Game-based training of flexibility and attention improves task-switch performance: near and far transfer of cognitive training in an EEG study

A cross-dataset adaptive domain selection transfer learning framework for motor imagery-based brain-computer interfaces

Objective. In brain-computer interfaces (BCIs) that utilize motor imagery (MI), minimizing calibration time has become increasingly critical for real-world applications. Recently, transfer learning (TL) has been shown to effectively reduce the calibration time in MI-BCIs. However, variations in data distribution among subjects can significantly influence the performance of TL in MI-BCIs.Approach.We propose a cross-dataset adaptive domain selection transfer learning framework that integrates domain selection, data alignment, and an enhanced common spatial pattern (CSP) algorithm. Our approach uses a huge dataset of 109 subjects as the source domain. We begin by identifying non-BCI illiterate subjects from this huge dataset, then determine the source domain subjects most closely aligned with the target subjects using maximum mean discrepancy. After undergoing Euclidean alignment processing, features are extracted by multiple composite CSP. The final classification is carried out using the support vector machine.Main results.Our findings indicate that the proposed technique outperforms existing methods, achieving classification accuracies of 75.05% and 76.82% in two cross-dataset experiments, respectively.Significance.By reducing the need for extensive training data, yet maintaining high accuracy, our method optimizes the practical implementation of MI-BCIs.

A process model of parental executive functioning as a spillover mechanism linking interparental conflict and parenting difficulties across parenting domains

There is a well-documented interdependency between destructive interparental conflict (IPC) and parenting difficulties (i.e., spillover effect), yet little is known about the mechanisms that "carry" spillover between IPC and parenting. Guided by a cascade model framework, the current study used a longitudinal, multimethod, multi-informant design to examine a process model of spillover that tested whether parental executive functioning (working memory, cognitive flexibility, inhibitory control) served as a mediator of the prospective associations between IPC and subsequent changes in parenting over a 2-year period. Mothers and fathers were separated into differentiated models and multiple domains of parenting were examined (i.e., authoritarian discipline and scaffolding behavior). Participants included 231 families (both mothers and fathers of preschoolers). Race was reported as White (62%), Black (21%), Mixed (8%), Asian (3%), or Other (6%) and 14% considered their ethnicity to be Hispanic/Latino. Median household income was $65,000. Results indicated that for fathers, IPC indirectly predicted domain-general parenting difficulties (increased authoritarian parenting and decreased scaffolding) via deficits in paternal cognitive flexibility (but not inhibitory control or working memory). In mothers, IPC directly predicted domain-specific parenting difficulties (decreased scaffolding only) that did not operate via maternal executive functions. Notably, these effects occurred over and above the influence of parental socioeconomic status. This study constitutes a first step toward documenting parental executive functioning as a mechanism underlying the spillover of IPC to the parent-child relationship. Family interventions intended to interrupt IPC spillover should emphasize father involvement and consider targeting parental executive functions as change mechanisms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Heart rate and breathing effects on attention and memory (HeartBEAM): study protocol for a randomized controlled trial in older adults

BACKGROUND

In healthy people, the "fight-or-flight" sympathetic system is counterbalanced by the "rest-and-digest" parasympathetic system. As we grow older, the parasympathetic system declines as the sympathetic system becomes hyperactive. In our prior heart rate variability biofeedback and emotion regulation (HRV-ER) clinical trial, we found that increasing parasympathetic activity through daily practice of slow-paced breathing significantly decreased plasma amyloid-β (Aβ) in healthy younger and older adults. In healthy adults, higher plasma Aβ is associated with greater risk of Alzheimer's disease (AD). Our primary goal of this trial is to reproduce and extend our initial findings regarding effects of slow-paced breathing on Aβ. Our secondary objectives are to examine the effects of daily slow-paced breathing on brain structure and the rate of learning.

