Evidence of stable individual differences in implicit learning

Stability of individual differences in implicitly guided attention

Daily activities often occur in familiar environments, affording us an opportunity to learn. Laboratory studies have shown that people readily acquire an implicit spatial preference for locations that frequently contained a search target in the past. These studies, however, have focused on group characteristics, downplaying the significance of individual differences. In a pre-registered study, we examined the stability of individual differences in two variants of an implicit location probability learning (LPL) task. We tested the possibility that individual differences were stable in variants that shared the same search process, but not in variants involving different search processes. In Experiment 1, participants performed alternating blocks of T-among-Ls and 5-among-2s search tasks. Unbeknownst to them, the search target appeared disproportionately often in one region of space; the high-probability regions differed between the two tasks. LPL transferred between the two tasks. In addition, individuals who showed greater LPL in the T-task also did so in the 5-task and vice versa. In Experiment 2, participants searched for either a camouflaged-T against background noise or a well-segmented T among well-segmented Ls. These two tasks produced task-specific learning that did not transfer between tasks. Moreover, individual differences in learning did not correlate between tasks. Thus, LPL is associated with stable individual differences across variants, but only when the variants share common search processes.

Unraveling the complex interplay between statistical learning and working memory in Chinese children with and without dyslexia across different ages

The relation between statistical learning and working memory in children with developmental dyslexia (DD) remains unclear. This study employed a distributional and a conditional statistical learning experiment and a working memory task to examine this relation in 651 Chinese 6- to 12-year-olds with and without DD (NDD = 199, 101 females; NwoDD = 452, 227 females; participated 2014-2019). Results showed working memory positively associated with recognizing high-predictable and familiar items in both groups, but negatively associated with recognizing unfamiliar items in the DD group only. These findings uncovered the complex interplay between statistical learning and working memory, demonstrating how different working memory abilities in children with and without DD relate to various statistical learning mechanisms at the item level.

One Size Does Not Fit All: Idiographic Computational Models Reveal Individual Differences in Learning and Meta-Learning Strategies

Complex skill learning depends on the joint contribution of multiple interacting systems: working memory (WM), declarative long-term memory (LTM) and reinforcement learning (RL). The present study aims to understand individual differences in the relative contributions of these systems during learning. We built four idiographic, ACT-R models of performance on the stimulus-response learning, Reinforcement Learning Working Memory task. The task consisted of short 3-image, and long 6-image, feedback-based learning blocks. A no-feedback test phase was administered after learning, with an interfering task inserted between learning and test. Our four models included two single-mechanism RL and LTM models, and two integrated RL-LTM models: (a) RL-based meta-learning, which selects RL or LTM to learn based on recent success, and (b) a parameterized RL-LTM selection model at fixed proportions independent of learning success. Each model was the best fit for some proportion of our learners (LTM: 68.7%, RL: 4.8%, Meta-RL: 13.25%, bias-RL:13.25% of participants), suggesting fundamental differences in the way individuals deploy basic learning mechanisms, even for a simple stimulus-response task. Finally, long-term declarative memory seems to be the preferred learning strategy for this task regardless of block length (3- vs 6-image blocks), as determined by the large number of subjects whose learning characteristics were best captured by the LTM only model, and a preference for LTM over RL in both of our integrated-models, owing to the strength of our idiographic approach.

Autistic Adults Show Intact Learning on a Visuospatial Serial Reaction Time Task

Some theories have proposed that autistic individuals have difficulty learning predictive relationships. We tested this hypothesis using a serial reaction time task in which participants learned to predict the locations of a repeating sequence of target locations. We conducted a large-sample online study with 61 autistic and 71 neurotypical adults. The autistic group had slower overall reaction times, but demonstrated sequence-specific learning equivalent to the neurotypical group, consistent with other findings of typical procedural memory in autism. The neurotypical group, however, made significantly more prediction-related errors early in the experiment when the stimuli changed from repeated sequences to random locations, suggesting certain limited behavioural differences in the learning or utilization of predictive relationships for autistic adults.

