Neural correlates of working memory training: Evidence for plasticity in older adults

Iordan, Alexandru D.; Cooke, Katherine A.; Moored, Kyle; Katz, Benjamin; Buschkuehl, Martin; Jaeggi, Susanne M.; Polk, Thad A.; Peltier, Scott; Jonides, John; Reuter‐Lorenz, Patricia A.

doi:10.1016/j.neuroimage.2020.116887

Cited by 29 publications

(18 citation statements)

References 81 publications

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“…Based on this perspective, WM has captured great attention in cognitive training research, and many training programs have been designed to specifically target WM 7 . For example, previous studies have shown that training older adults in certain WM tasks during a relatively short period (e.g., 10 days, 5 weeks or 3 months) could lead to a significant improvement in behavioral performance (i.e., accuracy) during the trained or untrained WM tasks, something referred to as ‘near’ transfer effects 8 – 15 . On the other hand, ‘far’ transfer is typically used to describe situations in which the training and transfer tasks are not regarded to rely on the same core process, while the distinction between what is ‘far’ and what is ‘near’ is usually qualitative rather than quantitative 16 , 17 .…”

Section: Introductionmentioning

confidence: 99%

Effects of multi-domain cognitive training on working memory retrieval in older adults: behavioral and ERP evidence from a Chinese community study

Hong

Chen

Wang

et al. 2021

Sci Rep

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Working memory (WM) is a fundamental cognitive function that typically declines with age. Previous studies have shown that targeted WM training has the potential to improve WM performance in older adults. In the present study, we investigated whether a multi-domain cognitive training program that was not designed to specifically target WM could improve the behavioral performance and affect the neural activity during WM retrieval in healthy older adults. We assigned healthy older participants (70–78 years old) from a local community into a training group who completed a 3-month multi-domain cognitive training and a control group who only attended health education lectures during the same period. Behavioral and electroencephalography (EEG) data were recorded from participants while performing an untrained delayed match or non-match to category task and a control task at a pre-training baseline session and a post-training follow-up session. Behaviorally, we found that participants in the training group showed a trend toward greater WM performance gains than participants in the control group. Event-related potential (ERP) results suggest that the task-related modulation of P3 during WM retrieval was significantly enhanced at the follow-up session compared with the baseline session, and importantly, this enhancement of P3 modulation was only significant in the training group. Furthermore, no training-related effects were observed for the P2 or N2 component during WM retrieval. These results suggest that the multi-domain cognitive training program that was not designed to specifically target WM is a promising approach to improve WM performance in older adults, and that training-related gains in performance are likely mediated by an enhanced modulation of P3 which might reflect the process of WM updating.

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Section: Introductionmentioning

confidence: 99%

Effects of multi-domain cognitive training on working memory retrieval in older adults: behavioral and ERP evidence from a Chinese community study

Hong

Chen

Wang

et al. 2021

Sci Rep

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“…[7][8][9] Notably, WM and executive functions belong to the most vulnerable cognitive domains in PD. 10 Furthermore, targeted WMT in healthy individuals has been associated with changes in frontoparietal and subcortical neural networks and particularly dopaminergic functions 11,12 -neural networks and neurotransmitter systems on the one hand directly associated with WM, 13 on the other hand, especially vulnerable in PD. 14 Therefore, first randomized controlled trials (RCTs) on targeted WMT in PD have been conducted recently.…”

Section: Introductionmentioning

confidence: 99%

Predicting Working Memory Training Responsiveness in Parkinson’s Disease: Both “System Hardware” and Room for Improvement Are Needed

Ophey

Rehberg

Giehl

et al. 2021

Neurorehabil Neural Repair

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Background. Patients with Parkinson’s disease (PD) are highly vulnerable to develop cognitive dysfunctions, and the mitigating potential of early cognitive training (CT) is increasingly recognized. Predictors of CT responsiveness, which could help to tailor interventions individually, have rarely been studied in PD. This study aimed to examine individual characteristics of patients with PD associated with responsiveness to targeted working memory training (WMT). Methods. Data of 75 patients with PD (age: 63.99 ± 9.74 years, 93% Hoehn & Yahr stage 2) without cognitive dysfunctions from a randomized controlled trial were analyzed using structural equation modeling. Latent change score models with and without covariates were estimated and compared between the WMT group ( n = 37), who participated in a 5-week adaptive WMT, and a waiting list control group ( n = 38). Results. Latent change score models yielded adequate model fit (χ2-test p > .05, SRMR ≤ .08, CFI ≥ .95). For the near-transfer working memory composite, lower baseline performance, younger age, higher education, and higher fluid intelligence were found to significantly predict higher latent change scores in the WMT group, but not in the control group. For the far-transfer executive function composite, higher self-efficacy expectancy tended to significantly predict larger latent change scores. Conclusions. The identified associations between individual characteristics and WMT responsiveness indicate that there has to be room for improvement (e.g., lower baseline performance) and also sufficient “hardware” (e.g., younger age, higher intelligence) to benefit in training-related cognitive plasticity. Our findings are discussed within the compensation versus magnification account. They need to be replicated by methodological high-quality research applying advanced statistical methods with larger samples.

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“…The initial sample size was based on prior work examining age and load effects in WM (Cappell et al, 2010). Detailed sample characteristics are presented elsewhere (Iordan et al, 2020). Briefly, all participants were right‐handed, native English speakers with normal or corrected‐to‐normal hearing and vision and were screened for history of head injury, psychiatric illness, or alcohol/drug abuse.…”

Section: Methodsmentioning

confidence: 99%

“…Behavioral results showed that WM performance improved with training for both groups, and were presented elsewhere (Iordan et al, 2020). Briefly, effects of task-exposure and training on WM performance were examined with loads 5-8, which were common to both groups, using Group × Time × Load ANOVAs on WM accuracy scores.…”

Section: Behavioral Analysesmentioning

confidence: 99%

“…Furthermore, recent evidence shows that modularity increases with training in younger adults, suggesting that less brain network integration is required to support high performance once a task is automated, even for complex tasks, such as WM (Finc et al, 2020). For older adults, recent evidence (Iordan et al, 2020) suggests that WM training increases brain responsiveness by shifting the activation peak toward higher WM loads. However, it is unclear what changes in the large‐scale network organization occur with training in older adults.…”

Section: Introductionmentioning

confidence: 99%

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Age differences in functional network reconfiguration with working memory training

Iordan

Moored

Katz

et al. 2021

Human Brain Mapping

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Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10 days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task‐related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default‐mode network for younger adults, it enhanced efficiency within a task‐specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default‐mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between‐network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age‐related trajectories in functional network reorganization with WM training.

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Neural correlates of working memory training: Evidence for plasticity in older adults

Cited by 29 publications

References 81 publications

Effects of multi-domain cognitive training on working memory retrieval in older adults: behavioral and ERP evidence from a Chinese community study

Effects of multi-domain cognitive training on working memory retrieval in older adults: behavioral and ERP evidence from a Chinese community study

Predicting Working Memory Training Responsiveness in Parkinson’s Disease: Both “System Hardware” and Room for Improvement Are Needed

Age differences in functional network reconfiguration with working memory training

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