The Influence of Individual Differences in Cognitive Ability on Working Memory Training Gains

Remote neurocognitive interventions for attention-deficit/hyperactivity disorder - Opportunities and challenges

Improving neurocognitive functions through remote interventions has been a promising approach to developing new treatments for attention-deficit/hyperactivity disorder (AD/HD). Remote neurocognitive interventions may address the shortcomings of the current prevailing pharmacological therapies for AD/HD, e.g., side effects and access barriers. Here we review the current options for remote neurocognitive interventions to reduce AD/HD symptoms, including cognitive training, EEG neurofeedback training, transcranial electrical stimulation, and external cranial nerve stimulation. We begin with an overview of the neurocognitive deficits in AD/HD to identify the targets for developing interventions. The role of neuroplasticity in each intervention is then highlighted due to its essential role in facilitating neuropsychological adaptations. Following this, each intervention type is discussed in terms of the critical details of the intervention protocols, the role of neuroplasticity, and the available evidence. Finally, we offer suggestions for future directions in terms of optimizing the existing intervention protocols and developing novel protocols.

Working memory training for reward processing in university students with subsyndromal depression: The influence of baseline severity of depression

Previous studies have tentatively suggested that working memory training (WMT) has the potential to improve reward processing, but it is not known how long this improvement lasts, whether there is a lag effect, or whether it is reflected in neurophysiological indicators. In this study, 40 university students with subsyndromal depression were randomly assigned to a training group or a control group and completed a 20-day working memory training task and a simple memory task, respectively. All participants completed the Temporal Experience of Pleasure Scale (TEPS) and a doors task with electroencephalogram (EEG) signals recorded simultaneously on a pre- and post-test and a 3-month follow-up. The reward-related positivity (RewP) amplitude, theta power, and their differences between conditions (i.e., ΔRewP and Δtheta power, respectively) in the doors task were the primary outcomes, and the score on TEPS was the secondary outcome. The results indicated no group-related effects were demonstrated in primary and secondary outcomes at post-test and 3-month follow-up. Furthermore, the differences in the pre- and post-test in Δtheta power were moderated by the baseline severity of depression. This was primarily driven by the fact that the change values in the control group increased with the severity of depression, while the change values in the training group had high homogeneity. Our findings did not provide support for the effect of WMT on reward processing across the whole sample, but without intervention, there would be high heterogeneity in the change in the cognitive control ability to loss feedback, which is detrimental to individuals with high depression severity.

Unicorn, Hare, or Tortoise? Using Machine Learning to Predict Working Memory Training Performance

People differ considerably in the extent to which they benefit from working memory (WM) training. Although there is increasing research focusing on individual differences associated with WM training outcomes, we still lack an understanding of which specific individual differences, and in what combination, contribute to inter-individual variations in training trajectories. In the current study, 568 undergraduates completed one of several N-back intervention variants over the course of two weeks. Participants' training trajectories were clustered into three distinct training patterns (high performers, intermediate performers, and low performers). We applied machine-learning algorithms to train a binary tree model to predict individuals' training patterns relying on several individual difference variables that have been identified as relevant in previous literature. These individual difference variables included pre-existing cognitive abilities, personality characteristics, motivational factors, video game experience, health status, bilingualism, and socioeconomic status. We found that our classification model showed good predictive power in distinguishing between high performers and relatively lower performers. Furthermore, we found that openness and pre-existing WM capacity to be the two most important factors in distinguishing between high and low performers. However, among low performers, openness and video game background were the most significant predictors of their learning persistence. In conclusion, it is possible to predict individual training performance using participant characteristics before training, which could inform the development of personalized interventions.

Investigating the Role of Individual Differences in Adherence to Cognitive Training

Consistent with research across several domains, intervention adherence is associated with desired outcomes. Our study investigates adherence, defined by participants' commitment to, persistence with, and compliance with an intervention's regimen, as a key mechanism underlying cognitive training effectiveness. We examine this relationship in a large and diverse sample comprising 4,775 adults between the ages of 18 and 93. We test the predictive validity of individual difference factors, such as age, gender, cognitive capability (i.e., fluid reasoning and working memory), grit, ambition, personality, self-perceived cognitive failures, socioeconomic status, exercise, and education on commitment to and persistence with a 20-session cognitive training regimen, as measured by the number of sessions completed. Additionally, we test the relationship between compliance measures: (i) spacing between training sessions, as measured by the average time between training sessions, and (ii) consistency in the training schedule, as measured by the variance in time between training sessions, with performance trajectories on the training task. Our data suggest that none of these factors reliably predict commitment to, persistence with, or compliance with cognitive training. Nevertheless, the lack of evidence from the large and representative sample extends the knowledge from previous research exploring limited, heterogenous samples, characterized by older adult populations. The absence of reliable predictors for commitment, persistence, and compliance in cognitive training suggests that nomothetic factors may affect program adherence. Future research will be well served to examine diverse approaches to increasing motivation in cognitive training to improve program evaluation and reconcile the inconsistency in findings across the field.

