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.

Near transfer to an unrelated N-back task mediates the effect of N-back working memory training on matrix reasoning.

The extent to which working memory training improves performance on untrained tasks is highly controversial. Here we address this controversy by testing the hypothesis that far transfer may depend on near transfer using mediation models in three separate randomized controlled trials (RCTs). In all three RCTs, totalling 460 individuals, performance on untrained N-back tasks (near transfer) mediated transfer to Matrix Reasoning (representing far transfer) despite the lack of an intervention effect in RCTs 2 and 3. Untrained N-back performance also mediated transfer to a working memory composite, which showed a significant intervention effect (RCT 3). These findings support a model of N-back training in which transfer to untrained N-back tasks gates further transfer (at least in the case of working memory at the construct level) and Matrix Reasoning. This model can help adjudicate between the many studies and meta-analyses of working memory training that have provided mixed results but have not examined the relationship between near and far transfer on an individual-differences level.

Video-Based Remote Administration of Cognitive Assessments and Interventions: a Comparison with In-Lab Administration.

While remote data collection is not a new concept, the quality and psychometric properties of data collected remotely often remain unclear. Most remote data collection is done via online survey tools or web-conferencing applications (i.e., Skype or Zoom) and largely involves questionnaires, interviews, or other self-report data. Little research has been done on the collection of cognitive assessments and interventions via web-conferencing that requires multiple sessions with or without the assistance of an experimenter. The present paper discusses limitations and challenges of studies administered remotely, and outlines methods used to overcome such challenges while effectively collecting cognitive performance data remotely via Zoom. We further discuss relative recruitment, retention rates, compliance, and performance findings between in-lab and remotely administered cognitive assessment and intervention studies, as well as limitations to remote data collection. We found that while it was necessary to recruit more participants in remote studies to reach enrollment goals, compliance and performance were largely comparable between in-lab and remotely administered studies, illustrating the opportunities of conducting this type of experimental research remotely with adequate fidelity.

UCancellation: A new mobile measure of selective attention and concentration.

Measuring selective attention in a speeded task can provide valuable insight into the concentration ability of an individual, and can inform neuropsychological assessment of attention in aging, traumatic brain injury, and in various psychiatric disorders. There are only a few tools to measure selective attention that are freely available, psychometrically validated, and can be used flexibly both for in-person and remote assessment. To address this gap, we developed a self-administrable, mobile-based test called "UCancellation" (University of California Cancellation), which was designed to assess selective attention and concentration and has two stimulus sets: Letters and Pictures. UCancellation takes less than 7 minutes to complete, is automatically scored, has multiple forms to allow repeated testing, and is compatible with a variety of iOS and Android devices. Here we report the results of a study that examined parallel-test reliability and convergent validity of UCancellation in a sample of 104 college students. UCancellation Letters and Pictures showed adequate parallel test reliability (r = .71-.83, p < 0.01) and internal consistency (ɑ = .73-.91). It also showed convergent validity with another widely used cancellation task, d2 Test of Attention (r = .43-.59, p < 0.01), and predicted performance on a cognitive control composite (r = .34-.41, p < 0.05). These results suggest that UCancellation is a valid test of selective attention and inhibitory control, which warrants further data collection to establish norms.

Multisensory Facilitation of Working Memory Training.

Research suggests that memorization of multisensory stimuli benefits performance compared to memorization of unisensory stimuli; however, little is known about multisensory facilitation in the context of working memory (WM) training and transfer. To investigate this, 240 adults were randomly assigned to an N-back training task that consisted of visual-only stimuli, alternating visual and auditory blocks, or audio-visual (multisensory) stimuli, or to a passive control group. Participants in the active groups completed 13 sessions of N-back training (6.7 hours in total) and all groups completed a battery of WM tasks: untrained N-back tasks, Corsi Blocks, Sequencing, and Symmetry Span. The Multisensory group showed similar training N-level gain compared to the Visual Only group, and both of these groups outperformed the Alternating group on the training task. As expected, all three active groups significantly improved on untrained visual N-back tasks compared to the Control group. In contrast, the Multisensory group showed significantly greater gains on the Symmetry Span task and to a certain extent on the Sequencing task compared to other groups. These results tentatively suggest that incorporating multisensory objects in a WM training protocol can benefit performance on the training task and potentially facilitate transfer to complex WM span tasks.