METHODS

Adults aged 50-70 have been randomized to practice one of two breathing protocols twice daily for 9 weeks: (1) "slow-paced breathing condition" involving daily cognitive training followed by slow-paced breathing designed to maximize heart rate oscillations or (2) "random-paced breathing condition" involving daily cognitive training followed by random-paced breathing to avoid increasing heart rate oscillations. The primary outcomes are plasma Aβ40 and Aβ42 levels and plasma Aβ42/40 ratio. The secondary outcomes are brain perivascular space volume, hippocampal volume, and learning rates measured by cognitive training performance. Other pre-registered outcomes include plasma pTau-181/tTau ratio and urine Aβ42. Recruitment began in January 2023. Interventions are ongoing and will be completed by the end of 2023.

DISCUSSION

Our HRV-ER trial was groundbreaking in demonstrating that a behavioral intervention can reduce plasma Aβ levels relative to a randomized control group. We aim to reproduce these findings while testing effects on brain clearance pathways and cognition.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05602220. Registered on January 12, 2023.

Measuring cognitive flexibility: A brief review of neuropsychological, self-report, and neuroscientific approaches

Cognitive flexibility involves dynamic processes that allow adaptation of our thinking and behavior in response to changing contextual demands. Despite a large consensus about its beneficial effects, cognitive flexibility is still poorly understood. In this mini review, we examined the main conceptualizations and approaches for assessing cognitive flexibility: (1) neuropsychological tasks, (2) self-report questionnaires, and (3) neuroscientific approaches. The reviewed evidence shows that the definition and assessment of cognitive flexibility are not unified within the field and suggests that a more consensual and consistent conceptualization and operationalization of this important concept is needed. We propose that an integrative behavior-brain-context approach can help advance our understanding of cognitive flexibility.

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.

LMDA-Net:A lightweight multi-dimensional attention network for general EEG-based brain-computer interfaces and interpretability

Electroencephalography (EEG)-based brain-computer interfaces (BCIs) pose a challenge for decoding due to their low spatial resolution and signal-to-noise ratio. Typically, EEG-based recognition of activities and states involves the use of prior neuroscience knowledge to generate quantitative EEG features, which may limit BCI performance. Although neural network-based methods can effectively extract features, they often encounter issues such as poor generalization across datasets, high predicting volatility, and low model interpretability. To address these limitations, we propose a novel lightweight multi-dimensional attention network, called LMDA-Net. By incorporating two novel attention modules designed specifically for EEG signals, the channel attention module and the depth attention module, LMDA-Net is able to effectively integrate features from multiple dimensions, resulting in improved classification performance across various BCI tasks. LMDA-Net was evaluated on four high-impact public datasets, including motor imagery (MI) and P300-Speller, and was compared with other representative models. The experimental results demonstrate that LMDA-Net outperforms other representative methods in terms of classification accuracy and predicting volatility, achieving the highest accuracy in all datasets within 300 training epochs. Ablation experiments further confirm the effectiveness of the channel attention module and the depth attention module. To facilitate an in-depth understanding of the features extracted by LMDA-Net, we propose class-specific neural network feature interpretability algorithms that are suitable for evoked responses and endogenous activities. By mapping the output of the specific layer of LMDA-Net to the time or spatial domain through class activation maps, the resulting feature visualizations can provide interpretable analysis and establish connections with EEG time-spatial analysis in neuroscience. In summary, LMDA-Net shows great potential as a general decoding model for various EEG tasks.

Effects of Near-Infrared Pulsed Light on the Attention of Human Beings Using Electroencephalography

In our previous studies, photobiomodulation (PBM) stimulation can induce significant brain activation in normal subjects. In an open-eye study, the PBM stimulation was able to increase the power of alpha rhythms and theta waves, as well as decrease the beta activities after PBM stimulation. However, in the closed eyes study, the alpha rhythms in the laser group were reduced. This means the PBM stimulation can induce specific brainwaves under different conditions. Thus, to investigate the effects of PBM stimulation on human's attention, forty students were recruited in this single-blind randomized trial. A PBM stimulator, with seven pcs laser diodes (LDs), frequency 10 Hz, 30 mW/each LD, and wavelength 830 nm, was used to radiate the palm of the subject. PBM stimulation was found to induce significant variation in beta activity in most of the regions of the brain in the laser group. Compared to the placebo group, the PBM stimulation has a significant change in beta activity on electroencephalography (EEG). Three types of tests, the random number test, the Stroop color-word test, and the Multiple-Dimension Attention Test (MDAT), were used to evaluate the effects of the PBM stimulation. The scores of MDAT in the laser group increased more significantly than those in the placebo group after PBM stimulation (p < 0.01). An improvement in attention was observed in this study.