Reliability of the serial reaction time task: If at first you don't succeed, try, try, try again

Procedural memory is involved in the acquisition and control of skills and habits that underlie rule and procedural learning, including the acquisition of grammar and phonology. The serial reaction time task (SRTT), commonly used to assess procedural learning, has been shown to have poor stability (test-retest reliability). We investigated factors that may affect the stability of the SRTT in adults. Experiment 1 examined whether the similarity of sequences learned in two sessions would impact stability: test-retest correlations were low regardless of sequence similarity (r < .31). Experiment 2 added a third session to examine whether individual differences in learning would stabilise with further training. There was a small (but nonsignificant) improvement in stability for later sessions (Sessions 1 and 2: r = .42; Sessions 2 and 3: r = .60). Stability of procedural learning on the SRTT remained suboptimal in all conditions, posing a serious obstacle to the use of this task as a sensitive predictor of individual differences and ultimately theoretical advance.

Effects of Cognitive Orientation to Daily Occupational Performance and Conductive Education Treatment Approaches on Fine Motor Skills, Activity and Participation Limitations in Children with Down Syndrome: A Randomised Controlled Trial

This study aiming to compare the effectiveness of Cognitive Orientation to Daily Occupational Performance (CO-OP) and Conductive Education (CE) approaches on motor skills, activity limitation and participation restrictions in children with Down Syndrome (DS). Twelwe children were randomly assigned into two groups. Twelve-week CO-OP or CE intervention (period-1) followed by a 12-week washout period. Same interventions were crossed over for another 12 weeks (period-2). The Performance Quality Rating Scale (PQRS), Canadian Occupational Performance Measure (COPM) and the Bruininks Oseretsky Test of Motor Proficiency Second Edition-Brief Form (BOT2-BF) were used for outcome measurements. CO-OP was effective in the improvement of task-specific activity performance, while both approaches have similar effects on the improvement of perceived performance, satisfaction, and motor skills performance.

The Visual Advantage Effect in Comparing Uni-Modal and Cross-Modal Probabilistic Category Learning

People rely on multiple learning systems to complete weather prediction (WP) tasks with visual cues. However, how people perform in audio and audiovisual modalities remains elusive. The present research investigated how the cue modality influences performance in probabilistic category learning and conscious awareness about the category knowledge acquired. A modified weather prediction task was adopted, in which the cues included two dimensions from visual, auditory, or audiovisual modalities. The results of all three experiments revealed better performances in the visual modality relative to the audio and audiovisual modalities. Moreover, participants primarily acquired unconscious knowledge in the audio and audiovisual modalities, while conscious knowledge was acquired in the visual modality. Interestingly, factors such as the amount of training, the complexity of visual stimuli, and the number of objects to which the two cues belonged influenced the amount of conscious knowledge acquired but did not change the visual advantage effect. These findings suggest that individuals can learn probabilistic cues and category associations across different modalities, but a robust visual advantage persists. Specifically, visual associations can be learned more effectively, and are more likely to become conscious. The possible causes and implications of these effects are discussed.

Implicit Statistical Learning in L2 Sentence Processing: Individual Cognitive Differences

This study investigates whether statistical learning ability, conceptualized as a cognitive ability to learn regularities implicitly, is a good predictor for L2 learners' online language processing performance. Native-English-speaking adults, as a control group, and native-Korean-speaking adult L2 learners of English participated. They completed: (a) an artificial grammar learning task containing nonadjacent dependencies in sequences of non-words, to test statistical learning ability; and (b) a self-paced English reading task containing relative clauses (RC) in which the "filler" and the "gap" formed a long-distance dependency, to test language processing. Both tasks' stimuli were presented element-by-element to mimic the incremental nature of online language processing. The results for the L1 group show that higher accuracy scores on the artificial grammar learning task did not predict higher sentence comprehension scores. The results for the L2 group, however, show a marginally significant correlation between accuracy scores on the artificial grammar learning task and sentence comprehension scores. For both groups, the reading time difference between grammatical and ungrammatical items in the artificial grammar learning task did predict the speed of reading times for items with RCs with a long-distance dependency in the sentence processing task: Larger differences in RTs in the artificial grammar task correlated with slower reading at the critical region of English RCs. These findings suggest a similar mechanism for online first and second language processing of core syntactic phenomena and for statistical learning ability that involves implicitly tracking distributional relations across elements.

