reaction Times and Accuracy in the Processing Speed Task (95% within-subject confidence intervals) As a Function of Experimental Conditions and Groups Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) View Large WM Performance As a Function of the Pace and the Nature of the Processing Task All of the 192 data values collected in the WM task (48 participants × 4 conditions) were included in the analyses as participants performed well on the distracting task (min = 74% accuracy). Ordered recall performance was analyzed by fitting a mixed effect logistic model, as recommended by Jaeger (2008), while the measured CL was analyzed by fitting a mixed effect linear model. Both models included Group, Task and Pace as fixed effects and Participant as a random factor. Results of the analyses revealed a significant effect of Group on recall performance (Wald Z = 3.75, odds ratio [OR] = 1.92, p < .001), with younger adults (M = 53.9%, SD = 23.4) outperforming older adults (M = 38.6%, SD = 13.9), but this factor was not significant on the measured CL (p = .47). There was also a significant effect of Pace on both recall performance (Wald Z = 9.54, OR = 1.77, p < .001) and measured CL (t(138) = −22.4, p < .001). In line with numerous previous results, the Fast condition elicited worse recall performance than the Slow condition (M = 39.8% and 52.8%, SD = 18.8 and 16.5, respectively) and, as planned, resulted in a higher measured CL than the Slow condition (M = 0.59 and 0.42, SD = 0.11 and 0.11, respectively). The same pattern of results was observed for the effect of Task on both recall performance (Wald Z = −8.95, OR = 0.59, p < .001) and measured CL (t(138) = 15.8, p < .001). More precisely, the Parity condition elicited a higher CL than the Location condition (M = 0.57 and 0.44; SD = 0.14 and 0.14, respectively) and resulted in worse recall (M = 40.4% and 52.2%, SD = 18.4 and 17.9, respectively). Most importantly, there was a significant interaction between Task and Group on recall performance (Wald Z = −3.53, OR = 0.66, p < .001), with a greater recall difference between the two tasks for younger (16.2%) than older adults (7.3%). However, there was also a significant interaction between these factors on measured CL (t(138) = 2.4, p = .015), with a greater difference in CL between the parity and location tasks for younger (0.14) than older adults (0.10). This last outcome was unexpected since our procedure was designed precisely to keep the CL constant between the two groups. Unfortunately, it prevented us from concluding in favor of an age-related refreshing deficit hypothesis because a differential CL effect between groups could have explained the decisive Group x Task interaction on recall performance. Hence, to test our hypothesis, we directly used the measured CL elicited by the conditions as a continuous predictor of recall performance. WM Performance As a Function of the CL of the Processing Task We fitted a mixed effect logistic model including Group and measured CL as fixed effects and Participant as a random factor. Results of the analyses, summarized in Table 2, revealed a significant effect of measured CL (Wald Z = −12.1, OR = 0.044, p < .001) and Group (Wald Z = 4.79, OR = 4.44, p < .001) and a significant interaction between measured CL and Group (Wald Z = −3.33, OR = 0.18, p < .001). As predicted, recall performance increased as CL decreased, younger adults outperformed older adults, and older adults were less affected by the modulation of CL (Figure 3). Table 2. Summary of the Recall Performance Model Fitted on Data With Coefficient Estimates, SE, Wald Z Values, p Values, OR, and 95% CI Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Note: Coef = Coefficient estimate; CI = Confidence interval; CL = Cognitive load; OR = Odds ratio; SE = Standard error. View Large Table 2. Summary of the Recall Performance Model Fitted on Data With Coefficient Estimates, SE, Wald Z Values, p Values, OR, and 95% CI Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Note: Coef = Coefficient estimate; CI = Confidence interval; CL = Cognitive load; OR = Odds ratio; SE = Standard error. View Large Figure 3. View largeDownload slide The proportion of letters recalled in the correct order as a function of the task’s cognitive load in the two age groups (older and younger adults), along with the mixed logistic model built for recall performance (including the significant effects of Group and Cognitive Load, and the interaction between the two). Figure 3. View largeDownload slide The proportion of letters recalled in the correct order as a function of the task’s cognitive load in the two age groups (older and younger adults), along with the mixed logistic model built for recall performance (including the significant effects of Group and Cognitive Load, and the interaction between the two). Discussion There is currently a growing consensus among researchers whereby attentional maintenance supplements the phonological maintenance of verbal information in WM. This attentional maintenance is thought to prolong and/or increase the activation of perceptual information that has disappeared by briefly focusing attention on it—thereby preventing its loss from WM (Barrouillet et al., 2004; Cowan, 1998; Johnson, 1992). Moreover, attentional maintenance also plays a role in the stabilization of information in longer term memory (Camos & Portrat, 2015; Jarjat et al., in press; Johnson et al., 2002; Loaiza & McCabe, 2013). However, whether attentional maintenance corresponds to a set of different mechanisms (i.e., memory search, Vergauwe & Cowan, 2015; refreshing, Johnson, 1992; focus switching, Basak & Verhaeghen, 2011; attentional refreshing, Barrouillet et al., 2011); or to a single mechanism with different names in the literature remains an open question (see Camos et al., in press). In the present study, we adopted the TBRS model of attentional maintenance (referred to as refreshing), which is thought to increase the activation of WM information during the short pauses following each distracting activity in CSTs (Barrouillet et al., 2004). While several studies have shown that the beneficial effect of attentional maintenance is reduced with age (Johnson et al., 2002; Loaiza & McCabe, 2013; Loaiza, et al., 2015; Raye et al., 2008), thus suggesting that it is impaired with age, there are also evidences that attentional maintenance might be preserved with age (Baumans et al., 2012, Experiment 2; Loaiza & Souza, in press; Souza, 2016). The aim of this study was therefore to further investigate the hypothesis that there is an age-related impairment in refreshing (Barrouillet et al., 2004) that contributes to the understanding of the well-known age-related decline in verbal WM (Bopp & Verhaeghen, 2005; Park et al., 2002). To do so, younger and older adults were asked to perform a CST in which the opportunity to use refreshing was manipulated by varying the CL of the task while the use of rehearsal was constrained. By introducing articulatory constraints into our paradigm, we found evidence against the hypothesis that younger and older adults show comparable CL effects—something that Baumans and colleagues (2012) did not observe in their “silent task” paradigm. In contrast to Baumans and colleagues (2012), we found that older adults benefited less from a decrease in CL than younger adults did. These results suggest that the two groups benefitted to a different extent from free time for WM maintenance. However, the participants could have used free time to rehearse instead of refresh. Indeed, as an anonymous reviewer suggested, our participants were not asked to continually articulate an irrelevant sound after having given their response aloud; this type of control would have been necessary to totally suppress articulatory rehearsal. We therefore ran a control experiment (see Supplementary Materials) in which younger and older adults were asked to perform a CST with strict articulatory suppression. We observed an age-related difference in WM performance even under conditions when only attentional maintenance could take place. This finding confirmed that the outcomes of the present study cannot be attributed solely to an age-related difference in rehearsal. Thus, asking participants to respond verbally in the concurrent task (as we did) probably reduces reliance on articulatory rehearsal, relative to the Baumans and colleagues (2012) study. In turn, this enabled us observe the critical interaction between CL and age. The hypothesis whereby the CL × age interaction depends on the incentive to rely on rehearsal would be strengthened by a within-subject comparison of silent versus articulatory suppression conditions. Given that our paradigm was adjusted to the participants’ short-term span and processing speed, the interaction cannot be interpreted with regard to age-related disparities in the task’s difficulty. Hence, in line with other studies (Johnson et al., 2002; Loaiza & McCabe, 2013; Loaiza, et al., 2015; Raye et al., 2008), our findings reflect an age-related impairment in the use of attention to maintain information. More precisely, and given the paradigm used here (i.e., a variation in the proportion of free time following each distracting activity in a CST), attentional refreshing is most likely to be involved (Barrouillet et al., 2004). Four hypotheses, not necessarily exclusive, could account for this age-related deficit in refreshing. Each of these hypotheses relies on a necessary step that refreshing implies within CST. First, in such tasks, participants are required to constantly switch back and forth from processing and maintenance of information. Because older adults are slower than younger adults to do so (e.g., Wasylyshyn, Verhaeghen, & Sliwinski, 2011), equating CL on the basis of RTs in a single