Neuronal effects following working memory training

AbstractThere is accumulating evidence that training working memory (WM) leads to beneficial effects in tasks that were not trained, but the mechanisms underlying this transfer remain elusive. Brain imaging can be a valuable method to gain insights into such mechanisms. Here, we discuss the impact of cognitive training on neural correlates with an emphasis on studies that implemented a WM intervention. We focus on changes in activation patterns, changes in resting state connectivity, changes in brain structure, and changes in the dopaminergic system. Our analysis of the existing literature reveals that there is currently no clear pattern of results that would single out a specific neural mechanism underlying training and transfer. We conclude that although brain imaging has provided us with information about the mechanisms of WM training, more research is needed to understand its neural impact

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\u27 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\u27 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

Exploring Age-Related Metamemory Differences using Modified Brier Scores and Hierarchical Clustering

Older adults (OAs) typically experience memory failures as they age. However, with some exceptions, studies of OAs’ ability to assess their own memory functions—Metamemory (MM)— find little evidence that this function is susceptible to age-related decline. Our study examines OAs’ and young adults’ (YAs) MM performance and strategy use. Groups of YAs (N = 138) and OAs (N = 79) performed a MM task that required participants to place bets on how likely they were to remember words in a list. Our analytical approach includes hierarchical clustering, and we introduce a new measure of MM—the modified Brier—in order to adjust for differences in scale usage between participants. Our data indicate that OAs and YAs differ in the strategies they use to assess their memory and in how well their MM matches with memory performance. However, there was no evidence that the chosen strategies were associated with differences in MM match, indicating that there are multiple strategies that might be effective (i.e. lead to similar match) in this MM task

Tuning the mind: Exploring the connections between musical ability and executive functions

A growing body of research suggests that musical experience and ability are related to a variety of cognitive abilities, including executive functioning (EF). However, it is not yet clear if these relationships are limited to specific components of EF, limited to auditory tasks, or reflect very general cognitive advantages. This study investigated the existence and generality of the relationship between musical ability and EFs by evaluating the musical experience and ability of a large group of participants and investigating whether this predicts individual differences on three different components of EF – inhibition, updating, and switching – in both auditory and visual modalities. Musical ability predicted better performance on both auditory and visual updating tasks, even when controlling for a variety of potential confounds (age, handedness, bilingualism, and socio-economic status). However, musical ability was not clearly related to inhibitory control and was unrelated to switching performance. These data thus show that cognitive advantages associated with musical ability are not limited to auditory processes, but are limited to specific aspects of EF. This supports a process-specific (but modality-general) relationship between musical ability and non-musical aspects of cognition.GRAMMY Foundatio

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training

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

The role of attention to emotion in recovery from major depressive disorder

Major Depressive Disorder (MDD) is characterized by several emotional disturbances. One possible but not well-examined disturbance is in attention to emotion, an important facet of emotional awareness. We examined whether attention to emotion predicted recovery from MDD. Fifty-three adults with current MDD completed a week of experience sampling (Time 1). At each prompt, participants reported attention to emotion, negative affect (NA), and positive affect (PA). Approximately one year later (Time 2), the depressive status of 27 participants was reassessed. Participants who had recovered from MDD (n=8) indicated paying less attention to their emotions at Time 1 than did participants who had not fully recovered (n=19). Attention to emotion was better predictor of recovery than was severity of MDD, NA, or PA at Time 1. Levels of attention to emotion at Time 1 in participants who recovered from MDD did not differ significantly from the levels reported by 53 never-depressed individuals who had participated in the experience sampling. Findings indicate that high levels of an otherwise adaptive emotional facet can adversely affect the course of MDD

Las variaciones de superficie cortical en la corteza dorsolateral prefrontal predicen mejor el futuro desempeño cognitivo que la inteligencia fluida y la memoria operativa

Are cognitive and biological variables useful for predicting future behavioral outcomes? Method: In two independent groups, we measured a set of cognitive (fluid and crystallized intelligence, working memory, and attention control) and biological (cortical thickness and cortical surface area) variables on two occasions separated by six months, to predict behavioral outcomes of interest (performance on an adaptive version of the n-back task) measured twelve and eighteen months later. We followed three stages: discovery, validation, and generalization. In the discovery stage, cognitive/biological variables and the behavioral outcome of interest were assessed in a group of individuals (in-sample). In the validation stage, the cognitive and biological variables were related with a parallel version of the behavioral outcome assessed several months later. In the generalization stage, the validation findings were tested in an independent group of individuals (out-of-sample). Results: The key fi nding revealed that cortical surface area variations within the right dorsolateral prefrontal cortex predict the behavioral outcome of interest in both groups, whereas the cognitive variables failed to show reliable predictive validity. Conclusions: Individual differences in biological variables might predict future behavioral outcomes better than cognitive variables concurrently correlated with these behavioral outcomesAntecedentes: ¿Predicen las variables cognitivas y biológicas el futuro desempeño cognitivo? Método: en dos grupos independientes de participantes se miden variables cognitivas (inteligencia fluida y cristalizada, memoria operativa y control atencional) y biológicas (grosor y superficie cortical) en dos ocasiones separadas por seis meses, para predecir el desempeño en la tarea n-back valorado doce y dieciocho meses después. Se completan tres etapas: descubrimiento, validación y generalización. En la de descubrimiento se valoran en un grupo de individuos las variables cognitivas/biológicas y el desempeño a predecir. En la de validación, se relacionan las mismas variables con una versión paralela de la n-back completada meses después. En la de generalización, los resultados de la validación se replican en un grupo independiente de individuos. Resultados: las variaciones de superficie cortical en la corteza dorsolateral prefrontal derecha predicen el desempeño cognitivo en los dos grupos independientes de individuos, mientras que las variables cognitivas no contribuyen a la predicción del desempeño futuro. Conclusiones: las diferencias individuales en determinadas variables biológicas predicen el desempeño cognitivo mejor que las variables cognitivas que correlacionan concurrentemente con ese desempeñoThis project was supported by PSI2017-82218-P (Ministerio de Economía, Industria y Competitividad, Spain

The Role of Attention to Emotion in Recovery from Major Depressive Disorder

Major Depressive Disorder (MDD) is characterized by several emotional disturbances. One possible but not well-examined disturbance is in attention to emotion, an important facet of emotional awareness. We examined whether attention to emotion predicted recovery from MDD. Fifty-three adults with current MDD completed a week of experience sampling (Time 1). At each prompt, participants reported attention to emotion, negative affect (NA), and positive affect (PA). Approximately one year later (Time 2), the depressive status of 27 participants was reassessed. Participants who had recovered from MDD (n = 8) indicated paying less attention to their emotions at Time 1 than did participants who had not fully recovered (n = 19). Attention to emotion was better predictor of recovery than was severity of MDD, NA, or PA at Time 1. Levels of attention to emotion at Time 1 in participants who recovered from MDD did not differ significantly from the levels reported by 53 never-depressed individuals who had participated in the experience sampling. Findings indicate that high levels of an otherwise adaptive emotional facet can adversely affect the course of MDD