Resting state electroencephalography power correlates with individual differences in implicit sequence learning

Neuroimaging resting state paradigms have revealed synchronised oscillatory activity is present even in the absence of completing a task or mental operation. One function of this neural activity is likely to optimise the brain's sensitivity to forthcoming information that, in turn, likely promotes subsequent learning and memory outcomes. The current study investigated whether this extends to implicit forms of learning. A total of 85 healthy adults participated in the study. Resting state electroencephalography was first acquired from participants before they completed a serial reaction time task. On this task, participants implicitly learnt a visuospatial-motor sequence. Permutation testing revealed a negative correlation between implicit sequence learning and resting state power in the upper theta band (6-7 Hz). That is, lower levels of resting state power in this frequency range were associated with superior levels of implicit sequence learning. This association was observed at midline-frontal, right-frontal and left-posterior electrodes. Oscillatory activity in the upper theta band supports a range of top-down processes including attention, inhibitory control and working memory, perhaps just for visuospatial information. Our results may be indicating that disengaging theta-supported top-down attentional processes improves implicit learning of visuospatial-motor information that is embedded in sensory input. This may occur because the brain's sensitivity to this type of information is optimally achieved when learning is driven by bottom-up processes. Moreover, the results of this study further demonstrate that resting state synchronised brain activity influences subsequent learning and memory.

The reliability of the serial reaction time task: meta-analysis of test-retest correlations

The Serial Reaction Time task, one of the most widely used tasks to index procedural memory, has been increasingly employed in individual differences research examining the role of procedural memory in language and other cognitive abilities. Yet, despite consistently producing robust procedural learning effects at the group level (i.e. faster responses to sequenced/probable trials versus random/improbable trials), these effects have recently been found to have poor reliability. In this meta-analysis (N = 7), comprising 719 participants (M = 20.81, s.d. = 7.13), we confirm this 'reliability paradox'. The overall retest reliability of the robust procedural learning effect elicited by the SRTT was found to be well below acceptable psychometric standards (r < 0.40). However, split-half reliability within a session is better, with an overall estimate of 0.66. There were no significant effects of sampling (participants' age), methodology (e.g. number of trials, sequence type) and analytical decisions (whether all trials were included when computing the procedural learning scores; using different indexes of procedural learning). Thus, despite producing robust effects at the group-level, until we have a better understanding of the factors that improve the reliability of this task using the SRTT for individual differences research should be done with caution.

What sticks after statistical learning: The persistence of implicit versus explicit memory traces

Statistical learning is a powerful mechanism that extracts even subtle regularities from our information-dense worlds. Recent theories argue that statistical learning can occur through multiple mechanisms-both the conventionally assumed automatic process that precipitates unconscious learning, and an attention-dependent process that brings regularities into conscious awareness. While this view has gained popularity, there are few empirical dissociations of the hypothesized implicit and explicit forms of statistical learning. Here we provide strong evidence for this dissociation in two ways. First, we show in healthy adults (N = 60) that implicit and explicit traces have divergent consolidation trajectories, with implicit knowledge of structure strengthened over a 24-h period, while precise explicit representations tend to decay. Second, we demonstrate that repeated testing strengthens the retention of explicit representations but that implicit statistical learning is uninfluenced by testing. Together these dissociations provide much needed support for the reconceptualization of statistical learning as a multi-component construct.

