Individual differences in cognitive plasticity: an investigation of training curves in younger and older adults

Abstract

To date, cognitive intervention research has provided mixed but nevertheless promising evidence with respect to the effects of cognitive training on untrained tasks (transfer). However, the mechanisms behind learning, training effects and their predictors are not fully understood. Moreover, individual differences, which may constitute an important factor impacting training outcome, are usually neglected. We suggest investigating individual training performance across training sessions in order to gain finer-grained knowledge of training gains, on the one hand, and assessing the potential impact of predictors such as age and fluid intelligence on learning rate, on the other hand. To this aim, we propose to model individual learning curves to examine the intra-individual change in training as well as inter-individual differences in intra-individual change. We recommend introducing a latent growth curve model (LGCM) analysis, a method frequently applied to learning data but rarely used in cognitive training research. Such advanced analyses of the training phase allow identifying factors to be respected when designing effective tailor-made training interventions. To illustrate the proposed approach, a LGCM analysis using data of a 10-day working memory training study in younger and older adults is reported.

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

“…Regarding neuroticism, our expectations were less specific, given that previous literature reported evidence for a negative association of neuroticism with mean training performance and transfer effects, but not with training gains (e.g., Studer-Luethi et al 2012, 2016. Based on the results by Bürki et al (2014), methodologically the most similar study to our own, we expected a negative association of age and a positive association of baseline cognitive performance with change in cognitive performance, which would support the magnification hypothesis. For all the other individual differences variables, the analyses were exploratory.…”

“…A closely related yet potentiallydistinct factor possibly contributing tothese mixed findings is general cognitive functioning (von Bastian and Oberauer 2014). Only few studies have directly assessed the effect of baseline cognitive performance on training outcomes though, with some evidence suggesting that initially lowperforming individuals benefit more from training (e.g., Jaeggi et al 2008;Zinke et al 2014), but others reported opposite effects (e.g., Bürki et al 2014).…”

“…A closely related yet potentiallydistinct factor possibly contributing tothese mixed findings is general cognitive functioning (von Bastian and Oberauer 2014). Only few studies have directly assessed the effect of baseline cognitive performance on training outcomes though, with some evidence suggesting that initially lowperforming individuals benefit more from training (e.g., Jaeggi et al 2008;Zinke et al 2014), but others reported opposite effects (e.g., Bürki et al 2014).Although motivation is arguably one of the most plausible factors possibly influencing cognitive training outcomes, its association with training performance has not yet been comprehensively examined. One exception is a study by Brose et al (2012), whoreported a positive associationbetween dailymotivation and daily cognitive performance on a 3-back task, indicating that on days on which task-related motivation was lower than on average, daily cognitive performance was also reduced.…”

LearningRx Cognitive Training Effects in Children Ages 8–14: A Randomized Controlled Trial

“…Dunning et al (2013) used a similar dual control group design and also concluded that experimental gains were not likely the result of expectancy effects. Burki, Ludwig, Chicherio, and Ribaupierre (2014) reported comparable results, finding no significant differences in training outcomes between active controls and no‐contact controls. Finally, two recent meta‐analyses of 35 cognitive training studies indicated no difference between types of control groups when compared to each other.…”

Improving Older Adults’ Working Memory: the Influence of Age and Crystallized Intelligence on Training Outcomes

“…However, in one of the training and transfer tasks, the authors found no age differences. Bürki et al (2014) also found that younger adults improved more over the working memory training sessions than older adults. The authors further showed that individual differences in fluid intelligence predicted the initial training performance independent of age.…”