Does Tennis Training Improve Attention? New Approach

This study aimed to examine the effect of a tennis training program on improving attention.

METHODS

A total of 40 tennis players from a Tennis Club, 20 in the experimental group (EG) and 20 in the control group (CG), participated in the study. The EG athletes received 40 serve balls from the trainer twice a week for nine weeks. The researcher applied the "d2 attention test" to the EG and CG before and after the nine-week period.

RESULTS

After comparing the pretest and posttest attention averages of the experimental group, there was a significant difference in the TN, TN-E, and CP mean scores (p < 0.001). In the comparison of the pretest and posttest attention averages of the CG, there was no significant difference in the TN, TN-E, and CP mean scores (p > 0.05). The comparison of the pretest attention averages of the EG and CG revealed no significant difference in the TN, TN-E, and CP mean scores (p > 0.05). The comparison of the posttest attention averages of the EG and CG revealed a significant difference in the mean scores of TN, TN-E, and CP (p < 0.05). There was a statistically significant difference between the posttest-pretest differences in the TN, TN-E, and CP values of the EG and CG (p < 0.05).

CONCLUSIONS

The study concluded that tennis training aimed at developing attention improved the results in the attention test.

Action Video Gaming and Attention in Young Adults: A Systematic Review

OBJECTIVE

Existing research in action video games has increased in recent years due to the expansion of their use all over the world. Specifically, there is growing evidence about the positive development of the cognitive functions associated with the use of this kind of video game. Therefore, this work aims to explore the relationship between playing action video games and the development of attention span as well as the impact at the brain level from a functional perspective.

METHODS

Articles were searched in Scopus, Pubmed, and Web of Science. A total of 196 studies were retrieved, among which 13 studies were systematically reviewed.

RESULTS

The review has shown that playing action video games can improve cognitive functions, including attention, with reaction time and processing speed being the aspects that would most benefit from such practice, as well as the development of focused, sustained, and divided attention. Also, there are functional brain changes.

CONCLUSION

It is necessary to deepen the understanding of the association between playing action video games and the development of attention.

Artificial Cognitive Systems Applied in Executive Function Stimulation and Rehabilitation Programs: A Systematic Review

This article presents a systematic review of studies on cognitive training programs based on artificial cognitive systems and digital technologies and their effect on executive functions. The aim has been to identify which populations have been studied, the characteristics of the implemented programs, the types of implemented cognitive systems and digital technologies, the evaluated executive functions, and the key findings of these studies. The review has been carried out following the PRISMA protocol; five databases have been selected from which 1889 records were extracted. The articles were filtered following established criteria, to give a final selection of 264 articles that have been used for the purposes of this study in the analysis phase. The findings showed that the most studied populations were school-age children and the elderly. The most studied executive functions were working memory and attentional processes, followed by inhibitory control and processing speed. Many programs were commercial, customizable, gamified, and based on classic tasks. Some more recent initiatives have begun to incorporate user-machine interfaces, robotics, and virtual reality, although studies on their effects remain scarce. The studies recognize multiple benefits of computerized neuropsychological stimulation and rehabilitation programs for executive functions in different age groups, but there is a lack of studies in specific population sectors and with more rigorous research designs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13369-022-07292-5.

Does Cognitive Training Improve Mobility, Enhance Cognition, and Promote Neural Activation?