Pay attention and you might miss it: Greater learning during attentional lapses

Attentional lapses have been found to impair everything from basic perception to learning and memory. Yet, despite the well-documented costs of lapses on cognition, recent work suggests that lapses might unexpectedly confer some benefits. One potential benefit is that lapses broaden our learning to integrate seemingly irrelevant content that could later prove useful-a benefit that prior research focusing only on goal-relevant memory would miss. Here, we measure how fluctuations in sustained attention influence the learning of seemingly goal-irrelevant content that competes for attention with target content. Participants completed a correlated flanker task in which they categorized central targets (letters or numbers) while ignoring peripheral flanking symbols that shared hidden probabilistic relationships with the targets. We found that across participants, higher rates of attentional lapses correlated with greater learning of the target-flanker relationships. Moreover, within participants, learning was more evident during attentional lapses. These findings address long-standing theoretical debates and reveal a benefit of attentional lapses: they expand the scope of learning and decisions beyond the strictly relevant.

Selecting for Learning Potential: Is Implicit Learning the New Cognitive Ability?

For decades, the field of workplace selection has been dominated by evidence that cognitive ability is the most important factor in predicting performance. Meta-analyses detailing the contributions of a wide-range of factors to workplace performance show that cognitive ability’s contribution is partly mediated by the learning of task-relevant skills and job-specific declarative knowledge. Further, there is evidence to suggest that this relationship is a function of task complexity, and partially mediated by learning performance in workplace induction and training activities. Simultaneously, evidence is mounting that stable individual differences in implicit learning exist, which are at least partially independent of traditional measures of intelligence. In this article we provide an overview of recent advances in our understanding of implicit learning, outline some of the advantages offered by its measurement, and highlight some of the challenges associated with its adoption as a measure of interest.

Overnight changes to dual-memory processes reflected in speech-perceptual performance

Adults' ability to attain and retain nonnative speech sound categories vary substantially among individuals. While we know that speech-perceptual skills play a role, we know less about how consolidation-related changes in acoustic-phonetic memory contribute to perceptual tasks. The goal of this investigation was to examine contributions of memory and perceptual skills to the perceptual performance on a trained nonnative speech contrast over two days. Twenty-one adult participants (ages 18-24) completed four different experiments. Three of these assessed learning and memory: visual statistical learning (implicit), visual object recognition (explicit), and nonnative (Hindi dental-retroflex) speech-sound training. Participants completed the learning tasks around 8 p.m., and performance was measured shortly after learning and again 12 hours later. On a separate day, participants completed a categorical perception task on a native (/a/-/e/) vowel continuum. Nonnative speech perception was associated with implicit learning performance when both were assessed shortly after learning, and associated with the retention of explicit memory when both were assessed after an overnight delay. Native speech-sounds were at least marginally associated with nonnative speech perception performance on both days, but with a stronger association observed with performance assessed on Day 2. These findings provide preliminary support for the interpretation that speech-sounds are encoded by at least two memory systems in parallel, but that perceptual performance may reflect acoustic-phonetic knowledge learned by different memory systems over time since exposure. Moreover, performance on speech perception tasks in both native and nonnative speech-sounds may rely on similar retrieval mechanisms for long-term storage of speech-sound information.

Dynamic development of intuitions and explicit knowledge during implicit learning

Implicit learning refers to learning without conscious awareness of the content acquired. Theoretical frameworks of human cognition suggest that intuitions develop based on incomplete perceptions of regularity during implicit learning and, in turn, lead to the development of more explicit, consciously-accessible knowledge. Surprisingly, however, this putative information processing pathway (i.e., implicit learning ➔ intuition ➔ explicit knowledge) has yet to be empirically demonstrated. The present study investigated the relationship between implicit learning, intuitions, and explicit knowledge using a modified Serial Reaction Time Task. Results indicate that intuitions of implicitly-learned patterns emerge prior to the development of explicit knowledge. Moreover, intuition timing and accuracy were significantly associated with accuracy of explicit reports. We did not, however, find that stronger implicit learners developed more accurate intuitions. Our findings suggest a crucial role of intuition in the formation of explicit knowledge from implicit learning.