Perceptual and semantic same-different processing under subliminal conditions

Although other types of subliminal integrative processing are widely refuted by recent studies, subliminal same-different processing (SSDP) remains unchallenged to this day. Using shapes, categorical images, and Chinese characters as stimuli, the current study assessed whether SSDP can occur on a perceptual and semantic basis. Although some significant results were found, the effects are much weaker than previous studies, with Bayes factors suggesting that these effects are not reliable. It is therefore concluded that substantiating claims of SSDP requires more reliable evidence than currently available.

Take a load off: examining partial and complete cognitive offloading of medication information

Although cognitive offloading, or the use of physical action to reduce internal cognitive demands, is a commonly used strategy in everyday life, relatively little is known about the conditions that encourage offloading and the memorial consequences of different offloading strategies for performance. Much of the extant work in this domain has focused on laboratory-based tasks consisting of word lists, letter strings, or numerical stimuli and thus makes little contact with real-world scenarios under which engaging in cognitive offloading might be likely. Accordingly, the current work examines offloading choice behavior and potential benefits afforded by offloading health-related information. Experiment 1 tests for internal memory performance for different pieces of missing medication interaction information. Experiment 2 tests internal memory and offloading under full offloading and partial offloading instructions for interaction outcomes that are relatively low severity (e.g., sweating). Experiment 3 extends Experiment 2 by testing offloading behavior and benefit in low-severity, medium-severity (e.g., backache), and high-severity interaction outcomes (e.g., heart attack). Here, we aimed to elucidate the potential benefits afforded by partial offloading and to examine whether there appears to be a preference for choosing to offload (i) difficult-to-remember information across outcomes that vary in severity, as well as (ii) information from more severe interaction outcomes. Results suggest that partial offloading benefits performance compared to relying on internal memory alone, but full offloading is more beneficial to performance than partial offloading.

Perspectives on heterogeneity-informed cognitive training for attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (AD/HD) is a heterogeneous neurodevelopmental condition, posing a severe threat to quality of life. Pharmacological therapies are the front-line treatment; however, their shortages encourage the development of alternative treatments for AD/HD. One promising method of developing alternative treatments is cognitive training (CT). A CT-based therapy was recently approved by the US Food and Drug Administration. However, due to heterogeneity in AD/HD, a CT protocol is unlikely to provide a one-size-fits-all solution for all patients with AD/HD. Therefore, this article highlights key aspects that need to be considered to further develop CT protocols for AD/HD, regarding training content, timing, suitability, and delivery mode. The perspectives presented here contribute to optimizing CT as an alternative option for treating AD/HD.

Using clustering algorithms to examine the association between working memory training trajectories and therapeutic outcomes among psychiatric and healthy populations

Working memory (WM) training has gained interest due to its potential to enhance cognitive functioning and reduce symptoms of mental disorders. Nevertheless, inconsistent results suggest that individual differences may have an impact on training efficacy. This study examined whether individual differences in training performance can predict therapeutic outcomes of WM training, measured as changes in anxiety and depression symptoms in sub-clinical and healthy populations. The study also investigated the association between cognitive abilities at baseline and different training improvement trajectories. Ninety-six participants (50 females, mean age = 27.67, SD = 8.84) were trained using the same WM training task (duration ranged between 7 to 15 sessions). An algorithm was then used to cluster them based on their learning trajectories. We found three main WM training trajectories, which in turn were related to changes in anxiety symptoms following the training. Additionally, executive function abilities at baseline predicted training trajectories. These findings highlight the potential for using clustering algorithms to reveal the benefits of cognitive training to alleviate maladaptive psychological symptoms.

A Machine Learning Approach to Personalize Computerized Cognitive Training Interventions

Executive functions are a class of cognitive processes critical for purposeful goal-directed behavior. Cognitive training is the adequate stimulation of executive functions and has been extensively studied and applied for more than 20 years. However, there is still a lack of solid consensus in the scientific community about its potential to elicit consistent improvements in untrained domains. Individual differences are considered one of the most important factors of inconsistent reports on cognitive training benefits, as differences in cognitive functioning are both genetic and context-dependent, and might be affected by age and socioeconomic status. We here present a proof of concept based on the hypothesis that baseline individual differences among subjects would provide valuable information to predict the individual effectiveness of a cognitive training intervention. With a dataset from an investigation in which 73 6-year-olds trained their executive functions using an online software with a fixed protocol, freely available at www.matemarote.org.ar, we trained a support vector classifier that successfully predicted (average accuracy = 0.67, AUC = 0.707) whether a child would improve, or not, after the cognitive stimulation, using baseline individual differences as features. We also performed a permutation feature importance analysis that suggested that all features contribute equally to the model's performance. In the long term, this results might allow us to design better training strategies for those players who are less likely to benefit from the current training protocols in order to maximize the stimulation for each child.