A close inter-relationship between mobility and cognition is reported in older adults, with improvements in gait performance noticeable after cognitive remediation in frail individuals. The aim of this study was to evaluate the efficacy of computerized cognitive training (CCT) on mobility in healthy, independently living older adults, and to determine whether CCT is associated with changes in neural activation for mobility-related brain processes. Using a randomized single-blind control design, sixty-three non-demented adults age 60 y and older (mean age = 67 y; 76% female, mean Montreal Cognitive Assessment [MoCA] score = 27) were recruited from a local Senior Activity Center. Participants were randomly assigned to either a 2-month CCT program (8 weeks, 3x/week, 40 min/session) or a wait-list control group. Primary outcome was self-selected gait speed during single- and dual-task walking. Secondary outcome was executive function on Trail Making Test (TMT), Part B. Neural activity was assessed via electroencephalography/event-related potentials (EEG/ERPs) targeting lower-limb performance. Results from a linear mixed effect model, adjusted for baseline MoCA score, age, gender, and study completion revealed that compared to controls, CCT improved gait speed during the dual-task (p = 0.008) but not during the single-task walking condition (p = 0.057). CCT also improved executive function (p = 0.024). Further, shorter foot reaction time responses (p = 0.019) were found with enhanced neural activation over sensorimotor areas, with shorter ERP latencies during the P2 component (p = 0.008) and enhanced motor responses (p = 0.009) also evident in the CCT group after the intervention. Overall, the electrophysiological findings suggest possible neural adaptations that could explain improvements in mobility and executive functions associated with CCT in healthy older adults.

Effects of exergame and video game training on cognitive and physical function in older adults: A randomized controlled trial

Few studies have simultaneously explored the training effects of exergame and video game. The purpose of this study was to investigate the effects of exergame and video game training on cognitive and physical function in healthy older adults. Eighty-four healthy older adults were randomly assigned to exergame training group, video game training group, and control group. Cognitive and physical function was measured before and after the training. Both training groups improved in verbal memory and aerobic endurance, but the training effects were greater in the exergame training group. The exergame training group also showed significant improvement in lower limb strength and balance. The current study provides evidence that exergame training, incorporating both cognitive engagement and physical activity, exerts greater benefits than cognitively engaging video game training alone. The findings shed lights into the future use of exergame in preventing cognitive and physical function decline in older adults.

Longitudinal white matter changes associated with cognitive training

Improvements in behavior are known to be accompanied by both structural and functional changes in the brain. However, whether those changes lead to more general improvements, beyond the behavior being trained, remains a contentious issue. We investigated whether training on one of two cognitive tasks would lead to either near transfer (that is, improvements on a quantifiably similar task) or far transfer (that is, improvements on a quantifiably different task), and furthermore, if such changes did occur, what the underlying neural mechanisms might be. Healthy adults (n = 16, 15 females) trained on either a verbal inhibitory control task or a visuospatial working memory task for 4 weeks, over the course of which they received five diffusion tensor imaging scans. Two additional tasks served as measures of near and far transfer. Behaviorally, participants improved on the task that they trained on, but did not improve on cognitively similar tests (near transfer), nor cognitively dissimilar tests (far transfer). Extensive changes to white matter microstructure were observed, with verbal inhibitory control training leading to changes in a left-lateralized network of frontotemporal and occipitofrontal tracts, and visuospatial working memory training leading to changes in right-lateralized frontoparietal tracts. Very little overlap was observed in changes between the two training groups. On the basis of these results, we suggest that near and far transfer were not observed because the changes in white matter tracts associated with training on each task are almost entirely nonoverlapping with, and therefore afford no advantages for, the untrained tasks.

EEG Correlates of Sustained Attention Variability during Discrete Multi-finger Force Control Tasks

The neurophysiological characteristics of sustained attention states are unclear in discrete multi-finger force control tasks. In this article, we developed an immersive visuo-haptic task for conducting stimulus-response measurements. Visual cues were randomly provided to signify the required amplitude and tolerance of fingertip force. Participants were required to respond to the visual cues by pressing force transducers using their fingertips. Response time variation was taken as a behavioral measure of sustained attention states during the task. 50% low-variability trials were classified as the optimal state and the other high-variability trials were classified as the suboptimal state using z-scoring over time. A 64-channel electroencephalogram (EEG) acquisition system was used to collect brain activities during the tasks. The haptics-elicited potential amplitude at 20 ∼ 40 ms in latency and over the frontal-central region significantly decreased in the optimal state. Furthermore, the alpha-band power in the spectra of 8 ∼ 13 Hz was significantly suppressed in the frontal-central, right temporal, and parietal regions in the optimal state. Taken together, we have identified neuroelectrophysiological features that were associated with sustained attention during multi-finger force control tasks, which would be potentially used in the development of closed-loop attention detection and training systems exploiting haptic interaction.