The Challenge of Inferring Unconscious Mental Processes

Studies of unconscious mental processes often compare a performance measure (e.g., some assessment of perception or memory) with a measure of awareness (e.g., a verbal report or forced-choice response) of the critical cue or contingency taken either concurrently or separately. The resulting patterns of bivariate data across participants lend themselves to several analytic approaches for inferring the existence of unconscious mental processes, but it is rare for researchers to consider the underlying generative processes that might cause these patterns. We show that bivariate data are generally insufficient to discriminate single-process models, with a unitary latent process determining both performance and awareness, from dual-process models, comprising distinct latent processes for performance and awareness. Future research attempting to isolate and investigate unconscious processes will need to employ richer types of data and analyses.

Cross-modal auditory priors drive the perception of bistable visual stimuli with reliable differences between individuals

It is a widely held assumption that the brain performs perceptual inference by combining sensory information with prior expectations, weighted by their uncertainty. A distinction can be made between higher- and lower-level priors, which can be manipulated with associative learning and sensory priming, respectively. Here, we simultaneously investigate priming and the differential effect of auditory vs. visual associative cues on visual perception, and we also examine the reliability of individual differences. Healthy individuals (N = 29) performed a perceptual inference task twice with a one-week delay. They reported the perceived direction of motion of dot pairs, which were preceded by a probabilistic visuo-acoustic cue. In 30% of the trials, motion direction was ambiguous, and in half of these trials, the auditory versus the visual cue predicted opposing directions. Cue-stimulus contingency could change every 40 trials. On ambiguous trials where the visual and the auditory cue predicted conflicting directions of motion, participants made more decisions consistent with the prediction of the acoustic cue. Increased predictive processing under stimulus uncertainty was indicated by slower responses to ambiguous (vs. non-ambiguous) stimuli. Furthermore, priming effects were also observed in that perception of ambiguous stimuli was influenced by perceptual decisions on the previous ambiguous and unambiguous trials as well. Critically, behavioural effects had substantial inter-individual variability which showed high test-retest reliability (intraclass correlation coefficient (ICC) > 0.78). Overall, higher-level priors based on auditory (vs. visual) information had greater influence on visual perception, and lower-level priors were also in action. Importantly, we observed large and stable differences in various aspects of task performance. Computational modelling combined with neuroimaging could allow testing hypotheses regarding the potential mechanisms causing these behavioral effects. The reliability of the behavioural differences implicates that such perceptual inference tasks could be valuable tools during large-scale biomarker and neuroimaging studies.

The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again

Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both "Cartesian theaters" and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals).

Raising awareness about measurement error in research on unconscious mental processes

Experimental psychologists often neglect the poor psychometric properties of the dependent measures collected in their studies. In particular, a low reliability of measures can have dramatic consequences for the interpretation of key findings in some of the most popular experimental paradigms, especially when strong inferences are drawn from the absence of statistically significant correlations. In research on unconscious cognition, for instance, it is commonly argued that the lack of a correlation between task performance and measures of awareness or explicit recollection of the target stimuli provides strong support for the conclusion that the cognitive processes underlying performance must be unconscious. Using contextual cuing of visual search as a case study, we show that given the low reliability of the dependent measures collected in these studies, it is usually impossible to draw any firm conclusion about the unconscious character of this effect from correlational analyses. Furthermore, both a psychometric meta-analysis of the available evidence and a cognitive-modeling approach suggest that, in fact, we should expect to see very low correlations between performance and awareness at the empirical level, even if both constructs are perfectly related at the latent level. Convincing evidence for the unconscious character of contextual cuing and other effects will most likely demand richer and larger data sets, coupled with more powerful analytic approaches.