task does not suppress the impact of this slower switching process, therefore CL is possibly still higher for older adults. Second, refreshing is supposed to be a controlled mechanism that can be divided in two subprocesses—initiation and refreshing per se (Johnson, 1992; Johnson, McCarthy, Muller, Brudner, & Johnson, 2015; Lemaire, Pageot, Plancher, & Portrat, 2017). Given that aging has been shown to be associated with a relative decrease in the processing resources that usually enable self-initiated processing (Craik, 1983; Luo & Craik, 2008), older adults may be impaired in the self-initiation of refreshing required in a CST. This hypothesis is consistent with electrophysiological evidence (Johnson et al., 2015). While the refreshing component relies on perceptual posterior cortical areas, the initiating component relies on frontal lobes—which are known to be impaired in healthy aging (Moscovitch & Winocur, 1995). A third possibility concerns item availability (Basak & Verhaeghen, 2011; Vaughan, Basak, Hartman, & Verhaeghen, 2008; Verhaeghen & Basak, 2005). Indeed, in order for refreshing to take place, items outside the focus of attention must first be retrieved and brought back into the focus of attention. Using mainly N-back tasks to investigate switching and aging, Verhaghen and colleagues found that once general slowing is taken into account, older adults are as efficient as younger adults to access information outside the focus of attention (i.e., the speed to search for information outside the focus of attention) but this information is less likely to still be available for processing. This age-related deficit in the availability of information could be due to a greater sensitivity of inter-item interference (see Plancher et al., 2017), a higher rate of time-based decay (but see Hoareau, Lemaire, Portrat, & Plancher, 2016 for contradictory results) and/or to a greater vulnerability to the presence of highly active competitors (i.e., prior refreshed items; Higgins & Johnson, 2009). Thus, it could be that older adults experience a deficit in refreshing because fewer items are available. This would echo Ward and Maylor’s (2005) qualitative finding concerning rehearsal: older adults refresh fewer items than younger adults. Finally, even when older adults are successful at bringing information back into the focus of attention, it is also possible that this process becomes slower with aging. In accordance with this view, related to the well-known age-related slowing of processing speed (Salthouse, 1996), a recent study based on computational modelling has suggested that refreshing a single item takes twice as much time for older adults (about 200 ms) than it does for younger adults (Hoareau et al., 2016). It thus could be that, in our study, older participants, being slower in refreshing, benefit less from increased free time. In conclusion, and although the present work strengthens the hypothesis that refreshing is a good candidate to account for WM age-related deficits, it should also motivate further studies to specify the locus for this refreshing deficit. Is it a matter of a slower switching process, a difficulty to self-initiate refreshing, the circulation of information in and out of the focus of attention or the time needed to enhance memory traces activation? Supplementary Material Supplementary data is available at The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences online. Funding This research was supported by a PhD grant allocated to the first author by the University of Savoie Mont-Blanc. Conflicts of Interest None reported. References Baddeley , A. D. , and Hitch , G. J . ( 1974 ). “Working memory,” in recent advances in learning and motivation (pp. 647 – 667 ). G. A. Bower (ed.). New York : Academic Press . Baddeley , A. , Lewis , V. , & Vallar , G . ( 1984 ). Exploring the articulatory loop . The Quarterly Journal of Experimental Psychology , 36 , 233 – 252 . doi:10.1080/14640748408402157 Google Scholar CrossRef Search ADS Baddeley , A. D. , Thomson , N. , and Buchanan , M . ( 1975 ). Word length and the structure of short-term memory . Journal of Verbal Learning and Verbal Behavior , 14 , 575 – 589 . doi:10.1016/S0022-5371(75)80045-4 Google Scholar CrossRef Search ADS Barrouillet , P. , Bernardin , S. , & Camos , V . ( 2004 ). Time constraints and resource sharing in adults’ working memory spans . Journal of Experimental Psychology: General , 133 , 83 – 100 . doi: https://doi.org/10.1037/0096-3445.133.1.83 Google Scholar CrossRef Search ADS PubMed Barrouillet , P. , Bernardin , S. , Portrat , S. , Vergauwe , E. , & Camos , V . ( 2007 ). Time and cognitive load in working memory . Journal of Experimental Psychology: Learning, Memory, and Cognition , 33 , 570 – 585 . doi: https://doi.org/10.1037/0278-7393.33.3.570 Google Scholar CrossRef Search ADS PubMed Barrouillet , P. , & Camos , V . ( 2015 ). Working memory: Loss and reconstruction . Hove, England : Psychology Press . Barrouillet , P. , Portrat , S. , & Camos , V . ( 2011 ). On the law relating processing to storage in working memory . Psychological Review , 118 , 175 – 192 . doi: https://doi.org/10.1037/a0022324 Google Scholar CrossRef Search ADS PubMed Basak , C. , & Verhaeghen , P . ( 2011 ). Aging and switching the focus of attention in working memory: Age differences in item availability but not in item accessibility . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 66 , 519 – 526 . doi: https://doi.org/10.1093/geronb/gbr028 Google Scholar CrossRef Search ADS Bates , D. , Maechler , M. , Bolker , B. , & Walker , S . ( 2015 ). Fitting linear mixed-effects models using lme4 . Journal of Statistical Software , 67 , 1 – 48 . doi: https://doi.org/10.18637/jss.v067.i01 Google Scholar CrossRef Search ADS Baumans , C. , Adam , S. , & Seron , X . ( 2012 ). Effect of cognitive load on working memory forgetting in aging . Experimental Psychology , 59 , 311 – 321 . doi: https://doi.org/10.1027/1618–3169/a000158 Google Scholar CrossRef Search ADS PubMed Bopp , K. L. , & Verhaeghen , P . ( 2005 ). Aging and verbal memory span: A meta-analysis . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 60 , 223 – 233 . doi: https://doi.org/10.1093/geronb/60.5.P223 Google Scholar CrossRef Search ADS Camos , V . ( 2015 ). Storing verbal information in working memory . Current Directions in Psychological Science , 24 , 440 – 445 . doi: https://doi.org/10.1177/0963721415606630 Google Scholar CrossRef Search ADS Camos , V. , Johnson , M. , Loaïza , V. , Portrat , S. , Souza , A. , & Vergauwe , E . ( in press ). What is attentional refreshing in working memory ? Annals of the New York Academy of Science . doi: https://doi.org/10.1111/nyas.13616 Camos , V. , & Portrat , S . ( 2015 ). The impact of cognitive load on delayed recall . Psychonomic Bulletin & Review , 22 , 1029 – 1034 . doi: https://doi.org/10.3758/s13423-014-0772-5 Google Scholar CrossRef Search ADS PubMed Conway , A. R. , Kane , M. J. , Bunting , M. F. , Hambrick , D. Z. , Wilhelm , O. , & Engle , R. W . ( 2005 ). Working memory span tasks: A methodological review and user’s guide . Psychonomic Bulletin & Review , 12 , 769 – 786 . doi:10.3758/BF03196772 Google Scholar CrossRef Search ADS PubMed Cowan , N . ( 1998 ). Attention and memory: An integrated framework. Oxford Psychology Series (No. 26) . New York : Oxford University Press . doi: https://doi.org/10.1093/acprof:oso/9780195119107.001.0001 Google Scholar CrossRef Search ADS Cowan , N . ( 1999 ). The differential maturation of two processing rates related to digit span . Journal of Experimental Child Psychology , 72 , 193 – 209 . doi: https://doi.org/10.1006/jecp.1998.2486 Google Scholar CrossRef Search ADS PubMed Craik , F. I. M . ( 1983 ). On the transfer of information from temporary to permanent memory . Philosophical Transactions of the Royal Society, London, Series B: Biological Sciences , 302 , 341 – 359 . doi:10.1098/rstb.1983.0059 Google Scholar CrossRef Search ADS Craik , F. I. M. , & Byrd , M . ( 1982 ). Aging and cognitive deficits: The role of attentional resources . In F. I. M. Craik , & S. Trehub (Eds.), Aging and cognitive processes (pp. 191 – 211 ). New York : Plenum . Google Scholar CrossRef Search ADS Gaillard , V. , Barrouillet , P. , Jarrold , C. , & Camos , V . ( 2011 ). Developmental differences in working memory: Where do they come from ? Journal of Experimental Child Psychology , 110 , 469 – 479 . doi: https://doi.org/10.1016/j.jecp.2011.05.004 Google Scholar CrossRef Search ADS PubMed Hasher , L. , & Zacks , R. T . ( 1988 ). Working memory, comprehension, and aging: A review and a new view . Psychology of Learning and Motivation , 22 , 193 – 225 . doi:10.1016/S0079-7421(08)60041-9 Google Scholar CrossRef Search ADS Higgins , J. A. , & Johnson , M. K . ( 2009 ). The consequence of refreshing for access to nonselected items in young and older adults . Memory & Cognition , 37 , 164 – 174 . doi: https://doi.org/10.3758/MC.37.2.164 Google Scholar CrossRef Search ADS PubMed Hoareau , V. , Lemaire , B. , Portrat , S. , & Plancher , G . ( 2016 ). Reconciling two computational models of working memory in aging . Topics in Cognitive Science , 8 , 264 – 278 . doi: https://doi.org/10.1111/tops.12184 Google Scholar CrossRef Search ADS PubMed Jaeger , T. F . ( 2008 ). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models . Journal of Memory and Language , 59 , 434 – 446 . doi: https://doi.org/10.1016/j.jml.2007.11.007 Google Scholar CrossRef Search ADS PubMed Jarjat , G. , Hoareau , V. , Plancher , G. , Hot , P. , Lemaire , B. and Portrat , S . ( 2018 ). What makes working memory traces stable over time ?. Annals of the New York Academy of Sciences . doi: https://doi.org/10.1111/nyas.13668 Johnson , M. K . ( 1992 ). MEM: Mechanisms of recollection . Journal of Cognitive Neuroscience , 4 , 268 – 280 . doi: https://doi.org/10.1162/jocn.1992.4.3.268 Google Scholar CrossRef Search ADS PubMed Johnson , M. R. , McCarthy , G. , Muller , K. A. , Brudner , S. N. , & Johnson , M. K . ( 2015 ). Electrophysiological correlates of refreshing: Event-related potentials associated with directing reflective attention to face, scene, or word representations . Journal of Cognitive Neuroscience , 27 , 1823 – 1839 . doi: https://doi.org/10.1162/jocn_a_00823 Google Scholar CrossRef Search ADS PubMed Johnson , M. K. , Mitchell , K. J. , Raye , C. L. , & Greene , E. J . ( 2004 ). An age-related deficit in prefrontal cortical function associated with refreshing information . Psychological Science , 15 , 127 – 132 . doi: https://doi.org/10.1111/j.0963-7214.2004.01502009.x Google Scholar CrossRef Search ADS PubMed Johnson , M. K. , Reeder , J. A. , Raye , C. L. , & Mitchell , K. J . ( 2002 ). Second thoughts versus second looks: An age-related deficit in reflectively refreshing just-activated information . Psychological Science , 13 , 64 – 67 . doi: https://doi.org/10.1111/1467-9280.00411 Google Scholar CrossRef Search ADS PubMed Kalafat , M. , Hugonot-Diener , L. , & Poitrenaud , J . ( 2003 ). Standardisation et étalonnage français du “Mini Mental State”(MMS) version GRECO . Revue De Neuropsychologie , 13 , 209 – 236 . Kane , M. J. , Hambrick , D. Z. , Tuholski , S. W. , Wilhelm , O. , Payne , T. W. , & Engle , R. W . ( 2004 ). The generality of working memory capacity: A latent-variable approach to verbal and visuospatial memory span and reasoning . Journal of Experimental Psychology: General , 133 , 189 – 217 . doi: https://doi.org/10.1037/0096-3445.133.2.189 Google Scholar CrossRef Search ADS PubMed Kuznetsova , A. , Brockhoff , P. B. , & Christensen , R. H. B . ( 2016 ). lmerTest: Tests in linear mixed effects models. R package version 2.0–32 . Retrieved from https://CRAN.R-project.org/package=lmerTest Kynette , D. , Kemper , S. , Norman , S. , & Cheung , H. T . ( 1990 ). Adults’ word recall and word repetition . Experimental Aging Research , 16 , 117 – 121 . doi: https://doi.org/10.1080/07340669008251538 Google Scholar CrossRef Search ADS PubMed Lemaire , B. , Pageot , A. , Plancher , G. , & Portrat , S . ( 2018 ) What is the time course of working memory attentional refreshing ? Psychonomic Bulletin and Review , 25 , 370 – 385 . doi: https://doi.org/10.3758/s13423-017-1282-z Google Scholar CrossRef Search ADS PubMed Loaiza , V. M. , & McCabe , D. P . ( 2013 ). The influence of aging on attentional refreshing and articulatory rehearsal during working memory on later episodic memory performance . Aging, Neuropsychology and Cognition , 20 , 471 – 493 . doi: https://doi.org/10.1080/13825585.2012.738289 Google Scholar CrossRef Search ADS Loaiza , V. M. , Rhodes , M. G. , & Anglin , J . ( 2015 ). The influence of age-related differences in prior knowledge and attentional refreshing opportunities on episodic memory . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 70 , 729 – 736 . doi: https://doi.org/10.1093/geronb/gbt119 Google Scholar CrossRef Search ADS Loaiza , V. M. and Souza , A. S . ( 2018 ), Is refreshing in working memory impaired in older age? Evidence from the retro‐cue paradigm . Annals of the New York Academy of Sciences . doi: https://doi.org/10.1111/nyas.13623 Luo , L. , & Craik , F. I . ( 2008 ). Aging and memory: A cognitive approach . Canadian Journal of Psychiatry , 53 , 346 – 353 . doi: https://doi.org/10.1177/070674370805300603 Google Scholar CrossRef Search ADS PubMed Moscovitch , M. , & Winocur , G . ( 1995 ). Frontal lobes, memory, and aging . Annals of the New York Academy of Sciences , 769 , 119 – 150 . doi:10.1111/j.1749-6632.1995.tb38135.x Google Scholar CrossRef Search ADS PubMed Park , D. C. , & Festini , S. B . ( 2017 ). Theories of memory and aging: A look at the past and a glimpse of the future . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 72 , 82 – 90 . doi: https://doi.org/10.1093/geronb/gbw066 Google Scholar CrossRef Search ADS Park , D. C. , Lautenschlager , G. , Hedden , T. , Davidson , N. S. , Smith , A. D. , & Smith , P. K . ( 2002 ). Models of visuospatial and verbal memory across the adult life span . Psychology and Aging , 17 , 299 – 320 . doi: https://doi.org/10.1037/0882-7974.17.2.299 Google Scholar CrossRef Search ADS PubMed Peters , F. , Majerus , S. , Olivier , L. , van der Linden , M. , Salmon , E. , & Collette , F . ( 2007 ). A multicomponent exploration of verbal short-term storage deficits in normal aging and Alzheimer’s disease . Journal of Clinical and Experimental Neuropsychology , 29 , 405 – 417 . doi: https://doi.org/10.1080/13803390600733064 Google Scholar CrossRef Search ADS PubMed Plancher , G. , Boyer , H. , Lemaire , B. , & Portrat , S . ( 2017 ). Under which conditions can older participants maintain information in working memory ? Experimental Aging Research , 43 , 409 – 429 . doi: https://doi.org/10.1080/0361073X.2017.1369730 Google Scholar CrossRef Search ADS PubMed Portrat , S. , Camos , V. , & Barrouillet , P . ( 2009 ). Working memory in children: A time-constrained functioning similar to adults . Journal of Experimental Child Psychology , 102 , 368 – 74 . doi: https://doi.org/10.1016/j.jecp.2008.05.005 Google Scholar CrossRef Search ADS PubMed Raye , C. L. , Johnson , M. K. , Mitchell , K. J. , Greene , E. J. , & Johnson , M. R . ( 2007 ). Refreshing: A minimal executive function . Cortex , 43 , 135 – 145 . doi:10.1016/S0010-9452(08)70451-9 Google Scholar CrossRef Search ADS PubMed Raye , C. L. , Mitchell , K. J. , Reeder , J. A. , Greene , E. J. , & Johnson , M. K . ( 2008 ). Refreshing one of several active representations: Behavioral and functional magnetic resonance imaging differences between young and older adults . Journal of Cognitive Neuroscience , 20 , 852 – 862 . doi: https://doi.org/10.1162/jocn.2008.20508 Google Scholar CrossRef Search ADS PubMed Richardson , J. T. E. , & Baddeley , A. D . ( 1975 ). The effect of articulatory suppression in free recall . Journal of Verbal Learning and Verbal Behavior , 14 , 623 – 629 . doi: https://doi.org/10.1016/S0022-5371 (75)80049-1 Google Scholar CrossRef Search ADS RStudio Team ( 2016 ). RStudio: Integrated development for R . Boston, MA : RStudio, Inc . Retrieved from http://www.rstudio.com/ Salthouse , T. A . ( 1996 ). The processing-speed theory of adult age differences in cognition . Psychological Review , 103 , 403 – 428 . doi: https://doi.org/10.1037/0033-295X.103.3.403 Google Scholar CrossRef Search ADS PubMed Souza , A. S . ( 2016 ). No age deficits in the ability to use attention to improve visual working memory . Psychology and Aging , 31 , 456 – 470 . doi: https://doi.org/10.1037/pag0000107 Google Scholar CrossRef Search ADS PubMed Tam , H. , Jarrold , C. , Baddeley , A. D. , & Sabatos-DeVito , M . ( 2010 ). The development of memory maintenance: Children’s use of phonological rehearsal and attentional refreshment in working memory tasks . Journal of Experimental Child Psychology , 107 , 306 – 324 . doi: https://doi.org/10.1016/j.jecp.2010.05.006 Google Scholar CrossRef Search ADS PubMed Vaughan , L. , Basak , C. , Hartman , M. , & Verhaeghen , P . ( 2008 ). Aging and working memory inside and outside the focus of attention: Dissociations of availability and accessibility . Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition , 15 , 703 – 724 . doi: https://doi.org/10.1080/13825580802061645 Google Scholar CrossRef Search ADS PubMed Vergauwe , E. , Barrouillet , P. , & Camos , V . ( 2010 ). Do mental processes share a domain-general resource ? Psychological Science , 21 , 384 – 390 . doi: https://doi.org/10.1177/0956797610361340 Google Scholar CrossRef Search ADS PubMed Vergauwe , E. , & Cowan , N . ( 2015 ). Attending to items in working memory: Evidence that refreshing and memory search are closely related . Psychonomic Bulletin & Review , 22 , 1001 – 1006 . doi: https://doi.org/10.3758/s13423-014-0755-6 Google Scholar CrossRef Search ADS PubMed Vergauwe , E. , & Langerock , N . ( 2017 ). Attentional refreshing of information in working memory: Increased immediate accessibility of just-refreshed representations . Journal of Memory and Language , 96 , 23 – 35 . doi:10.1016/j.jml.2017.05.001 Google Scholar CrossRef Search ADS Verhaeghen , P. , & Basak , C . ( 2005 ). Ageing and switching of the focus of attention in working memory: Results from a modified N-back task . The Quarterly Journal of Experimental Psychology. A, Human Experimental Psychology , 58 , 134 – 154 . doi: https://doi.org/10.1080/02724980443000241 Google Scholar CrossRef Search ADS PubMed Verhaeghen , P. , & Hoyer , W. J . ( 2007 ). Aging, focus switching, and task switching in a continuous calculation task : Evidence toward a new working memory control process . Aging, Neuropsychology, and Cognition , 14 , 22 – 39 . doi: https://doi.org/10.1080/138255890969357 Google Scholar CrossRef Search ADS Ward , G. , & Maylor , E. A . ( 2005 ). Age-related deficits in free recall: The role of rehearsal . The Quarterly Journal of Experimental Psychology. A, Human Experimental Psychology , 58 , 98 – 119 . doi: https://doi.org/10.1080/02724980443000223 Google Scholar CrossRef Search ADS PubMed Wasylyshyn , C. , Verhaeghen , P. , & Sliwinski , M. J . ( 2011 ). Aging and task switching: A meta-analysis . Psychology and Aging , 26 , 15 – 20 . doi: https://doi.org/10.1037/a0020912 Google Scholar CrossRef Search ADS PubMed Wechsler , D . ( 2008 ) Wechsler Adult Intelligence Scale – Fourth Edition . Pearson ; San Antonio, TX . © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journals of Gerontology Series B: Psychological Sciences and Social Sciences Oxford University Press

Aging Influences the Efficiency of Attentional Maintenance in Verbal Working Memory

Loading next page...