N-Back Related ERPs Depend on Stimulus Type, Task Structure, Pre-processing, and Lab Factors.

The N-Back, a common working memory (WM) updating task, is increasingly used in basic and applied psychological research. As such, an increasing number of electroencephalogram (EEG) studies have sought to identify the electrophysiological signatures of N-Back task performance. However, stimulus type, task structure, pre-processing methods, and differences in the laboratory environment, including the EEG recording setup employed, greatly vary across studies, which in turn may introduce inconsistencies in the obtained results. Here we address this issue by conducting nine different variations of an N-Back task manipulating stimulus type and task structure. Furthermore, we explored the effect of the pre-processing method used and differences in the laboratory environment. Results reveal significant differences in behavioral and electrophysiological signatures in response to N-Back stimulus type, task structure, pre-processing method, and laboratory environment. In conclusion, we suggest that experimental factors, analysis pipeline, and laboratory differences, which are often ignored in the literature, need to be accounted for when interpreting findings and making comparisons across studies.

Application of Machine Learning Models for Tracking Participant Skills in Cognitive Training.

A key need in cognitive training interventions is to personalize task difficulty to each user and to adapt this difficulty to continually apply appropriate challenges as users improve their skill to perform the tasks. Here we examine how Bayesian filtering approaches, such as hidden Markov models and Kalman filters, and deep-learning approaches, such as the long short-term memory (LSTM) model, may be useful methods to estimate user skill level and predict appropriate task challenges. A possible advantage of these models over commonly used adaptive methods, such as staircases or blockwise adjustment methods that are based only upon recent performance, is that Bayesian filtering and deep learning approaches can model the trajectory of user performance across multiple sessions and incorporate data from multiple users to optimize local estimates. As a proof of concept, we fit data from two large cohorts of undergraduate students performing WM training using an N-back task. Results show that all three models predict appropriate challenges for different users. However, the hidden Markov models were most accurate in predicting participants' performances as a function of provided challenges, and thus, they placed participants at appropriate future challenges. These data provide good support for the potential of machine learning approaches as appropriate methods to personalize task performance to users in tasks that require adaptively determined challenges.

Divergent Research Methods Limit Understanding of Working Memory Training.

Working memory training has been a hot topic over the last decade. Although studies show benefits in trained and untrained tasks as a function of training, there is an ongoing debate on the efficacy of working memory training. There have been numerous meta-analyses put forth to the field, some finding overall broad transfer effects while others do not. However, discussion of this research typically overlooks specific qualities of the training and transfer tasks. As such, there has been next to no discussion in the literature on what training and transfer tasks features are likely to mediate training outcomes. To address this gap, here, we characterized the broad diversity of features employed in N-back training tasks and outcome measures in published working memory training studies. Extant meta-analyses have not taken into account the diversity of methodology at this level, primarily because there are too few studies using common methods to allow for a robust meta-analysis. We suggest that these limitations preclude strong conclusions from published data. In order to advance research on working memory training, and in particular, N-back training, more studies are needed that systematically compare training features and use common outcome measures to assess transfer effects.

rTMS evidence for a dissociation in short-term memory for spoken words and nonwords.

Differing patterns of verbal short-term memory (STM) impairment have provided unique insights into the relationship between STM and broader language function. Lexicality effects (i.e., better recall for words than nonwords) are larger in patients with phonological deficits following left temporoparietal lesions, and smaller in patients with semantic impairment and anterior temporal damage, supporting linguistic accounts of STM. However, interpretation of these patient dissociations are complicated by (i) non-focal damage and (ii) confounding factors and secondary impairments. This study addressed these issues by examining the impact of inhibitory transcranial magnetic stimulation (TMS) on auditory-verbal STM performance in healthy individuals. We compared the effects of TMS to left anterior supramarginal gyrus (SMG) and left anterior middle temporal gyrus (ATL) on STM for lists of nonwords and random words. SMG stimulation disrupted nonword recall, in a pattern analogous to that observed in patients, compatible with a role for this site in processing speech sounds without support from long-term lexical-semantic representations. Stimulation of ATL, a semantic site, disrupted the recall of words but not nonwords. A visual pattern memory task indicated that these effects of TMS were restricted to the verbal domain. These data provide convergent evidence for the conclusions of neuropsychological studies that support linguistic accounts of verbal STM.