Short-Term Audiovisual Spatial Training Enhances Electrophysiological Correlates of Auditory Selective Spatial Attention

Audiovisual cross-modal training has been proposed as a tool to improve human spatial hearing. Here, we investigated training-induced modulations of event-related potential (ERP) components that have been associated with processes of auditory selective spatial attention when a speaker of interest has to be localized in a multiple speaker ("cocktail-party") scenario. Forty-five healthy participants were tested, including younger (19-29 years; n = 21) and older (66-76 years; n = 24) age groups. Three conditions of short-term training (duration 15 min) were compared, requiring localization of non-speech targets under "cocktail-party" conditions with either (1) synchronous presentation of co-localized auditory-target and visual stimuli (audiovisual-congruency training) or (2) immediate visual feedback on correct or incorrect localization responses (visual-feedback training), or (3) presentation of spatially incongruent auditory-target and visual stimuli presented at random positions with synchronous onset (control condition). Prior to and after training, participants were tested in an auditory spatial attention task (15 min), requiring localization of a predefined spoken word out of three distractor words, which were presented with synchronous stimulus onset from different positions. Peaks of ERP components were analyzed with a specific focus on the N2, which is known to be a correlate of auditory selective spatial attention. N2 amplitudes were significantly larger after audiovisual-congruency training compared with the remaining training conditions for younger, but not older, participants. Also, at the time of the N2, distributed source analysis revealed an enhancement of neural activity induced by audiovisual-congruency training in dorsolateral prefrontal cortex (Brodmann area 9) for the younger group. These findings suggest that cross-modal processes induced by audiovisual-congruency training under "cocktail-party" conditions at a short time scale resulted in an enhancement of correlates of auditory selective spatial attention.

Anodal Transcranial Direct Current Stimulation-Induced Effects Over the Right Dorsolateral Prefrontal Cortex: Differences in the Task Types of Task Switching

Transcranial direct current stimulation (tDCS) has been previously used to investigate the causal relationships between the dorsolateral prefrontal cortex (DLPFC) and task switching but has delivered inconclusive results that may be due to different switching tasks involving different cognitive control processes. In the current study, we manipulated task types and task predictability to investigate the role of DLPFC in task-switching performances. Notably, we distinguished the specific effects of anodal-tDCS on two types of tasks (parity/magnitude and parity/vowel-consonant tasks). Forty-eight participants were randomly assigned to four task groups as follows; Group I who was assigned right anode (RA) parity/magnitude tasks, Group II who were assigned sham parity/magnitude tasks, Group III who were assigned RA parity/vowel-consonant tasks, and Group IV who were assigned sham parity/vowel-consonant tasks. Participants were asked to complete both predictable and unpredictable tasks. In the parity/magnitude task, we demonstrated a lower switch cost for the RA group compared to the sham group for unpredictable tasks. In contrast, in the parity/vowel-consonant task, the switch cost was higher for the RA group compared to the sham group for unpredictable and predictable tasks. These findings confirmed an anodal-tDCS-induced effect over the right DLPFC both in the parity/magnitude and parity/vowel-consonant tasks. Our data indicated that anodal tDCS may have a stronger influence on task-switching performance over the right DLPFC by changing the irrelevant task-set inhibition process. Also, the right DLPFC is unlikely to act by performing exogenous adjustment of predictable task switching.