 
/lp/ou_press/aging-influences-the-efficiency-of-attentional-maintenance-in-verbal-QgmtlkE40v
Publisher
Oxford University Press
Copyright
© The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
ISSN
1079-5014
eISSN
1758-5368
D.O.I.
10.1093/geronb/gby067
Publisher site
See Article on Publisher Site

Abstract

Abstract Objectives Numerous studies reported an age-related deficit in verbal working memory (WM). Beyond the well-established general factors of cognitive aging, the alteration of the specific WM maintenance mechanisms may account for this deficit. This paper aims to investigate the hypothesis that WM attentional maintenance is impaired with age. Method In a WM task adapted to individual short-term memory and processing speed, younger and older participants maintained letters while verbally responding to a concurrent processing task, in order to constrain the use of rehearsal. Critically, the opportunity to use attentional maintenance was manipulated by varying the cognitive load (CL) of the concurrent processing via its nature and pace. Results Younger participants outperformed older participants and, in both groups, recall performance decreased as the CL increased. Importantly, in line with our predictions, the CL effect was modulated by age. Older adults benefited less from free pauses that allowed participants to engage in attentional maintenance of WM traces. Discussion Although still effective in normal aging, WM attentional maintenance seems to be altered. It could therefore be a good candidate to account for WM age-related deficits. Cognitive aging, Complex span task, Maintenance mechanisms, Working memory Working memory (WM) is defined as the immediate memory system that allows maintenance and manipulation of information in the service of ongoing complex cognitive activities (e.g., Kane et al., 2004). Its functioning is commonly assessed with a complex span task (CST) that requires participants to maintain a series of to-be-remembered items while concurrently engage in other processing activities (for a methodological review of CSTs, see Conway et al., 2005). It is well documented that older adults are less efficient than younger adults in these CSTs (Bopp & Verhaeghen, 2005; Park et al., 2002). General factors of cognitive aging have been proposed to affect WM functioning (e.g., decline of processing resources, Craik & Byrd, 1982; decrease of processing speed, Salthouse, 1996; inefficient inhibition, Hasher & Zacks, 1988, see Park & Festini, 2017 for a review of theories). In addition, one obvious aspect of WM functioning that should account for age-related differences in WM is the efficiency of the mechanisms being used to maintain the information in WM. Following the seminal model of Baddeley and Hitch (1974), the maintenance of verbal information in WM is commonly assumed to be underpinned by rehearsal (Baddeley, Lewis, & Vallar, 1984). However, there is now a large literature suggesting that, in addition to rehearsal, WM maintenance also relies on attention (e.g., Barrouillet, Portrat, & Camos, 2011; Cowan, 1998; Tam, Jarrold, Baddeley, & Sabatos-DeVito, 2010; Vergauwe & Langerock, 2017). The present study aimed to investigate age-related deficits in attentional maintenance of information in verbal WM by examining its consequences for recall performance in a CST. Rehearsal is assumed to be based on language-production processes that involve covert or overt repetition of the phonological representation of the to-be-remembered information. Two specific effects related to verbal constraints of rehearsal are documented in WM tasks: worse recall for lists of long words than for lists of short words (word-length effect, e.g., Baddeley, Thomson, & Buchanan, 1975) and worse recall when subjects have to continuously recite irrelevant sounds (concurrent articulation effect; e.g., Richardson & Baddeley, 1975). Although the word-length and concurrent articulation effects observed in older adults were commensurate with those observed in young adults (Loaiza & McCabe, 2013; Peters et al., 2007), suggesting that rehearsal is preserved with age, other studies have revealed both qualitative (e.g., number of different items being rehearsed, Ward & Maylor, 2005) and quantitative age-related differences in rehearsal (e.g., slowed articulation rate, Kynette, Kemper, Norman, & Cheung, 1990). A fairly recent body of research has highlighted the importance of attention for the maintenance of verbal information in WM. Several attentional mechanisms have been proposed in the literature, such as memory search (Cowan, 1999; Vergauwe & Cowan, 2015), refreshing (Johnson, 1992; Raye, Johnson, Mitchell, Greene, & Johnson, 2007), focus switching (Basak & Verhaeghen, 2011; Verhaeghen & Hoyer, 2007), and attentional refreshing (Barrouillet, Bernardin, & Camos, 2004; Barrouillet et al., 2011). Whether or not these different concepts refer to a single mechanism remains an open question (see Camos et al., in press) and is outside the scope of the present study. However, there is agreement on the existence of attention-based maintenance of information, which prolongs and/or increases the activation of WM information by briefly focusing attention on it (Barrouillet et al., 2011; Cowan, 1999; Johnson, 1992). Data from behavioral and neuroimaging studies strongly suggest that this attention-based maintenance is distinct from articulatory rehearsal (Cowan, 1999; Raye et al., 2007; see Camos, 2015 for a review). Whereas rehearsal is exclusively dedicated to the maintenance of verbal information and is thought to rely on subvocal articulation (which barely requires attention after the articulatory sequence has been initiated), attention-based maintenance relies on attention and is thought to act on information from different sensory modalities (i.e., verbal, visual, and spatial modalities). Consequently, this attention-based maintenance should be affected by attentional constraints imposed in WM tasks. In line with this assumption, many studies have shown that the variation of the proportion of time during which attention is available in a CST, through the manipulation of the number of to-be-processed items, the difficulty of the processing task, or the total time allowed to perform it, affects recall performance (e.g., Barrouillet et al., 2011; Portrat, Camos, & Barrouillet, 2009, Vergauwe, Barrouillet, & Camos, 2010). These results prompted the generation of the Time-Based Resource-Sharing model (TBRS, Barrouillet & Camos, 2015) of WM. In this model, attentional maintenance is underpinned by a mechanism called attentional refreshing, which counteracts, during the short pauses following each distracting activity in CSTs, the loss of information caused by concurrent processing. In this framework, the proportion of time during which attention is distracted from refreshing during the processing phase of a WM task is referred to as the cognitive load (CL). The manipulation of CL in CSTs has proven to be fruitful for investigating the use of refreshing in young adults (Barrouillet & Camos, 2015, for a review) as well as the developmental differences in children (Gaillard, Barrouillet, Jarrold & Camos, 2011). More specifically, Gaillard and colleagues (2011) showed that these differences could be accounted for by a development of the efficiency of refreshing with age. Indeed, in their second experiment, they observed that for equated CL, younger children took less advantage from the same periods of free time than older children, suggesting that younger children may be less efficient in refreshing. Yet, CL effect has not been extensively tested in the context of aging: to the best of our knowledge, only two studies have investigated the hypothesis of an age-related impairment in refreshing from a CL perspective (Baumans, Adam, & Seron, 2012; Plancher, Boyer, Lemaire, & Portrat, 2017). In Plancher and colleagues (2017), younger and older adults performed a CST in which they had to memorize a series of images while reading aloud words. The pace of the to-be-read words was varied (slow vs fast) as well as the degree of interference induced by these words (repeated words vs all new words within a trial). While the recall performance of young participants elicited an easy-to-interpret pattern with a classical pace effect but no interference effect, older participants also performed better at slow pace than at fast pace but only when the amount of interference was low. The authors concluded that a decrease in WM performance with aging can be explained by a difficulty in taking advantage of WM maintenance opportunities, especially in conditions of high interference. In their study, Baumans and colleagues (2012) had younger and older adults perform a CST in which participants had to maintain series of letters, presented first, before performing a processing task that consisted of judging the color of digits. Then, participants had to recall the letters in the correct order. The pace of the digits was varied to manipulate the CL of the processing task. The results showed that while a small CL variation had no effect on older adults (Experiment 1), a large CL manipulation had the same detrimental effect on recall performance for both age groups (Experiment 2). As acknowledged by the authors themselves, these results preclude a “definitive” conclusion in term of refreshing. Although a small variation of CL has been shown to affect WM performance in younger adults (e.g., Barrouillet, Bernardin, Portrat, Vergauwe, & Camos, 2007), Baumans and colleagues did not find such a pattern in older adults (Experiment 1). This result could count as evidence in favor of a lower sensitivity of older adults to the CL effect and therefore in favor of an age-related deficit of refreshing. This interpretation would be in line with other studies suggesting such a deficit using different verbal memory tasks (delayed recognition test, Johnson, Reeder, Raye, & Mitchell, 2002; Johnson, Mitchell, Raye, & Greene, 2004; Raye, Mitchell, Reeder, Greene, & Johnson, 2008; delayed free recall, Loaiza & McCabe, 2013; Loaiza, Rhodes, & Anglin, 2015). However, as mentioned above, Baumans and colleagues (2012) also observed that equivalent large manipulations of CL across groups had a similar effect on recall performance for both age groups (Experiment 2), a result that goes against an age-related refreshing deficit. This result is at odd with the body of research developed by Johnson and colleagues but is in line with recent studies (Loaiza & Souza, in press; Souza, 2016). For instance, in her study, Souza (2016) found