Benjamin Katz

The largest human cognitive performance dataset reveals insights into the effects of lifestyle factors and aging

Making new breakthroughs in understanding the processes underlying human cognition may depend on the availability of very large datasets that have not historically existed in psychology and neuroscience. Lumosity is a web-based cognitive training platform that has grown to include over 600 million cognitive training task results from over 35 million individuals, comprising the largest existing dataset of human cognitive performance. As part of the Human Cognition Project, Lumositys collaborative research program to understand the human mind, Lumos Labs researchers and external research collaborators have begun to explore this dataset in order uncover novel insights about the correlates of cognitive performance. This paper presents two preliminary demonstrations of some of the kinds of questions that can be examined with the dataset. The first example focuses on replicating known findings relating lifestyle factors to baseline cognitive performance in a demographically diverse, healthy population at a much larger scale than has previously been available. The second example examines a question that would likely be very difficult to study in laboratory-based and existing online experimental research approaches at a large scale: specifically, how learning ability for different types of cognitive tasks changes with age. We hope that these examples will provoke the imagination of researchers who are interested in collaborating to answer fundamental questions about human cognitive performance.

Enhancing working memory training with transcranial direct current stimulation

Working memory (WM) is a fundamental cognitive ability that supports complex thought but is limited in capacity. Thus, WM training interventions have become very popular as a means of potentially improving WM-related skills. Another promising intervention that has gained increasing traction in recent years is transcranial direct current stimulation (tDCS), a noninvasive form of brain stimulation that can modulate cortical excitability and temporarily increase brain plasticity. As such, it has the potential to boost learning and enhance performance on cognitive tasks. This study assessed the efficacy of tDCS to supplement WM training. Sixty-two participants were randomized to receive either right prefrontal, left prefrontal, or sham stimulation with concurrent visuospatial WM training over the course of seven training sessions. Results showed that tDCS enhanced training performance, which was strikingly preserved several months after training completion. Furthermore, we observed stronger effects when tDCS was spaced over a weekend break relative to consecutive daily training, and we also demonstrated selective transfer in the right prefrontal group to nontrained tasks of visual and spatial WM. These findings shed light on how tDCS may be leveraged as a tool to enhance performance on WM-intensive learning tasks.

Differential effect of motivational features on training improvements in school-based cognitive training

Cognitive training often utilizes game-like motivational features to keep participants engaged. It is unclear how these elements, such as feedback, reward, and theming impact player performance during training. Recent research suggests that motivation and engagement are closely related to improvements following cognitive training. We hypothesized that training paradigms featuring game-like motivational elements would be more effective than a version with no motivational elements. Five distinct motivational features were chosen for examination: a real-time scoring system, theme changes, prizes, end-of-session certificates, and scaffolding to explain the lives and leveling system included in the game. One version of the game was created with all these motivational elements included, and one was created with all of them removed. Other versions removed a single element at a time. Seven versions of a game-like n-back working memory task were then created and administered to 128 students in second through eight grade at school-based summer camps in southeastern Michigan. The inclusion of real-time scoring during play, a popular motivational component in both entertainment games and cognitive training, was found to negatively impact training improvements over the three day period. Surprisingly, scaffolding to explain lives and levels also negatively impacted training gains. The other game adjustments did not significantly impact training improvement compared to the original version of the game with all features included. These findings are preliminary and are limited by both the small sample size and the brevity of the intervention. Nonetheless, these findings suggest that certain motivational elements may distract from the core cognitive training task, reducing task improvement, especially at the initial stage of learning.

Individual Differences and Long-term Consequences of tDCS-augmented Cognitive Training

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.

Third-person self-talk facilitates emotion regulation without engaging cognitive control: Converging evidence from ERP and fMRI

Does silently talking to yourself in the third-person constitute a relatively effortless form of self control? We hypothesized that it does under the premise that third-person self-talk leads people to think about the self similar to how they think about others, which provides them with the psychological distance needed to facilitate self control. We tested this prediction by asking participants to reflect on feelings elicited by viewing aversive images (Study 1) and recalling negative autobiographical memories (Study 2) using either “I” or their name while measuring neural activity via ERPs (Study 1) and fMRI (Study 2). Study 1 demonstrated that third-person self-talk reduced an ERP marker of self-referential emotional reactivity (i.e., late positive potential) within the first second of viewing aversive images without enhancing an ERP marker of cognitive control (i.e., stimulus preceding negativity). Conceptually replicating these results, Study 2 demonstrated that third-person self-talk was linked with reduced levels of activation in an a priori defined fMRI marker of self-referential processing (i.e., medial prefrontal cortex) when participants reflected on negative memories without eliciting increased levels of activity in a priori defined fMRI markers of cognitive control. Together, these results suggest that third-person self-talk may constitute a relatively effortless form of self-control.

