A great deal of interest surrounds the use of transcranial direct current stimulation (tDCS) to augment cognitive training. However, effects are inconsistent across studies, and meta-analytic evidence is mixed, especially for healthy, young adults. One major source of this inconsistency is individual differences among the participants, but these differences are rarely examined in the context of combined training/stimulation studies. In addition, it is unclear how long the effects of stimulation last, even in successful interventions. Some studies make use of follow-up assessments, but very few have measured performance more than a few months after an intervention. Here, we utilized data from a previous study of tDCS and cognitive training [Au, J., Katz, B., Buschkuehl, M., Bunarjo, K., Senger, T., Zabel, C., et al. Enhancing working memory training with transcranial direct current stimulation. Journal of Cognitive Neuroscience, 28, 1419–1432, 2016] in which participants trained on a working memory task over 7 days while receiving active or sham tDCS. A new, longer-term follow-up to assess later performance was conducted, and additional participants were added so that the sham condition was better powered. We assessed baseline cognitive ability, gender, training site, and motivation level and found significant interactions between both baseline ability and motivation with condition (active or sham) in models predicting training gain. In addition, the improvements in the active condition versus sham condition appear to be stable even as long as a year after the original intervention.

Adaptive working memory (WM) training may lead to cognitive benefits that are associated with white matter plasticity in parietofrontal networks, but the underlying mechanisms remain poorly understood. We investigated white matter microstructural changes after adaptive WM training relative to a nonadaptive comparison group. Microstructural changes were studied in the superior longitudinal fasciculus, the main parietofrontal connection, and the cingulum bundle as a comparison pathway. MRI-based metrics were the myelin water fraction and longitudinal relaxation rate R 1 from multicomponent relaxometry (captured with the mcDESPOT approach) as proxy metrics of myelin, the restricted volume fraction from the composite hindered and restricted model of diffusion as an estimate of axon morphology, and fractional anisotropy and radial diffusivity from diffusion tensor imaging. PCA was used for dimensionality reduction. Adaptive training was associated with benefits in a “WM capacity” component and increases in a microstructural component (increases in R 1 , restricted volume fraction, fractional anisotropy, and reduced radial diffusivity) that predominantly loaded on changes in the right dorsolateral superior longitudinal fasciculus and the left parahippocampal cingulum. In contrast, nonadaptive comparison activities were associated with the opposite pattern of reductions in WM capacity and microstructure. No group differences were observed for the myelin water fraction metric suggesting that R 1 was a more sensitive “myelin” index. These results demonstrate task complexity and location-specific white matter microstructural changes that are consistent with tissue alterations underlying myelination in response to training.

Daily experiences demand both focused and broad allocation of attention for us to interact efficiently with our complex environments. Many types of attention have shown age-related decline, although there is also evidence that such deficits may be remediated with cognitive training. However, spatial attention abilities have shown inconsistent age-related differences, and the extent of potential enhancement of these abilities remains unknown. Here, we assessed spatial attention in both healthy younger and older adults and trained this ability in both age groups for 5 hr over the course of 2 weeks using a custom-made, computerized mobile training application. We compared training-related gains on a spatial attention assessment and spatial working memory task to age-matched controls who engaged in expectancy-matched, active placebo computerized training. Age-related declines in spatial attention abilities were observed regardless of task difficulty. Spatial attention training led to improved focused and distributed attention abilities as well as improved spatial working memory in both younger and older participants. No such improvements were observed in either of the age-matched control groups. Note that these findings were not a function of improvements in simple response time, as basic motoric function did not change after training. Furthermore, when using change in simple response time as a covariate, all findings remained significant. These results suggest that spatial attention training can lead to enhancements in spatial working memory regardless of age.

Development of measures to preserve cognitive function or even reverse cognitive decline in the ever-growing elderly population is the focus of many research and commercial efforts. One such measure gaining in popularity is the development of computer-based interventions that “exercise” cognitive functions. Computer-based cognitive training has the potential to be specific and flexible, accommodates feedback, and is highly accessible. As in most budding fields, there are still considerable inconsistencies across methodologies and results, as well as a lack of consensus on a comprehensive assessment protocol. We propose that the success of training-based therapeutics will rely on targeting specific cognitive functions, informed by comprehensive and sensitive batteries that can provide a “fingerprint” of an individual's abilities. Instead of expecting a panacea from training regimens, focused and personalized training interventions that accommodate individual differences should be developed to redress specific patterns of deficits in cognitive rehabilitation, both in healthy aging and in disease.