that older and younger adults benefited to the same extent from retro-cue displayed during the maintenance phase of a visual WM task. To summarize, the current literature does not offer clear evidence in favor of an age-related deficit in refreshing. The aim of the present study was therefore to further investigate this hypothesis by having younger and older adults performing an adapted computer-paced CST in which the CL of the processing task was varied through its nature (parity and location judgment) and pace (slow and fast). Moreover, participants had to perform this task under articulatory constraints in order to minimize the use of rehearsal. Indeed, the CL effects observed in Baumans’ study could be attributed, at least in part, to a different involvement of rehearsal across conditions since participants had to maintained letters in the face of a silent concurrent processing task. The WM task was adapted to control for possible age differences in short-term memory and processing speed. According to an age-related deficit in refreshing hypothesis, we predicted that older adults should be less affected by the manipulation of CL than younger adults. Indeed, if refreshing is less efficient with age, as suggested by several evidences in the literature, then older adults should benefit less from increased free time, thereby leading to greater differences between age groups as CL decreases. METHOD Participants Twenty-four undergraduate students (four males) aged between 18 and 28 years (M = 21.2, SD = 2.2) and 24 older adults (six males) aged between 60 and 84 years (M = 69.5, SD = 6.1) participated in the study, which was approved by an ethics committee (CERNI, IRB00010290, 2015-11-10-4). All participants were volunteers, were native French speakers, had normal or corrected-to-normal vision, had no neurological background, and provided written informed consent before taking part in the study. After the experimental session, older participants were screened to rule out dementia by means of the Mini-Mental State Examination (Kalafat, Hugonot-Diener, & Poitrenaud, 2003). Older participants were recruited either from social centers or from previous studies carried out in our laboratory. Students received partial course credit for participating. Materials and Procedure All tasks were displayed on a laptop by using E-Prime 2.0 software (Psychology Software Tools, Pittsburgh, PA). First, participants performed a short-term span task (Figure 1A) designed to calibrate the memory load in the subsequent WM task. The computer-paced series of consonants to be memorized were displayed on the computer screen. We used all the consonants except W, which is trisyllabic in French. The various consonants were displayed at approximately the same frequency throughout the task, after controlling for their position within the lists. Within a single series, a consonant was never repeated. Acronyms and alphabetically ordered series were avoided. Each trial began with a screen indicating the number of letters to be remembered. The first trial was set to two consonants. A central fixation point was then displayed on the screen for 500 ms, followed by the first letter of the sequence. Letters (in Courier New font) were displayed in the center of the screen for 700 ms, and then replaced after a 300 ms delay. Participants had to read each letter aloud. At the end of each sequence, the word “Rappel” (recall, in French) appeared on the screen; this indicated to the participant that he or she had to verbally recall the consonants in the correct order. The experimenter noted the participant’s recall, and then pressed the “Enter” key if all the consonants had been recalled in the correct order or any other key on the keyboard if not. There were two trials for each list length. The task ended when the participant failed to recall both trials of a given length. As conventionally assessed, the short-term span corresponded to the greatest length for which the participant had recalled at least one series in the correct order (see Wechsler, 2008, Longest Span Scores). Figure 1. View largeDownload slide (A) Illustration of the short-term memory span task. (B) Illustration of the processing speed tasks. Figure 1. View largeDownload slide (A) Illustration of the short-term memory span task. (B) Illustration of the processing speed tasks. Next, the participants’ processing speed was evaluated in a parity/location judgement task (Figure 1B). Two tasks (location and parity) were displayed at two paces (fast and slow), resulting in four conditions. The conditions were randomly presented. Each consisted of a block of twenty successive stimuli to be processed. The stimuli were digits ranging from “1” to “10”, and they were displayed on the screen randomly in either a lower or an upper position (80% and 20%, respectively of the screen’s Y-axis). In the location task, participants had to judge the position of the digits (saying “up” or “down”). In the parity task, they had to judge the parity of the digits (saying “even” or “odd”). Each trial began with a screen indicating the task to be performed (parity or location) and the pace (slow or fast). After the participant pressed a key on the keyboard, a central fixation point was displayed on the screen for 500 ms, followed by the first digit. In the fast-paced condition, digits were displayed for 700 ms and replaced after 350 ms. In the slow-paced condition, digits were displayed for 1,200 ms and followed by a 600 ms delay. Participants were given the full time period (presentation plus delay) to give their responses, which were recorded with a vocal key connected to a serial response box. The experimenter marked the participants’ responses. The mean reaction time for each condition was calculated after excluding reaction times below 200 ms. Lastly, participants had to perform a computer-paced CST that combined letters to be memorized with a digit processing task (Figure 2). The series of consonants to be maintained and stimuli to be processed had the same restrictive characteristics as in the short-term span task and the processing speed task, respectively. The CL was varied across four experimental conditions in which the type of processing (location or parity) and pace of processing (fast or slow) was manipulated. The various experimental conditions were presented in random order, and each consisted of five successive trials. Each trial began with a screen indicating the processing task (“L” for location or “P” for parity) and the pace (“S” for slow or “F” for fast). After the participant pressed a key on the keyboard, a central fixation point was displayed on the screen for 500 ms, followed by the first letter in the sequence. Letters were displayed at the center of the screen for 1,200 ms, and participants had to read them aloud. After a 300 ms delay, four digits appeared randomly on the lower or upper part of the screen. After the last delay following the last digit, the second letter appeared, and so on until the end of the sequence. Throughout the session, the length of the series to be remembered was set to the short-term span of each participant. At the end of each sequence, the word “Rappel” (recall) appeared on the screen—indicating that the participant had to verbally recall the consonants in the correct order. The experimenter marked participants’ responses and then pressed a key on the keyboard to continue to the next trial. Figure 2. View largeDownload slide Illustration of the time course of two trials in the working memory span task: a “location” trial in the slow-paced condition (L/S, upper panel), and a “parity” trial in the fast-paced condition (P/F, lower panel). Td refers to the time delay following each distractor, and pT refers to the distractor presentation time. Figure 2. View largeDownload slide Illustration of the time course of two trials in the working memory span task: a “location” trial in the slow-paced condition (L/S, upper panel), and a “parity” trial in the fast-paced condition (P/F, lower panel). Td refers to the time delay following each distractor, and pT refers to the distractor presentation time. In the fast-paced and slow-paced conditions, digits were displayed for 700 ms and 1,200 ms, respectively. The delay between two digits (denoted as “Td” in the figure) was specific for each participant, in order to standardize the CL across individuals. Indeed, the CL correspond to CL =a/(pT + Td) where a is the time during which a distractor captures attention, pT is the distractor presentation time (700 and 1,200 ms for fast- and slow-paced conditions, respectively), and Td is the duration of the delay following the distractor. Thus, it is possible to find the specific value of Td if one knows the values of the other parameters (Td = a/CL-pT). Given that we were testing for an interaction between age group and CL, we wanted to achieve a high degree of variation in the CL. However, the task also had to be manageable for the participants. Thus, we wanted the most difficult condition to elicit a CL of around 0.65 and the easiest condition to elicit a CL of around 0.25. On the basis of the literature (e.g., Barrouillet et al., 2007) and a pilot study, we expected the parity judgement to elicit longer RTs. Thus, in the fast-paced conditions, parameter a corresponded to the mean reaction time of the participant in the parity tasks (slow and fast) measured beforehand in the processing speed tasks. In the slow-paced conditions, parameter a corresponded to the participant’s mean reaction time in the location tasks. Thus, the fast and slow paces were adjusted for each participant. Participants were given the full time period (presentation plus delay) to give their responses, which were recorded with a vocal key connected to a serial response box. The use of rehearsal was constrained by asking participant to verbally respond to the processing task. Accuracy and reaction times for the processing tasks were recorded, together with the number of letters recalled in the correct order. The measured CL in each condition was calculated by dividing the mean reaction time for a correct response in the processing task by the total available response time (i.e., presentation plus delay). The experimental session was preceded by a training phase in which participants performed two random CST trials (parity/fast and location/slow). Data Analysis Statistical analyses were conducted by using RStudio version 1.0.143 for Windows (RStudio Team, 2016) with the R package lme4 (Bates, Maechler, Bolker, & Walker, 2015). To obtain the p values