Validation of a matrix reasoning task for mobile devices.

Many cognitive tasks have been adapted for tablet-based testing, but tests to assess nonverbal reasoning ability, as measured by matrix-type problems that are suited to repeated testing, have yet to be adapted for and validated on mobile platforms. Drawing on previous research, we developed the University of California Matrix Reasoning Task (UCMRT)-a short, user-friendly measure of abstract problem solving with three alternate forms that works on tablets and other mobile devices and that is targeted at a high-ability population frequently used in the literature (i.e., college students). To test the psychometric properties of UCMRT, a large sample of healthy young adults completed parallel forms of the test, and a subsample also completed Raven's Advanced Progressive Matrices and a math test; furthermore, we collected college records of academic ability and achievement. These data show that UCMRT is reliable and has adequate convergent and external validity. UCMRT is self-administrable, freely available for researchers, facilitates repeated testing of fluid intelligence, and resolves numerous limitations of existing matrix tests.

The Effects of Theta and Gamma tACS on Working Memory and Electrophysiology.

A single blind sham-controlled study was conducted to explore the effects of theta and gamma transcranial alternating current stimulation (tACS) on offline performance on working memory tasks. In order to systematically investigate how specific parameters of tACS affect working memory, we manipulated the frequency of stimulation (theta frequency vs. gamma frequency), the type of task (n-back vs. change detection task) and the content of the tasks (verbal vs. figural stimuli). A repeated measures design was used that consisted of three sessions: theta tACS, gamma tACS and sham tACS. In total, four experiments were conducted which differed only with respect to placement of tACS electrodes (bilateral frontal, bilateral parietal, left fronto-parietal and right-fronto parietal). Healthy female students (N = 72) were randomly assigned to one of these groups, hence we were able to assess the efficacy of theta and gamma tACS applied over different brain areas, contrasted against sham stimulation. The pre-post/sham resting electroencephalogram (EEG) analysis showed that theta tACS significantly affected theta amplitude, whereas gamma tACS had no significant effect on EEG amplitude in any of the frequency bands of interest. Gamma tACS did not significantly affect working memory performance compared to sham, and theta tACS led to inconsistent changes in performance on the n-back tasks. Active theta tACS significantly affected P3 amplitude and latency during performance on the n-back tasks in the bilateral parietal and right-fronto parietal protocols.

Making Brains run Faster: are they Becoming Smarter?

A brief overview of structural and functional brain characteristics related to g is presented in the light of major neurobiological theories of intelligence: Neural Efficiency, P-FIT and Multiple-Demand system. These theories provide a framework to discuss the main objective of the paper: what is the relationship between individual alpha frequency (IAF) and g? Three studies were conducted in order to investigate this relationship: two correlational studies and a third study in which we experimentally induced changes in IAF by means of transcranial alternating current stimulation (tACS). (1) In a large scale study (n = 417), no significant correlations between IAF and IQ were observed. However, in males IAF positively correlated with mental rotation and shape manipulation and with an attentional focus on detail. (2) The second study showed sex-specific correlations between IAF (obtained during task performance) and scope of attention in males and between IAF and reaction time in females. (3) In the third study, individuals' IAF was increased with tACS. The induced changes in IAF had a disrupting effect on male performance on Raven's matrices, whereas a mild positive effect was observed for females. Neuro-electric activity after verum tACS showed increased desynchronization in the upper alpha band and dissociation between fronto-parietal and right temporal brain areas during performance on Raven's matrices. The results are discussed in the light of gender differences in brain structure and activity.