Dynamic Joint Domain Adaptation Network for Motor Imagery Classification

Electroencephalogram (EEG) has been widely used in brain computer interface (BCI) due to its convenience and reliability. The EEG-based BCI applications are majorly limited by the time-consuming calibration procedure for discriminative feature representation and classification. Existing EEG classification methods either heavily depend on the handcrafted features or require adequate annotated samples at each session for calibration. To address these issues, we propose a novel dynamic joint domain adaptation network based on adversarial learning strategy to learn domain-invariant feature representation, and thus improve EEG classification performance in the target domain by leveraging useful information from the source session. Specifically, we explore the global discriminator to align the marginal distribution across domains, and the local discriminator to reduce the conditional distribution discrepancy between sub-domains via conditioning on deep representation as well as the predicted labels from the classifier. In addition, we further investigate a dynamic adversarial factor to adaptively estimate the relative importance of alignment between the marginal and conditional distributions. To evaluate the efficacy of our method, extensive experiments are conducted on two public EEG datasets, namely, Datasets IIa and IIb of BCI Competition IV. The experimental results demonstrate that the proposed method achieves superior performance compared with the state-of-the-art methods.

Deep Representation-Based Domain Adaptation for Nonstationary EEG Classification

In the context of motor imagery, electroencephalography (EEG) data vary from subject to subject such that the performance of a classifier trained on data of multiple subjects from a specific domain typically degrades when applied to a different subject. While collecting enough samples from each subject would address this issue, it is often too time-consuming and impractical. To tackle this problem, we propose a novel end-to-end deep domain adaptation method to improve the classification performance on a single subject (target domain) by taking the useful information from multiple subjects (source domain) into consideration. Especially, the proposed method jointly optimizes three modules, including a feature extractor, a classifier, and a domain discriminator. The feature extractor learns the discriminative latent features by mapping the raw EEG signals into a deep representation space. A center loss is further employed to constrain an invariant feature space and reduce the intrasubject nonstationarity. Furthermore, the domain discriminator matches the feature distribution shift between source and target domains by an adversarial learning strategy. Finally, based on the consistent deep features from both domains, the classifier is able to leverage the information from the source domain and accurately predict the label in the target domain at the test time. To evaluate our method, we have conducted extensive experiments on two real public EEG data sets, data set IIa, and data set IIb of brain-computer interface (BCI) Competition IV. The experimental results validate the efficacy of our method. Therefore, our method is promising to reduce the calibration time for the use of BCI and promote the development of BCI.

Impact of Chronic Stress on Attention Control: Evidence from Behavioral and Event-Related Potential Analyses

Chronic stress affects brain function, so assessing its hazards is important for mental health. To overcome the limitations of behavioral data, we combined behavioral and event-related potentials (ERPs) in an attention network task. This task allowed us to differentiate between three specific aspects of attention: alerting, orienting, and execution. Forty-one participants under chronic stress and 31 non-stressed participants were enrolled. On the performance level, the chronically stressed group showed a significantly slower task response and lower accuracy. Concerning ERP measures, smaller cue-N1, cue-N2, and larger cue-P3 amplitudes were found in the stressed group, indicating that this group was less able to assign attention to effective information, i.e., they made inefficient use of cues and had difficulty in maintaining alerting. In addition, the stressed group showed larger target-N2 amplitudes, indicating that this group needed to allocate more cognitive resources to deal with the conflict targets task. Subgroup analysis revealed lower target-P3 amplitudes in the stressed than in the non-stressed group. Group differences associated with the attention networks were found at the ERP level. In the stressed group, excessive depletion of resources led to changes in attention control. In this study, we examined the effects of chronic stress on individual executive function from a neurological perspective. The results may benefit the development of interventions to improve executive function in chronically stressed individuals.