from multilevel models, we used the Satterthwaite approximation of degrees of freedom, which is implemented in the lmerTest package (Kuznetsova, Brockhoff, & Christensen, 2016). Our main analysis was focused on the memory performance on the WM task; therefore, we computed the number of letters recalled in correct position in each condition for each participant. Moreover, we computed the mean reaction time to respond to the processing component of the WM task in each of the four conditions by taking into account correct responses only. These mean reaction times for each condition were computed for each participant, thus we were able to compute the measured CL elicited by our experimental manipulations for each participant using the equation: CL = reaction time/(presentation time + delay). RESULTS Short-term Span Task There was no difference in short-term spans between the two groups (t < 1), with performance ranging from 4 to 7 for both young (M = 5.42, SD = 0.93) and older adults (M = 5.42, SD = 0.72). Processing Speed Task Reaction times below 200 ms were disregarded for this analysis (accounting for 10% and 8% of the data for older and younger adults, respectively). Reaction times were analyzed by fitting a mixed effect linear model including Group (younger vs older adults), Task (Parity vs Location) and Pace (Slow vs Fast) as fixed effects and Participant as a random factor (accounting for the multiple response measures per participant). The results of the analyses (see Table 1) revealed significant effects of Task (t(137.9) = 28.81, p < .001) and Pace (t(137.9) = 4.94, p < .001). All other effects were not significant (p > .1). Table 1. Mean Reaction Times and Accuracy in the Processing Speed Task (95% within-subject confidence intervals) As a Function of Experimental Conditions and Groups Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) View Large Table 1. Mean Reaction Times and Accuracy in the Processing Speed Task (95% within-subject confidence intervals) As a Function of Experimental Conditions and Groups Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) Location slow Location fast Parity slow Parity fast Reaction Times (ms) Young 425 (24) 390 (18) 675 (23) 638 (28) Older 432 (28) 403 (20) 679 (26) 615 (26) Accuracy Young 99.7 (1.2) 99.2 (1.1) 97.5 (1.1) 93.5 (2.4) Older 99 (0.7) 98.1 (0.9) 97.5 (1.2) 95.3 (1.7) View Large WM Performance As a Function of the Pace and the Nature of the Processing Task All of the 192 data values collected in the WM task (48 participants × 4 conditions) were included in the analyses as participants performed well on the distracting task (min = 74% accuracy). Ordered recall performance was analyzed by fitting a mixed effect logistic model, as recommended by Jaeger (2008), while the measured CL was analyzed by fitting a mixed effect linear model. Both models included Group, Task and Pace as fixed effects and Participant as a random factor. Results of the analyses revealed a significant effect of Group on recall performance (Wald Z = 3.75, odds ratio [OR] = 1.92, p < .001), with younger adults (M = 53.9%, SD = 23.4) outperforming older adults (M = 38.6%, SD = 13.9), but this factor was not significant on the measured CL (p = .47). There was also a significant effect of Pace on both recall performance (Wald Z = 9.54, OR = 1.77, p < .001) and measured CL (t(138) = −22.4, p < .001). In line with numerous previous results, the Fast condition elicited worse recall performance than the Slow condition (M = 39.8% and 52.8%, SD = 18.8 and 16.5, respectively) and, as planned, resulted in a higher measured CL than the Slow condition (M = 0.59 and 0.42, SD = 0.11 and 0.11, respectively). The same pattern of results was observed for the effect of Task on both recall performance (Wald Z = −8.95, OR = 0.59, p < .001) and measured CL (t(138) = 15.8, p < .001). More precisely, the Parity condition elicited a higher CL than the Location condition (M = 0.57 and 0.44; SD = 0.14 and 0.14, respectively) and resulted in worse recall (M = 40.4% and 52.2%, SD = 18.4 and 17.9, respectively). Most importantly, there was a significant interaction between Task and Group on recall performance (Wald Z = −3.53, OR = 0.66, p < .001), with a greater recall difference between the two tasks for younger (16.2%) than older adults (7.3%). However, there was also a significant interaction between these factors on measured CL (t(138) = 2.4, p = .015), with a greater difference in CL between the parity and location tasks for younger (0.14) than older adults (0.10). This last outcome was unexpected since our procedure was designed precisely to keep the CL constant between the two groups. Unfortunately, it prevented us from concluding in favor of an age-related refreshing deficit hypothesis because a differential CL effect between groups could have explained the decisive Group x Task interaction on recall performance. Hence, to test our hypothesis, we directly used the measured CL elicited by the conditions as a continuous predictor of recall performance. WM Performance As a Function of the CL of the Processing Task We fitted a mixed effect logistic model including Group and measured CL as fixed effects and Participant as a random factor. Results of the analyses, summarized in Table 2, revealed a significant effect of measured CL (Wald Z = −12.1, OR = 0.044, p < .001) and Group (Wald Z = 4.79, OR = 4.44, p < .001) and a significant interaction between measured CL and Group (Wald Z = −3.33, OR = 0.18, p < .001). As predicted, recall performance increased as CL decreased, younger adults outperformed older adults, and older adults were less affected by the modulation of CL (Figure 3). Table 2. Summary of the Recall Performance Model Fitted on Data With Coefficient Estimates, SE, Wald Z Values, p Values, OR, and 95% CI Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Note: Coef = Coefficient estimate; CI = Confidence interval; CL = Cognitive load; OR = Odds ratio; SE = Standard error. View Large Table 2. Summary of the Recall Performance Model Fitted on Data With Coefficient Estimates, SE, Wald Z Values, p Values, OR, and 95% CI Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Predictors Coef SE Wald Z p OR 95% CI CL −3.12 (0.26) −12.01 <.001 0.04 (0.03; 0.07) Group 1.49 (0.31) 4.79 <.001 4.44 (2.41; 8.19) CL × Group −1.72 (0.52) −3.33 <.001 0.18 (0.07; 0.49) Note: Coef = Coefficient estimate; CI = Confidence interval; CL = Cognitive load; OR = Odds ratio; SE = Standard error. View Large Figure 3. View largeDownload slide The proportion of letters recalled in the correct order as a function of the task’s cognitive load in the two age groups (older and younger adults), along with the mixed logistic model built for recall performance (including the significant effects of Group and Cognitive Load, and the interaction between the two). Figure 3. View largeDownload slide The proportion of letters recalled in the correct order as a function of the task’s cognitive load in the two age groups (older and younger adults), along with the mixed logistic model built for recall performance (including the significant effects of Group and Cognitive Load, and the interaction between the two). Discussion There is currently a growing consensus among researchers whereby attentional maintenance supplements the phonological maintenance of verbal information in WM. This attentional maintenance is thought to prolong and/or increase the activation of perceptual information that has disappeared by briefly focusing attention on it—thereby preventing its loss from WM (Barrouillet et al., 2004; Cowan, 1998; Johnson, 1992). Moreover, attentional maintenance also plays a role in the stabilization of information in longer term memory (Camos & Portrat, 2015; Jarjat et al., in press; Johnson et al., 2002; Loaiza & McCabe, 2013). However, whether attentional maintenance corresponds to a set of different mechanisms (i.e., memory search, Vergauwe & Cowan, 2015; refreshing, Johnson, 1992; focus switching, Basak & Verhaeghen, 2011; attentional refreshing, Barrouillet et al., 2011); or to a single mechanism with different names in the literature remains an open question (see Camos et al., in press). In the present study, we adopted the TBRS model of attentional maintenance (referred to as refreshing), which is thought to increase the activation of WM information during the short pauses following each distracting activity in CSTs (Barrouillet et al., 2004). While several studies have shown that the beneficial effect of attentional maintenance is reduced with age (Johnson et al., 2002; Loaiza & McCabe, 2013; Loaiza, et al., 2015; Raye et al., 2008), thus suggesting that it is impaired with age, there are also evidences that attentional maintenance might be preserved with age (Baumans et al., 2012, Experiment 2; Loaiza & Souza, in press; Souza, 2016). The aim of this study was therefore to further investigate the hypothesis that there is an age-related impairment in refreshing (Barrouillet et al., 2004) that contributes to the understanding of the well-known age-related decline in verbal WM (Bopp & Verhaeghen, 2005; Park et al., 2002). To do so, younger and older adults were asked to perform a CST in which the opportunity to use refreshing was manipulated by varying the CL of the task while the use of rehearsal was constrained. By introducing articulatory constraints into our paradigm, we found evidence against the hypothesis that younger and older adults show comparable CL effects—something that Baumans and colleagues (2012) did not observe in their “silent task” paradigm. In contrast to Baumans and colleagues (2012), we found that older adults benefited less from a decrease in CL than younger adults did. These results suggest that the two groups benefitted to a different extent from free time for WM maintenance. However, the participants could have used free time to rehearse instead of refresh. Indeed, as an anonymous reviewer suggested, our participants were not asked to continually articulate an irrelevant sound after having given their response aloud; this type of control would have been necessary to totally suppress articulatory rehearsal. We therefore ran a control experiment (see Supplementary Materials) in which younger and older adults were asked to perform a CST with strict articulatory suppression. We observed an age-related difference in WM performance even under conditions when only attentional maintenance could take place. This finding confirmed that the outcomes of the present study cannot be attributed solely to an age-related difference in rehearsal. Thus, asking