EEG alpha frequency correlates of burnout and depression: The role of gender.

EEG alpha frequency band biomarkers of depression are widely explored. Due to their trait-like features, they may help distinguish between depressive and burnout symptomatology, which is often referred to as "work-related depression". The present correlational study strived to examine whether individual alpha frequency (IAF), power, and coherence in the alpha band can provide evidence for establishing burnout as a separate diagnostic entity. Resting EEG (eyes closed) was recorded in 117 individuals (42 males). In addition, the participants filled-out questionnaires of burnout and depression. Regression analyses highlighted the differential value of IAF and power in predicting burnout and depression. IAF was significantly related to depressive symptomatology, whereas power was linked mostly to burnout. Moreover, seven out of twelve interactions between EEG indicators and gender were significant. Connectivity patterns were significant for depression displaying gender-related differences. The results offer tentative support for establishing burnout as a separate clinical syndrome.

Making brains run faster: are they becoming smarter?

A brief overview of structural and functional brain characteristics related to g is presented in the light of major neurobiological theories of intelligence: Neural Efficiency, P-FIT and Multiple-Demand system. These theories provide a framework to discuss the main objective of the paper: what is the relationship between individual alpha frequency (IAF) and g? Three studies were conducted in order to investigate this relationship: two correlational studies and a third study in which we experimentally induced changes in IAF by means of transcranial alternating current stimulation (tACS). (1) In a large scale study (n = 417), no significant correlations between IAF and IQ were observed. However, in males IAF positively correlated with mental rotation and shape manipulation and with an attentional focus on detail. (2) The second study showed sex-specific correlations between IAF (obtained during task performance) and scope of attention in males and between IAF and reaction time in females. (3) In the third study, individuals’ IAF was increased with tACS. The induced changes in IAF had a disrupting effect on male performance on Raven’s matrices, whereas a mild positive effect was observed for females. Neuro-electric activity after verum tACS showed increased desynchronization in the upper alpha band and dissociation between fronto-parietal and right temporal brain areas during performance on Raven’s matrices. The results are discussed in the light of gender differences in brain structure and activity (AU)

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The effects of theta transcranial alternating current stimulation (tACS) on fluid intelligence.

The objective of the study was to explore the influence of transcranial alternating current stimulation (tACS) on resting brain activity and on measures of fluid intelligence. Theta tACS was applied to the left parietal and left frontal brain areas of healthy participants after which resting electroencephalogram (EEG) data was recorded. Following sham/active stimulation, the participants solved two tests of fluid intelligence while their EEG was recorded. The results showed that active theta tACS affected spectral power in theta and alpha frequency bands. In addition, active theta tACS improved performance on tests of fluid intelligence. This influence was more pronounced in the group of participants that received stimulation to the left parietal area than in the group of participants that received stimulation to the left frontal area. Left parietal tACS increased performance on the difficult test items of both tests (RAPM and PF&C) whereas left frontal tACS increased performance only on the easy test items of one test (RAPM). The observed behavioral tACS influences were also accompanied by changes in neuroelectric activity. The behavioral and neuroelectric data tentatively support the P-FIT neurobiological model of intelligence.

The influence of theta transcranial alternating current stimulation (tACS) on working memory storage and processing functions.

The study aimed to explore the role of the fronto-parietal brain network in working memory function--in temporary storage and manipulation of information. In a single blind sham controlled experiment 36 respondents solved different working memory tasks after theta transcranial alternating current stimulation (tACS) was applied to left frontal, left parietal and right parietal areas. Both verum tACS protocols stimulating parietal brain areas (target electrodes positioned at location P3, or P4) had a positive effect on WM storage capacity as compared with sham tACS, whereas no such influence was observed for the stimulation of the left frontal area (target electrode positioned at location F3). A second finding was that left parietal theta tACS had a more pronounced influence on backward recall than on forward recall, which was not related to task content (spatial or verbal). The influence of theta tACS on WM executive processes was most pronounced for right parietal stimulation. The results are discussed in the broad theoretical framework of the multicomponent model of working memory.