Individual Differences and Motivational Effects

Why do some people improve on untrained tasks following cognitive training while others do not? One possibility is that there are individual difference factors that play a key role in cognitive training outcomes. The present chapter examines a range of these factors, including baseline performance, age, personality, and motivation. Some of these factors, such as baseline performance and age, have long been examined in the context of cognitive training, and extant research provides evidence that they contribute to the outcome of both training-related improvements as well as transfer gains. Other factors, including personality and motivation, remain largely unexamined in the context of cognitive training, but preliminary research indicates that they may play a substantial role in the success of these interventions. We suggest that researchers ignore these factors at their peril and that future cognitive training studies should incorporate measures of individual differences in studies well powered enough to examine them. Furthermore, it is possible that for training interventions to be broadly successful for large populations, they must be personalized to take these factors into account.

Working memory plasticity and aging.

The present research explores how the trajectory of learning on a working memory task changes throughout the life span, and whether gains in working memory performance are exclusively a question of initial working memory capacity (WMC) or whether age exerts an independent effect. In a large, cross-sectional study of younger, middle-aged, and older adults, we examined learning on a widely used working memory task—the dual n-back task—over 20 sessions of practice. We found that, while all age groups improved on the task, older adults demonstrated less improvement on the task, and also reached a lower asymptotic maximum performance than younger adults. After controlling for initial WMC, we found that age exerted independent effects on training gains and asymptotic performance; older adults tended to improve less and reached lower levels of performance than younger adults. The difference between younger and older adults’ rates of learning depended in part on initial WMC. These results suggest that age-related effects on working memory include not only effects on capacity, but also plasticity and the ability to improve on a task.

How to play 20 questions with nature and lose: Reflections on 100 years of brain-training research

Despite dozens of empirical studies and a growing body of meta-analytic work, there is little consensus regarding the efficacy of cognitive training. In this review, we examine why this substantial corpus has failed to answer the often-asked question, “Does cognitive training work?” We first define cognitive training and discuss the general principles underlying training interventions. Next, we review historical interventions and discuss how findings from this early work remain highly relevant for current cognitive-training research. We highlight a variety of issues preventing real progress in understanding the underlying mechanisms of training, including the lack of a coherent theoretical framework to guide training research and methodological issues across studies and meta-analyses. Finally, suggestions for correcting these issues are offered in the hope that we might make greater progress in the next 100 y of cognitive-training research.

Aging and network properties: Stability over time and links with learning during working memory training

Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA) and 20 older adults (OA) were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of cognitive transfer in both younger and older adults.

Targeting self-regulation to promote health behaviors in children

Poor self-regulation (i.e., inability to harness cognitive, emotional, motivational resources to achieve goals) is hypothesized to contribute to unhealthy behaviors across the lifespan. Enhancing early self-regulation may increase positive health outcomes. Obesity is a major public health concern with early-emerging precursors related to self-regulation; it is therefore a good model for understanding self-regulation and health behavior. Preadolescence is a transition when children increase autonomy in health behaviors (e.g., eating, exercise habits), many of which involve self-regulation. This paper presents the scientific rationale for examining self-regulation mechanisms that are hypothesized to relate to health behaviors, specifically obesogenic eating, that have not been examined in children. We describe novel intervention protocols designed to enhance self-regulation skills, specifically executive functioning, emotion regulation, future-oriented thinking, and approach bias. Interventions are delivered via home visits. Assays of self-regulation and obesogenic eating behaviors using behavioral tasks and self-reports are implemented and evaluated to determine feasibility and psychometrics and to test intervention effects. Participants are low-income 9-12 year-old children who have been phenotyped for self-regulation, stress, eating behavior and adiposity through early childhood. Study goals are to examine intervention effects on self-regulation and whether change in self-regulation improves obesogenic eating.