Mental-Imagery-Based Mnemonic Training: A New Kind of Cognitive Training

We investigated the immediate and maintenance effects of mental-imagery-based mnemonic training on improving youths’ working memory, long-term memory, arithmetic and spatial abilities, and fluid intelligence. In Experiment 1, 26 Chinese participants (15 boys, 11 girls) aged 10–16 years were divided into an experimental group that received 8 days of mental-imagery-based mnemonic training and a no-contact control group. Participants completed pre-, post-, and three follow-up tests (3, 6, and 12 months after the pre-test). In Experiment 2, 54 Chinese children (28 boys, 26 girls), all 12 years old, were divided into experimental and control groups. Participants completed pre-, post-, and follow-up tests (three months after the pre-test). Results showed that the training significantly affected long-term memory-related task performance but no effects were observed on working memory, arithmetic or spatial ability, or fluid intelligence-related tasks. Moreover, the effect of the training on long-term memory lasted up to one year; the more frequently the training was used, the more effective it was. A content analysis of the feedback submitted by parents of participants in Experiment 2 three months after the training showed that the children used the strategy more for memorizing content such as Chinese and English, as well as for musical scores. Furthermore, there was also the possibility that the training improved abilities and academic performance such as concentration and math performance. Our results provide a basis for the further exploration of mental-imagery-based mnemonic training as a novel training modality.

Change by challenge: A common genetic basis behind childhood cognitive development and cognitive training

The interplay of genetic and environmental factors behind cognitive development has preoccupied multiple fields of science and sparked heated debates over the decades. Here we tested the hypothesis that developmental genes rely heavily on cognitive challenges-as opposed to natural maturation. Starting with a polygenic score (cogPGS) that previously explained variation in cognitive performance in adults, we estimated its effect in 344 children and adolescents (mean age of 12 years old, ranging from 6 to 25) who showed changes in working memory (WM) in two distinct samples: (1) a developmental sample showing significant WM gains after 2 years of typical, age-related development, and (2) a training sample showing significant, experimentally-induced WM gains after 25 days of an intense WM training. We found that the same genetic factor, cogPGS, significantly explained the amount of WM gain in both samples. And there was no interaction of cogPGS with sample, suggesting that those genetic factors are neutral to whether the WM gains came from development or training. These results represent evidence that cognitive challenges are a central piece in the gene-environment interplay during cognitive development. We believe our study sheds new light on previous findings of interindividual differences in education (rich-get-richer and compensation effects), brain plasticity in children, and the heritability increase of intelligence across the lifespan.

Why Does Cognitive Training Yield Inconsistent Benefits? A Meta-Analysis of Individual Differences in Baseline Cognitive Abilities and Training Outcomes

Despite growing interest in improving cognitive abilities across the lifespan through training, the benefits of cognitive training are inconsistent. One powerful contributor may be that individuals arrive at interventions with different baseline levels of the cognitive skill being trained. Some evidence suggests poor performers benefit the most from cognitive training, showing compensation for their weak abilities, while other evidence suggests that high performers benefit most, experiencing a magnification of their abilities. Whether training leads to compensation or magnification effects may depend upon the specific cognitive domain being trained (such as executive function or episodic memory) and the training approach implemented (strategy or process). To clarify the association between individual differences in baseline cognitive ability and training gains as well as potential moderators, we conducted a systematic meta-analysis of the correlation between these two variables. We found evidence of a significant meta-correlation demonstrating a compensatory effect, a negative association between initial ability on a trained cognitive process and training gains. Too few papers met our search criteria across the levels of proposed moderators of cognitive domain and training approach to conduct a reliable investigation of their influence over the meta-analytic effect size. We discuss the implications of a compensatory meta-correlation, potential reasons for the paucity of qualifying papers, and important future directions for better understanding how cognitive trainings work and for whom.

Training-induced improvement in working memory tasks results from switching to efficient strategies

It is debated whether training with a working memory (WM) task, particularly n-back, can improve general WM and reasoning skills. Most training studies found substantial improvement in the trained task, with little to no transfer to untrained tasks. We hypothesized that training does not increase WM capacity, but instead provides opportunities to develop an efficient task-specific strategy. We derived a strategy for the task that optimizes WM resources and taught it to participants. In two sessions, 14 participants who were taught this strategy performed as well as fourteen participants who trained for 40 sessions without strategy instructions. To understand the mechanisms underlying the no-instruction group's improvement, participants answered questionnaires during their training period. Their replies indicate that successful learners discovered the same strategy and their improvement was associated with this discovery. We conclude that n-back training allows the discovery of strategies that enable better performance with the same WM resources.