Enhancing task-demands disrupts learning but enhances transfer gains in short-term task-switching training

Content variability was previously suggested to promote stronger learning effects in cognitive training whereas less variability incurred transfer costs (Sabah et al. Psychological Research, 10.1007/s00426-018-1006-7, 2018). Here, we expanded these findings by additionally examining the role of learners’ control in short-term task-switching training by comparing voluntary task-switching to a yoked control forced task-switching condition. To this end, four training conditions were compared: (1) forced fixed content, (2) voluntary fixed content, (3) forced varied content, and (3) voluntary varied content. To further enhance task demands, bivalent stimuli were used during training. Participants completed baseline assessment commencing with task-switching and verbal fluency blocks, followed by seven training blocks and last by task-switching (near transfer) and verbal fluency (far transfer) blocks, respectively. For the baseline and transfer task-switching blocks, we used the exact same baseline and first transfer block from Sabah et al. (Psychological Research, 10.1007/s00426-018-1006-7, 2018), employing univalent stimuli and alternating-runs task sequence. Our results pointed again to the contribution of content variability to task-switching performance. No indications for far transfer were observed. Allowing for learners’ control was not found to produce additional transfer gains beyond content variability. A between-study comparison suggests that enhanced task demands, by means of bivalency, promoted higher transfer gains in the current study when compared to Sabah et al. (Psychological Research, 10.1007/s00426-018-1006-7, 2018). Taken together, the current results provide further evidence to the beneficial impact of variability on training outcomes. The lack of modulatory effect for learners’ control is discussed in relation to possible methodological limitations.

From Evaluation to Prediction: Behavioral Effects and Biological Markers of Cognitive Control Intervention

Although the intervention effectiveness of cognitive control is disputed, some methods, such as single-task training, integrated training, meditation, aerobic exercise, and transcranial stimulation, have been reported to improve cognitive control. This review of recent advances from evaluation to prediction of cognitive control interventions suggests that brain modularity may be an important candidate marker for informing clinical decisions regarding suitable interventions. The intervention effect of cognitive control has been evaluated by behavioral performance, transfer effect, brain structure and function, and brain networks. Brain modularity can predict the benefits of cognitive control interventions based on individual differences and is independent of intervention method, group, age, initial cognitive ability, and education level. The prediction of cognitive control intervention based on brain modularity should extend to task states, combine function and structure networks, and assign different weights to subnetwork modularity.

Effects of a Computerized Training on Attentional Capacity of Young Soccer Players

The purpose of this work was to analyze the effects of a computerized training on attentional capacity in a group of young soccer players. Seventy-five male adolescents from two soccer clubs in the city of Malaga (Spain) and aged between 14 and 18 (15.45 ± 1.43 years) participated in the investigation. A quasi-experimental design was used, and the adolescents were divided into control (n = 38) and experimental (n = 37) groups. The experimental group underwent a computerized training (Rejilla 1.0) of their attention during 9 weeks and 27 sessions. In addition, the D2 attention test was used to analyze the evolution of participants after the intervention program. The results showed positive effects of the computerized intervention program on selective attention, observing changes both in the executions of the software used (p < 0.001, Cohen's d = 1.58, 95% CI [1.06, 2.11]) and in the main measures of the D2 test, total effectiveness (p < 0.001, Cohen's d = 0.62, 95% CI [0.15, 1.08]) and concentration (p < 0.01, Cohen's d = 0.48, 95% CI [0.02, 0.94]).

ERP and Behavioral Effects of Physical and Cognitive Training on Working Memory in Aging: A Randomized Controlled Study

Working memory (WM) performance decreases with age. A promising method to improve WM is physical or cognitive training. The present randomized controlled study is aimed at evaluating the effects of different training methods on WM. A sample of 141 healthy older adults (mean age 70 years) was assigned to one of four groups: physical training, cognitive training, a social control group, and a no-contact control group. The participants trained for four months. Before and after the training, n-back task during an EEG recording was applied. The results show that cognitive training enhanced the target detection rate in the 2-back task. This was corroborated by an increased number of repeated digits in the backward digit-span test but not in other memory tests. The improvement of WM was supported by an increased P3a prior to a correct target and an increased P3b both in nontarget and target trials. No ERP effects in the physical and no-contact control groups were found, while a reduction of P3a and P3b was found in the social control group. Thus, cognitive training enhances frontal and parietal processing related to the maintenance of a stored stimulus for subsequent matching with an upcoming stimulus and increases allocation of cognitive resources. These results indicate that multidomain cognitive training may increase WM capacity and neuronal activity in older age.