participants to respond verbally in the concurrent task (as we did) probably reduces reliance on articulatory rehearsal, relative to the Baumans and colleagues (2012) study. In turn, this enabled us observe the critical interaction between CL and age. The hypothesis whereby the CL × age interaction depends on the incentive to rely on rehearsal would be strengthened by a within-subject comparison of silent versus articulatory suppression conditions. Given that our paradigm was adjusted to the participants’ short-term span and processing speed, the interaction cannot be interpreted with regard to age-related disparities in the task’s difficulty. Hence, in line with other studies (Johnson et al., 2002; Loaiza & McCabe, 2013; Loaiza, et al., 2015; Raye et al., 2008), our findings reflect an age-related impairment in the use of attention to maintain information. More precisely, and given the paradigm used here (i.e., a variation in the proportion of free time following each distracting activity in a CST), attentional refreshing is most likely to be involved (Barrouillet et al., 2004). Four hypotheses, not necessarily exclusive, could account for this age-related deficit in refreshing. Each of these hypotheses relies on a necessary step that refreshing implies within CST. First, in such tasks, participants are required to constantly switch back and forth from processing and maintenance of information. Because older adults are slower than younger adults to do so (e.g., Wasylyshyn, Verhaeghen, & Sliwinski, 2011), equating CL on the basis of RTs in a single task does not suppress the impact of this slower switching process, therefore CL is possibly still higher for older adults. Second, refreshing is supposed to be a controlled mechanism that can be divided in two subprocesses—initiation and refreshing per se (Johnson, 1992; Johnson, McCarthy, Muller, Brudner, & Johnson, 2015; Lemaire, Pageot, Plancher, & Portrat, 2017). Given that aging has been shown to be associated with a relative decrease in the processing resources that usually enable self-initiated processing (Craik, 1983; Luo & Craik, 2008), older adults may be impaired in the self-initiation of refreshing required in a CST. This hypothesis is consistent with electrophysiological evidence (Johnson et al., 2015). While the refreshing component relies on perceptual posterior cortical areas, the initiating component relies on frontal lobes—which are known to be impaired in healthy aging (Moscovitch & Winocur, 1995). A third possibility concerns item availability (Basak & Verhaeghen, 2011; Vaughan, Basak, Hartman, & Verhaeghen, 2008; Verhaeghen & Basak, 2005). Indeed, in order for refreshing to take place, items outside the focus of attention must first be retrieved and brought back into the focus of attention. Using mainly N-back tasks to investigate switching and aging, Verhaghen and colleagues found that once general slowing is taken into account, older adults are as efficient as younger adults to access information outside the focus of attention (i.e., the speed to search for information outside the focus of attention) but this information is less likely to still be available for processing. This age-related deficit in the availability of information could be due to a greater sensitivity of inter-item interference (see Plancher et al., 2017), a higher rate of time-based decay (but see Hoareau, Lemaire, Portrat, & Plancher, 2016 for contradictory results) and/or to a greater vulnerability to the presence of highly active competitors (i.e., prior refreshed items; Higgins & Johnson, 2009). Thus, it could be that older adults experience a deficit in refreshing because fewer items are available. This would echo Ward and Maylor’s (2005) qualitative finding concerning rehearsal: older adults refresh fewer items than younger adults. Finally, even when older adults are successful at bringing information back into the focus of attention, it is also possible that this process becomes slower with aging. In accordance with this view, related to the well-known age-related slowing of processing speed (Salthouse, 1996), a recent study based on computational modelling has suggested that refreshing a single item takes twice as much time for older adults (about 200 ms) than it does for younger adults (Hoareau et al., 2016). It thus could be that, in our study, older participants, being slower in refreshing, benefit less from increased free time. In conclusion, and although the present work strengthens the hypothesis that refreshing is a good candidate to account for WM age-related deficits, it should also motivate further studies to specify the locus for this refreshing deficit. Is it a matter of a slower switching process, a difficulty to self-initiate refreshing, the circulation of information in and out of the focus of attention or the time needed to enhance memory traces activation? Supplementary Material Supplementary data is available at The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences online. Funding This research was supported by a PhD grant allocated to the first author by the University of Savoie Mont-Blanc. Conflicts of Interest None reported. References Baddeley , A. D. , and Hitch , G. J . ( 1974 ). “Working memory,” in recent advances in learning and motivation (pp. 647 – 667 ). G. A. Bower (ed.). New York : Academic Press . Baddeley , A. , Lewis , V. , & Vallar , G . ( 1984 ). Exploring the articulatory loop . The Quarterly Journal of Experimental Psychology , 36 , 233 – 252 . doi:10.1080/14640748408402157 Google Scholar CrossRef Search ADS Baddeley , A. D. , Thomson , N. , and Buchanan , M . ( 1975 ). Word length and the structure of short-term memory . Journal of Verbal Learning and Verbal Behavior , 14 , 575 – 589 . doi:10.1016/S0022-5371(75)80045-4 Google Scholar CrossRef Search ADS Barrouillet , P. , Bernardin , S. , & Camos , V . ( 2004 ). Time constraints and resource sharing in adults’ working memory spans . Journal of Experimental Psychology: General , 133 , 83 – 100 . doi: https://doi.org/10.1037/0096-3445.133.1.83 Google Scholar CrossRef Search ADS PubMed Barrouillet , P. , Bernardin , S. , Portrat , S. , Vergauwe , E. , & Camos , V . ( 2007 ). Time and cognitive load in working memory . Journal of Experimental Psychology: Learning, Memory, and Cognition , 33 , 570 – 585 . doi: https://doi.org/10.1037/0278-7393.33.3.570 Google Scholar CrossRef Search ADS PubMed Barrouillet , P. , & Camos , V . ( 2015 ). Working memory: Loss and reconstruction . Hove, England : Psychology Press . Barrouillet , P. , Portrat , S. , & Camos , V . ( 2011 ). On the law relating processing to storage in working memory . Psychological Review , 118 , 175 – 192 . doi: https://doi.org/10.1037/a0022324 Google Scholar CrossRef Search ADS PubMed Basak , C. , & Verhaeghen , P . ( 2011 ). Aging and switching the focus of attention in working memory: Age differences in item availability but not in item accessibility . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 66 , 519 – 526 . doi: https://doi.org/10.1093/geronb/gbr028 Google Scholar CrossRef Search ADS Bates , D. , Maechler , M. , Bolker , B. , & Walker , S . ( 2015 ). Fitting linear mixed-effects models using lme4 . Journal of Statistical Software , 67 , 1 – 48 . doi: https://doi.org/10.18637/jss.v067.i01 Google Scholar CrossRef Search ADS Baumans , C. , Adam , S. , & Seron , X . ( 2012 ). Effect of cognitive load on working memory forgetting in aging . Experimental Psychology , 59 , 311 – 321 . doi: https://doi.org/10.1027/1618–3169/a000158 Google Scholar CrossRef Search ADS PubMed Bopp , K. L. , & Verhaeghen , P . ( 2005 ). Aging and verbal memory span: A meta-analysis . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 60 , 223 – 233 . doi: https://doi.org/10.1093/geronb/60.5.P223 Google Scholar CrossRef Search ADS Camos , V . ( 2015 ). Storing verbal information in working memory . Current Directions in Psychological Science , 24 , 440 – 445 . doi: https://doi.org/10.1177/0963721415606630 Google Scholar CrossRef Search ADS Camos , V. , Johnson , M. , Loaïza , V. , Portrat , S. , Souza , A. , & Vergauwe , E . ( in press ). What is attentional refreshing in working memory ? Annals of the New York Academy of Science . doi: https://doi.org/10.1111/nyas.13616 Camos , V. , & Portrat , S . ( 2015 ). The impact of cognitive load on delayed recall . Psychonomic Bulletin & Review , 22 , 1029 – 1034 . doi: https://doi.org/10.3758/s13423-014-0772-5 Google Scholar CrossRef Search ADS PubMed Conway , A. R. , Kane , M. J. , Bunting , M. F. , Hambrick , D. Z. , Wilhelm , O. , & Engle , R. W . ( 2005 ). Working memory span tasks: A methodological review and user’s guide . Psychonomic Bulletin & Review , 12 , 769 – 786 . doi:10.3758/BF03196772 Google Scholar CrossRef Search ADS PubMed Cowan , N . ( 1998 ). Attention and memory: An integrated framework. Oxford Psychology Series (No. 26) . New York : Oxford University Press . doi: https://doi.org/10.1093/acprof:oso/9780195119107.001.0001 Google Scholar CrossRef Search ADS Cowan , N . ( 1999 ). The differential maturation of two processing rates related to digit span . Journal of Experimental Child Psychology , 72 , 193 – 209 . doi: https://doi.org/10.1006/jecp.1998.2486 Google Scholar CrossRef Search ADS PubMed Craik , F. I. M . ( 1983 ). On the transfer of information from temporary to permanent memory . Philosophical Transactions of the Royal Society, London, Series B: Biological Sciences , 302 , 341 – 359 . doi:10.1098/rstb.1983.0059 Google Scholar CrossRef Search ADS Craik , F. I. M. , & Byrd , M . ( 1982 ). Aging and cognitive deficits: The role of attentional resources . In F. I. M. Craik , & S. Trehub (Eds.), Aging and cognitive processes (pp. 191 – 211 ). New York : Plenum . Google Scholar CrossRef Search ADS Gaillard , V. , Barrouillet , P. , Jarrold , C. , & Camos , V . ( 2011 ). Developmental differences in working memory: Where do they come from ? Journal of Experimental Child Psychology , 110 , 469 – 479 . doi: https://doi.org/10.1016/j.jecp.2011.05.004 Google Scholar CrossRef Search ADS PubMed Hasher , L. , & Zacks , R. T . ( 1988 ). Working memory, comprehension, and aging: A review and a new view . Psychology of Learning and Motivation , 22 , 193 – 225 . doi:10.1016/S0079-7421(08)60041-9 Google Scholar CrossRef Search ADS Higgins , J. A. , & Johnson , M. K . ( 2009 ). The consequence of refreshing for access to nonselected items in young and older adults . Memory & Cognition , 37 , 164 – 174 . doi: https://doi.org/10.3758/MC.37.2.164 Google Scholar CrossRef Search ADS PubMed Hoareau , V. , Lemaire , B. , Portrat , S. , & Plancher , G . ( 2016 ). Reconciling two computational models of working memory in aging . Topics in Cognitive Science , 8 , 264 – 278 . doi: https://doi.org/10.1111/tops.12184 Google Scholar CrossRef Search ADS PubMed Jaeger , T. F . ( 2008 ). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models . Journal of Memory and Language , 59 , 434 – 446 . doi: https://doi.org/10.1016/j.jml.2007.11.007 Google Scholar CrossRef Search ADS PubMed Jarjat , G. , Hoareau , V. , Plancher , G. , Hot , P. , Lemaire , B. and Portrat , S . ( 2018 ). What makes working memory traces stable over time ?. Annals of the New York Academy of Sciences . doi: https://doi.org/10.1111/nyas.13668 Johnson , M. K . ( 1992 ). MEM: Mechanisms of recollection . Journal of Cognitive Neuroscience , 4 , 268 – 280 . doi: https://doi.org/10.1162/jocn.1992.4.3.268 Google Scholar CrossRef Search ADS PubMed Johnson , M. R. , McCarthy , G. , Muller , K. A. , Brudner , S. N. , & Johnson , M. K . ( 2015 ). Electrophysiological correlates of refreshing: Event-related potentials associated with directing reflective attention to face, scene, or word representations . Journal of Cognitive Neuroscience , 27 , 1823 – 1839 . doi: https://doi.org/10.1162/jocn_a_00823 Google Scholar CrossRef Search ADS PubMed Johnson , M. K. , Mitchell , K. J. , Raye , C. L. , & Greene , E. J . ( 2004 ). An age-related deficit in prefrontal cortical function associated with refreshing information . Psychological Science , 15 , 127 – 132 . doi: https://doi.org/10.1111/j.0963-7214.2004.01502009.x Google Scholar CrossRef Search ADS PubMed Johnson , M. K. , Reeder , J. A. , Raye , C. L. , & Mitchell , K. J . ( 2002 ). Second thoughts versus second looks: An age-related deficit in reflectively refreshing just-activated information . Psychological Science , 13 , 64 – 67 . doi: https://doi.org/10.1111/1467-9280.00411 Google Scholar CrossRef Search ADS PubMed Kalafat , M. , Hugonot-Diener , L. , & Poitrenaud , J . ( 2003 ). Standardisation et étalonnage français du “Mini Mental State”(MMS) version GRECO . Revue De Neuropsychologie , 13 , 209 – 236 . Kane , M. J. , Hambrick , D. Z. , Tuholski , S. W. , Wilhelm , O. , Payne , T. W. , & Engle , R. W . ( 2004 ). The generality of working memory capacity: A latent-variable approach to verbal and visuospatial memory span and reasoning . Journal of Experimental Psychology: General , 133 , 189 – 217 . doi: https://doi.org/10.1037/0096-3445.133.2.189 Google Scholar CrossRef Search ADS PubMed Kuznetsova , A. , Brockhoff , P. B. , & Christensen , R. H. B . ( 2016 ). lmerTest: Tests in linear mixed effects models. R package version 2.0–32 . Retrieved from https://CRAN.R-project.org/package=lmerTest Kynette , D. , Kemper , S. , Norman , S. , & Cheung , H. T . ( 1990 ). Adults’ word recall and word repetition . Experimental Aging Research , 16 , 117 – 121 . doi: https://doi.org/10.1080/07340669008251538 Google Scholar CrossRef Search ADS PubMed Lemaire , B. , Pageot , A. , Plancher , G. , & Portrat , S . ( 2018 ) What is the time course of working memory attentional refreshing ? Psychonomic Bulletin and Review , 25 , 370 – 385 . doi: https://doi.org/10.3758/s13423-017-1282-z Google Scholar CrossRef Search ADS PubMed Loaiza , V. M. , & McCabe , D. P . ( 2013 ). The influence of aging on attentional refreshing and articulatory rehearsal during working memory on later episodic memory performance . Aging, Neuropsychology and Cognition , 20 , 471 – 493 . doi: https://doi.org/10.1080/13825585.2012.738289 Google Scholar CrossRef Search ADS Loaiza , V. M. , Rhodes , M. G. , & Anglin , J . ( 2015 ). The influence of age-related differences in prior knowledge and attentional refreshing opportunities on episodic memory . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 70 , 729 – 736 . doi: https://doi.org/10.1093/geronb/gbt119 Google Scholar CrossRef Search ADS Loaiza , V. M. and Souza , A. S . ( 2018 ), Is refreshing in working memory impaired in older age? Evidence from the retro‐cue paradigm . Annals of the New York Academy of Sciences . doi: https://doi.org/10.1111/nyas.13623 Luo , L. , & Craik , F. I . ( 2008 ). Aging and memory: A cognitive approach . Canadian Journal of Psychiatry , 53 , 346 – 353 . doi: https://doi.org/10.1177/070674370805300603 Google Scholar CrossRef Search ADS PubMed Moscovitch , M. , & Winocur , G . ( 1995 ). Frontal lobes, memory, and aging . Annals of the New York Academy of Sciences , 769 , 119 – 150 . doi:10.1111/j.1749-6632.1995.tb38135.x Google Scholar CrossRef Search ADS PubMed Park , D. C. , & Festini , S. B . ( 2017 ). Theories of memory and aging: A look at the past and a glimpse of the future . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 72 , 82 – 90 . doi: https://doi.org/10.1093/geronb/gbw066 Google Scholar CrossRef Search ADS Park , D. C. , Lautenschlager , G. , Hedden , T. , Davidson , N. S. , Smith , A. D. , & Smith , P. K . ( 2002 ). Models of visuospatial and verbal memory across the adult life span . Psychology and Aging , 17 , 299 – 320 . doi: https://doi.org/10.1037/0882-7974.17.2.299 Google Scholar CrossRef Search ADS PubMed Peters , F. , Majerus , S. , Olivier , L. , van der Linden , M. , Salmon , E. , & Collette , F . ( 2007 ). A multicomponent exploration of verbal short-term storage deficits in normal aging and Alzheimer’s disease . Journal of Clinical and Experimental Neuropsychology , 29 , 405 – 417 . doi: https://doi.org/10.1080/13803390600733064 Google Scholar CrossRef Search ADS PubMed Plancher , G. , Boyer , H. , Lemaire , B. , & Portrat , S . ( 2017 ). Under which conditions can older participants maintain information in working memory ? Experimental Aging Research , 43 , 409 – 429 . doi: https://doi.org/10.1080/0361073X.2017.1369730 Google Scholar CrossRef Search ADS PubMed Portrat , S. , Camos , V. , & Barrouillet , P . ( 2009 ). Working memory in children: A time-constrained functioning similar to adults . Journal of Experimental Child Psychology , 102 , 368 – 74 . doi: https://doi.org/10.1016/j.jecp.2008.05.005 Google Scholar CrossRef Search ADS PubMed Raye , C. L. , Johnson , M. K. , Mitchell , K. J. , Greene , E. J. , & Johnson , M. R . ( 2007 ). Refreshing: A minimal executive function . Cortex , 43 , 135 – 145 . doi:10.1016/S0010-9452(08)70451-9 Google Scholar CrossRef Search ADS PubMed Raye , C. L. , Mitchell , K. J. , Reeder , J. A. , Greene , E. J. , & Johnson , M. K . ( 2008 ). Refreshing one of several active representations: Behavioral and functional magnetic resonance imaging differences between young and older adults . Journal of Cognitive Neuroscience , 20 , 852 – 862 . doi: https://doi.org/10.1162/jocn.2008.20508 Google Scholar CrossRef Search ADS PubMed Richardson , J. T. E. , & Baddeley , A. D . ( 1975 ). The effect of articulatory suppression in free recall . Journal of Verbal Learning and Verbal Behavior , 14 , 623 – 629 . doi: https://doi.org/10.1016/S0022-5371 (75)80049-1 Google Scholar CrossRef Search ADS RStudio Team ( 2016 ). RStudio: Integrated development for R . Boston, MA : RStudio, Inc . Retrieved from http://www.rstudio.com/ Salthouse , T. A . ( 1996 ). The processing-speed theory of adult age differences in cognition . Psychological Review , 103 , 403 – 428 . doi: https://doi.org/10.1037/0033-295X.103.3.403 Google Scholar CrossRef Search ADS PubMed Souza , A. S . ( 2016 ). No age deficits in the ability to use attention to improve visual working memory . Psychology and Aging , 31 , 456 – 470 . doi: https://doi.org/10.1037/pag0000107 Google Scholar CrossRef Search ADS PubMed Tam , H. , Jarrold , C. , Baddeley , A. D. , & Sabatos-DeVito , M . ( 2010 ). The development of memory maintenance: Children’s use of phonological rehearsal and attentional refreshment in working memory tasks . Journal of Experimental Child Psychology , 107 , 306 – 324 . doi: https://doi.org/10.1016/j.jecp.2010.05.006 Google Scholar CrossRef Search ADS PubMed Vaughan , L. , Basak , C. , Hartman , M. , & Verhaeghen , P . ( 2008 ). Aging and working memory inside and outside the focus of attention: Dissociations of availability and accessibility . Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition , 15 , 703 – 724 . doi: https://doi.org/10.1080/13825580802061645 Google Scholar CrossRef Search ADS PubMed Vergauwe , E. , Barrouillet , P. , & Camos , V . ( 2010 ). Do mental processes share a domain-general resource ? Psychological Science , 21 , 384 – 390 . doi: https://doi.org/10.1177/0956797610361340 Google Scholar CrossRef Search ADS PubMed Vergauwe , E. , & Cowan , N . ( 2015 ). Attending to items in working memory: Evidence that refreshing and memory search are closely related . Psychonomic Bulletin & Review , 22 , 1001 – 1006 . doi: https://doi.org/10.3758/s13423-014-0755-6 Google Scholar CrossRef Search ADS PubMed Vergauwe , E. , & Langerock , N . ( 2017 ). Attentional refreshing of information in working memory: Increased immediate accessibility of just-refreshed representations . Journal of Memory and Language , 96 , 23 – 35 . doi:10.1016/j.jml.2017.05.001 Google Scholar CrossRef Search ADS Verhaeghen , P. , & Basak , C . ( 2005 ). Ageing and switching of the focus of attention in working memory: Results from a modified N-back task . The Quarterly Journal of Experimental Psychology. A, Human Experimental Psychology , 58 , 134 – 154 . doi: https://doi.org/10.1080/02724980443000241 Google Scholar CrossRef Search ADS PubMed Verhaeghen , P. , & Hoyer , W. J . ( 2007 ). Aging, focus switching, and task switching in a continuous calculation task : Evidence toward a new working memory control process . Aging, Neuropsychology, and Cognition , 14 , 22 – 39 . doi: https://doi.org/10.1080/138255890969357 Google Scholar CrossRef Search ADS Ward , G. , & Maylor , E. A . ( 2005 ). Age-related deficits in free recall: The role of rehearsal . The Quarterly Journal of Experimental Psychology. A, Human Experimental Psychology , 58 , 98 – 119 . doi: https://doi.org/10.1080/02724980443000223 Google Scholar CrossRef Search ADS PubMed Wasylyshyn , C. , Verhaeghen , P. , & Sliwinski , M. J . ( 2011 ). Aging and task switching: A meta-analysis . Psychology and Aging , 26 , 15 – 20 . doi: https://doi.org/10.1037/a0020912 Google Scholar CrossRef Search ADS PubMed Wechsler , D . ( 2008 ) Wechsler Adult Intelligence Scale – Fourth Edition . Pearson ; San Antonio, TX . © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

The Journals of Gerontology Series B: Psychological Sciences and Social SciencesOxford University Press

Published: Jun 6, 2018

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off