The approximate number system (ANS) is an innate cognitive template that allows for the mental representation of approximate magnitude, and has been controversially linked to symbolic number knowledge and math ability. A series of recent studies found that an approximate arithmetic training (AAT) task that draws upon the ANS can improve math skills, which not only supports the existence of this link, but suggests it may be causal. However, no direct transfer effects to any measure of the ANS have yet been reported, calling into question the mechanisms by which math improvements may emerge. The present study investigated the effects of a 7-day AAT and successfully replicated previously reported transfer effects to math. Furthermore, our exploratory analyses provide preliminary evidence that certain ANS-related skills may also be susceptible to training. We conclude that AAT has reproducible effects on math performance, and provide avenues for future studies to further explore underlying mechanisms - specifically, the link between improvements in math and improvements in ANS skills.

Despite promising reports of broad cognitive benefit in studies of cognitive training, it has been argued that the reliance of many studies on no-intervention control groups (passive controls) make these reports difficult to interpret because placebo effects cannot be ruled out. Although researchers have recently been trying to incorporate more active controls, in which participants engage in an alternate intervention, previous work has been contentious as to whether this actually yields meaningfully different results. To better understand the influence of passive and active control groups on cognitive interventions, we conducted two meta-analyses to estimate their relative effect sizes. While the first one broadly surveyed the literature by compiling data from 34 meta-analyses, the second one synthesized data from 42 empirical studies that simultaneously employed both types of controls. Both analyses showed no meaningful performance difference between passive and active controls, suggesting that current active control placebo paradigms might not be appropriately designed to reliably capture these non-specific effects or that these effects are minimal in this literature.

Our recent meta-analysis concluded that training on working memory can improve performance on tests of fluid intelligence (Au et al., Psychon Bull Rev, 22(2), 366-377, 2015). Melby-Lervåg and Hulme (Psychon Bull Rev, doi: 10.3758/s13423-015-0862-z ) challenge this conclusion on the grounds that it did not take into consideration baseline differences on a by-study level and that the effects were primarily driven by purportedly less rigorous studies that did not include active control groups. Their re-analysis shows that accounting for baseline differences produces a statistically significant, but considerably smaller, overall effect size (g = 0.13 vs g = 0.24 in Au et al.), which loses significance after excluding studies without active controls. The present report demonstrates that evidence of impact variation by the active/passive nature of control groups is ambiguous and also reveals important discrepancies between Melby-Lervåg and Hulme's analysis and our original meta-analysis in terms of the coding and organization of data that account for the discrepant effect sizes. We demonstrate that there is in fact no evidence that the type of control group per se moderates the effects of working memory training on measures of fluid intelligence and reaffirm the original conclusions in Au et al., which are robust to multiple methods of calculating effect size, including the one proposed by Melby-Lervåg and Hulme.

Working memory (WM) capacity is critically important for the success in school and complex cognitive activitiesacross the lifespan. Training WM skills has shown to lead to improvements in a variety of important cognitive tasks. One’sperformance on an adaptive and challenging longitudinal WM intervention may serve as an assay of cognitive plasticity. Withover 400 participants having completed a minimum of 15 sessions of WM training, we have a rich dataset that allows investigat-ing individual differences and other factors that might determine training outcome using a novel machine learning techniques.Preliminary results suggest that factors such as age, type of n-back, and baseline abilities significantly impact one’s ability toimprove in training. Other factors such as gender and whether or not training was supervised were not significant. Finally, ourmodel allows prediction of training gain with 78% accuracy.

Executive function (EF), its importance for scholastic achievement and the question of whether or not EF is malleable, have become a topic of intense interest. Education or schooling is often seen as effective approaches to enhance EF due to the specific school-related requirements as compared to kindergarten or pre-school. However, no study to date has investigated whether targeted training focusing on those domains might be comparable with regular schooling in improving EF and fluid intelligence (Gf). The aim of the present study was to replicate and extend the previously demonstrated schooling effects on EF by using a school-cutoff design, and to further investigate whether a theoretically motivated intervention targeting specific EF, i.e., working memory (WM) or inhibitory control (IC), could achieve comparable effects with schooling in both, WM and IC, as well as Gf. 91 6-year-old kindergarteners and first-graders with similar chronological age participated the study. We compared the performance of a first-grade schooling group with that of two kindergarten training groups as well as a business-as-usual kindergarten control group. Participants were assessed in WM, IC and Gf at baseline, immediately after the intervention (posttest), as well as 3 months after training completion (follow-up). The results showed that the schooling group indeed outperformed the kindergarten groups at baseline in several cognitive tasks. Furthermore, both the WM and IC training showed pronounced gains in the trained tasks, as well as varying degrees of improvement in non-trained outcome measures. Most importantly, both training groups achieved comparable performance with the schooling group, which was especially apparent in Gf at follow-up. Our findings provide further evidence for the malleability of EF demonstrating that both, long-term and short-term interventions can facilitate the acquisition of those important skills, and as such, our work has important implications for educational practice.

Working memory (WM), the ability to store and manipulate information for short periods of time, is an important predictor of scholastic aptitude and a critical bottleneck underlying higher-order cognitive processes, including controlled attention and reasoning. Recent interventions targeting WM have suggested plasticity of the WM system by demonstrating improvements in both trained and untrained WM tasks. However, evidence on transfer of improved WM into more general cognitive domains such as fluid intelligence (Gf) has been more equivocal. Therefore, we conducted a meta-analysis focusing on one specific training program, n-back. We searched PubMed and Google Scholar for all n-back training studies with Gf outcome measures, a control group, and healthy participants between 18 and 50 years of age. In total, we included 20 studies in our analyses that met our criteria and found a small but significant positive effect of n-back training on improving Gf. Several factors that moderate this transfer are identified and discussed. We conclude that short-term cognitive training on the order of weeks can result in beneficial effects in important cognitive functions as measured by laboratory tests.

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.

Previous cognitive training research with the change-detection paradigm found only sparse effects that went beyond improvements in the training task but stressed an increase in fidelity of internal memory representations. Motivated by the demanding visual processing requirements of change-detection training, we extended this work by focusing on whether training on a change-detection task would improve visual processing skills. Fifty participants were randomly assigned to train on a change-detection task or on a control task for seven sessions. Participants' visual processing skills were assessed before and after the intervention, focusing on visual search, contrast sensitivity, and contour integration. Our results suggest a general improvement in perceptual skills that was primarily driven by a conjunction search task and to a much lesser extent by a complex visual search task and a contrast sensitivity task. The data from the conjunction search task further suggest a causal link between training and improvements of perceptual as opposed to attentional processes. Since the change-detection paradigm is commonly used to assess working memory capacity, future research needs to investigate how much of its variance is explained by memory performance and how much is explained by perceptual processes.

Working memory training has been the focus of intense research interest. Despite accumulating behavioral work, knowledge about the neural mechanisms underlying training effects is scarce. Here, we show that 7 days of training on an n-back task led to substantial performance improvements in the trained task; furthermore, the experimental group showed cross-modal transfer, as compared with an active control group. In addition, there were two neural effects that emerged as a function of training: first, increased perfusion during task performance in selected regions, reflecting a neural response to cope with high task demand; second, increased blood flow at rest in regions where training effects were apparent. We also found that perfusion at rest was correlated with task proficiency, probably reflecting an improved neural readiness to perform. Our findings are discussed within the context of the available neuroimaging literature on n-back training.