Working memory training: Taking a step back to retool and create a bridge between clinical and neuroimaging research methods

Improvements in patient outcomes and mortality after brain injury alongside increasing ageing population have resulted in an increasing need to develop cognitive interventions for individuals experiencing changes in their cognitive function. One topic of increasing research interest is whether cognitive functions such as attention, memory and executive functioning can be improved through the use of working memory training interventions. Both clinical and neuroimaging researchers are working to evidence this, but their efforts rarely come together. We discuss here several issues that may be hindering progress in this area, including the tools researchers utilize to measure cognition, the choice between employing active or passive control groups, the focus on transfer effects at the expense of well-characterized training effects, and the overall lack of neuroimaging studies in individuals with neurological disorders. We argue that the only way to advance the field is to build bridges between the disciplines of clinical neuropsychology and cognitive neuroscience. We suggest a multi-level framework to validate the efficacy of working memory interventions and other forms of cognitive training that combine both clinical and neuroimaging approaches. We conclude that in order to move forward we need to form multidisciplinary teams, employ interdisciplinary methods, brain imaging quality rating tools and build national and international collaborations based on open science principles.

MRI Predictors of Cognitive Training Outcomes

The prospect of improving or maintaining cognitive functioning has provoked a steadily increasing number of cognitive training interventions over the last years, especially for clinical and elderly populations. However, there are discrepancies between the findings of the studies. One of the reasons behind these heterogeneous findings is that there are vast inter-individual differences in how people benefit from the training and in the extent that training-related gains are transferred to other untrained tasks and domains. In this paper, we address the value of incorporating neural measures to cognitive training studies in order to fully understand the mechanisms leading to inter-individual differences in training gains and their generalizability to other tasks. Our perspective is that it is necessary to collect multimodal neural measures in the pre- and post-training phase, which can enable us to understand the factors contributing to successful training outcomes. More importantly, this understanding can enable us to predict who will benefit from different types of interventions, thereby allowing the development of individually tailored intervention programs.

Offloading items from memory: individual differences in cognitive offloading in a short-term memory task

Cognitive offloading refers to the act of reducing the mental processing requirements of a task through physical actions like writing down information or storing information on a cell phone or computer. Offloading can lead to improved performance on ongoing tasks with high cognitive demand, such as tasks where multiple pieces of information must be simultaneously maintained. However, less is known about why some individuals choose to engage in offloading and under what conditions they might choose to do so. In the present study, offloading behavior is investigated in a short-term memory task requiring memory for letters. The present study is a replication and extension of a previous study conducted by Risko and Dunn, and tests the new prediction that individuals with lower working memory capacity will be more likely to offload. Here, we find that offloading information confers a performance advantage over relying on internal memory stores, particularly at higher memory loads. However, we fail to observe that those with poorer memory abilities have a greater propensity for offloading or benefit more from it. Instead, our findings suggest that cognitive offloading may be a valid compensatory strategy to improve performance of memory-based tasks for individuals with a wide range of memory ability.

The Hype Cycle of Working Memory Training

Seventeen years and hundreds of studies after the first working memory training journal article was published, evidence for the efficacy of working memory training is still wanting. Numerous studies show that individuals who repeatedly practice computerized working memory tasks improve on those tasks and closely related variants. Critically, although individual studies have claimed improvements in untrained abilities and behaviors, systematic reviews of the broader literature show that studies producing large, positive findings are often those with the most methodological shortcomings. The current review discusses the past, present, and future status of working memory training, including consideration of factors that might influence working memory training and transfer efficacy.

The role of proactive interference in working memory training and transfer

Recent work on working memory training has produced conflicting results regarding the degree and generality of transfer to other cognitive processes. However, few studies have investigated possible mechanisms underlying transfer. The current study was designed to test the role of proactive interference in working memory training and transfer. Eighty-six young adults participated in a pretest-posttest design, with ten training sessions in between. In the two working memory training conditions, subjects performed an operation span task, with one condition requiring recall of letters on every trial (operation-letters), whereas the other condition alternated between letters, digits, and words as the to-be-remembered items across trials (operation-mix). These groups were compared to an active-control group (visual-search). Working memory, verbal fluency, and reading comprehension measures were administered in pretest and posttest sessions. All groups significantly increased their performance over the ten training sessions. There was evidence of strategy-specific benefits on transfer, such that transfer to working memory measures was higher for the operation-letters group on tasks specifically involving letters, and no differential transfer to working memory tests without letters, to verbal fluency, or to reading comprehension. The results indicate that proactive interference does not appear to play a causal role in determining transfer from working memory training, and instead a strategy account based on stimulus content provides a more parsimonious explanation for the pattern of training and transfer.