As a potential means of enhancing general cognitive functioning, computer-based cognitive training interventions have become increasingly popular for children and adults alike. Commercial companies that offer so-called “brain training” are constantly developing new programs and apps, advertising them with such compelling marketing slogans as “Think faster, focus better, and remember more with BrainHQ” or “CogniFit […] boosts your patient’s weakest cognitive skills and brain plasticity.”

Whether and to what extent promises like these can be kept has been the subject of a heated debate in light of current scientific findings.

In 2014, the Max Planck Institute for Human Development, the Stanford Center on Longevity, and a group of more than 70 leading cognitive psychologists and neuroscientists signed a position statement addressing these issues. In that document, the researchers concluded that there is insufficient evidence to support the manifold marketing claims of commercial brain training companies suggesting that their products can enhance general cognitive functioning or postpone age-related cognitive decline.

Should we therefore dismiss entirely the idea that cognitive training might be effective?

Cognition across the lifespan

To answer this question, we first have to understand how cognitive abilities (e.g., memory, intelligence, attention) change and can be modified throughout the lifespan. Although developmental changes in cognition may be characterized by growth and decline at any point in the life course, most cognitive abilities differentiate and improve from early childhood to early adulthood and tend to dedifferentiate and decline in late adulthood, with fluid abilities (e.g., processing speed, memory, reasoning) deteriorating earlier than more knowledge-based, crystallized abilities (e.g., vocabulary).

These are the general trends in cognitive development, but it is important to note that individuals differ in their levels of cognitive functioning and age-related changes.

“Research has shown that an active lifestyle is associated with higher levels of cognitive functioning and less cognitive decline.”

While some individuals may still have an exceptionally good memory at the age of 80, others may have a hard time remembering names or phone numbers even at age 60. These individual differences are influenced in part by lifestyle factors, such as intellectual, social, and physical activities, which can be actively managed by the individual.

Research has shown that an active lifestyle is associated with higher levels of cognitive functioning and less cognitive decline. Based on such findings, researchers have started to develop standardized cognitive training interventions – intellectually stimulating activities – to enhance or stabilize cognitive functioning throughout the lifespan.

Effectiveness of cognitive interventions: training gains vs. transfer effects

A large number of training interventions have targeted working memory. Working memory is a cognitive ability with a limited capacity for temporarily storing and manipulating information. This ability is important for successfully completing a variety of complex everyday tasks, such as solving mathematical problems, reading the newspaper, or learning a new language.

Over the last two decades, many studies have evaluated the effectiveness of certain working memory training programs in improving the individual’s performance on specific tasks (i.e., training gains).

“The degree to which such improvements can transfer to other tasks is limited.”

More importantly, studies have also sought to determine whether the effects of such programs might generalize to untrained cognitive tasks that measure the trained ability differently (i.e., near transfer) or even to untrained abilities (i.e., far transfer).

Recent evidence suggests that although both children and adults showed significant improvement in their performance on the trained working memory tasks, the degree to which such improvements can transfer to other tasks is limited. There is some support for near transfer effects, indicating that working memory training also improves performance on untrained working memory tasks, but far transfer to untrained cognitive abilities, such as intelligence, is rarely found.

The role of individual characteristics

At the moment, it appears that cognitive training is not a “one-size-fits-all” solution to enhance cognitive functioning above and beyond the trained tasks. Thus, researchers have started to investigate the influence of individual characteristics on training outcomes.

And indeed, there is some initial evidence that specific personality traits, motivation, baseline cognitive performance, or demographic variables (e.g., age) can moderate training outcomes. For example, researchers have found that conscientious individuals show enhanced training and transfer performance, whereas neurotic individuals generally perform worse.

“At the moment, it appears that cognitive training is not a ‘one-size-fits-all’ solution to enhance cognitive functioning above and beyond the trained tasks.”

However, there are still large gaps in the literature, and we need more evidence to reach a definitive conclusion as to whether, and for whom, training works.

If we learn more about the individual characteristics that are predictive of training effectiveness, we might be better able to distinguish subgroups of individuals who are responsive to current cognitive training interventions from those who are not, and to promote the development of individualized training interventions in the future.

Footnotes

Baltes, P. B. (1987). Theoretical propositions of life-span developmental psychology: On the dynamics between growth and decline. Developmental Psychology, 23(5), 611–626.

Feldmann Barrett, L., Tugade, M. M., & Engle, R. W. (2004). Individual Differences in Working Memory Capacity and Dual-Process Theories of the Mind. Psychological Bulletin, 130(4), 553–573.

Guye, S., De Simoni, C., & von Bastian, C. C. (in revision). Do Individual Differences Predict Change in Cognitive Performance? A Latent Growth Curve Modeling Approach.

Guye, S., Röcke, C., Mérillat, S., von Bastian, C. C., & Martin, M. (2016). Adult Lifespan. In T. Strobach & J. Karbach (Eds.), Cognitive Training: An Overview of Features and Applications (pp. 45–55). Berlin: Springer.

Katz, B., Jones, M. R., Shah, P., Buschkuehl, M., & Jaeggi, S. M. (2016). Individual Differences and Motivational Effects in Cognitive Training Research. In T. Strobach & J. Karbach (Eds.), Cognitive Training: An Overview of Features and Applications (pp. 157–166). Berlin: Springer.

Hertzog, C., Kramer, A. F., Wilson, R. S., & Lindenberger, U. (2009). Enrichment Effects on Adult Cognitive Development. Psychological Science in the Public Interest, 9(1), 1–65.

Sala, G. & Gobet, F. (2017). Working Memory Training in Tipically Developing Children: A Meta-Analysis of the Available Evidence. Developmental Psychology, 53(4), 671-685.

Salthouse, T. A. (2004). What and When of Cognitive Aging. Current Directions in Psychological Science, 13(4), 140–144.

von Bastian, C. C., & Oberauer, K. (2014). Effects and mechanisms of working memory training: a review. Psychological Research, 78(6), 803–820.

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