Correlation analysis to investigate unconscious mental processes: A critical appraisal and mini-tutorial

As a method to investigate the scope of unconscious mental processes, researchers frequently obtain concurrent measures of task performance and stimulus awareness across participants. Even though both measures might be significantly greater than zero, the correlation between them might not, encouraging the inference that an unconscious process drives task performance. We highlight the pitfalls of this null-correlation approach and provide a mini-tutorial on ways to avoid them. As reference, we use a recent study by Salvador et al. (2018) reporting a non-significant correlation between the extent to which memory was suppressed by a Think/No-Think cue and an index of cue awareness. In the Null Hypothesis Significance Testing (NHST) framework, it is inappropriate to interpret failure to reject the null hypothesis (i.e., correlation = 0) as evidence for the null. Furthermore, psychological measures are often unreliable, which can dramatically attenuate the size of observed correlations. A Bayesian approach can circumvent both problems and compare the extent to which the data provide evidence for the null versus the alternative hypothesis (i.e., correlation > 0), while considering the usually low reliabilities of the variables. Applied to Salvador et al.'s data, this approach indicates no to moderate support for the claimed unconscious nature of participants' memory-suppression performance-depending on the model of the alternative hypothesis. Hence, more reliable data are needed. When analyzing correlational data, we recommend researchers to employ the Bayesian methods developed here (and made freely available as R scripts), rather than standard NHST methods, to take account of unreliability.

A Study on Human Learning Ability during Classification of Motion and Colour Visual Cues and Their Combination

The paper presents a study on the human learning process during the classification of stimuli, defined by motion and color visual cues and their combination. Because the classification dimension and the features that define each category are uncertain, we model the learning curves using Bayesian inference and more precisely the Normalized Conjunctive Consensus rule, and also on the base of the more efficient probabilistic Proportional Conflict Redistribution rule No 5 (pPCR5) defined within Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. Our goal is to study how these rules succeed to model consistently both: human individual and group behaviour during the learning of the associations between the stimuli and the responses in categorization tasks varying by the amount of relevant stimulus information. The effect of age on this process is also evaluated.

Implicit pattern learning predicts individual differences in belief in God in the United States and Afghanistan

Most humans believe in a god, but many do not. Differences in belief have profound societal impacts. Anthropological accounts implicate bottom-up perceptual processes in shaping religious belief, suggesting that individual differences in these processes may help explain variation in belief. Here, in findings replicated across socio-religiously disparate samples studied in the U.S. and Afghanistan, implicit learning of patterns/order within visuospatial sequences (IL-pat) in a strongly bottom-up paradigm predict 1) stronger belief in an intervening/ordering god, and 2) increased strength-of-belief from childhood to adulthood, controlling for explicit learning and parental belief. Consistent with research implicating IL-pat as a basis of intuition, and intuition as a basis of belief, mediation models support a hypothesized effect pathway whereby IL-pat leads to intuitions of order which, in turn, lead to belief in ordering gods. The universality and variability of human IL-pat may thus contribute to the global presence and variability of religious belief.

A positive influence of basal ganglia iron concentration on implicit sequence learning

Iron homeostasis is important for maintaining normal physiological brain functioning. In two independent samples, we investigate the link between iron concentration in the basal ganglia (BG) and implicit sequence learning (ISL). In Study 1, we used quantitative susceptibility mapping and task-related fMRI to examine associations among regional iron concentration measurements, brain activation, and ISL in younger and older adults. In Study 2, we examined the link between brain iron and ISL using a metric derived from fMRI in an age-homogenous sample of older adults. Three main findings were obtained. First, BG iron concentration was positively related to ISL in both studies. Second, ISL was robust for both younger and older adults, and performance-related activation was found in fronto-striatal regions across both age groups. Third, BG iron was positively linked to task-related BOLD signal in fronto-striatal regions. This is the first study investigating the relationship among brain iron accumulation, functional brain activation, and ISL, and the results suggest that higher brain iron concentration may be linked to better neurocognitive functioning in this particular task.