Intuition: a social cognitive neuroscience approach

Procedural learning is associated with microstructure of basal ganglia-cerebellar circuitry in children

In adults, individual differences in procedural learning (PL) are associated with white matter organization within the basal ganglia-cerebellar circuit. However, no research has examined whether this circuitry is related to individual differences in PL during childhood. Here, 28 children (Mage = 10.00 ± 2.31, 10 female) completed the serial reaction time (SRT) task to measure PL, and underwent structural magnetic resonance imaging (MRI). Fixel-Based Analysis was performed to extract specific measures of white matter fiber density (FD) and fiber cross-section (FC) from the superior cerebellar peduncles (SCP) and the striatal premotor tracts (STPMT), which underlie the fronto-basal ganglia-cerebellar system. These fixel metrics were correlated with the 'rebound effect' from the SRT task - a measure of PL proficiency which compares reaction times associated with generating a sequence, to random trials. While no significant associations were observed at the fixel level, a significant positive association was observed between average FD in the right SCP and the rebound effect, with a similar trend observed in the left SCP. No significant effects were detected in the STPMT. Our results indicate that, like in adults, microstructure of the basal ganglia-cerebellar circuit may explain individual differences in childhood PL.

More than meets the gut: a prototype analysis of the lay conceptions of intuition and analysis

Using a prototype approach, we assessed people's lay conceptions of intuition and analysis. Open-ended descriptions of intuition and analysis were generated by participants (Study 1) and resulting exemplars were sorted into features subsequently rated in centrality by independent participants (Study 2). Feature centrality was validated by showing that participants were quicker and more accurate in classifying central (as compared to peripheral) features (Study 3). Centrality ratings suggested a single-factor structure describing analysis but revealed that participants held lay conceptions of intuition as involving two different types of processes: (1) as an automatic, affective, and non-logical processing, and (2) as a holistic processing that can assist in problem-solving. Additional analyses showed that the centrality ratings of intuition's facets were predicted by participants' self-reported intuitive style, suggesting intuition is differently perceived by intuitive and non-intuitive people. We discuss the implications of these results for the study of intuition and analysis.

Atypical procedural learning in children with developmental coordination disorder: A combined behavioral and neuroimaging study

While procedural learning (PL) has been implicated in delayed motor skill observed in developmental coordination disorder (DCD), few studies have considered the impact of co-occurring attentional problems. Furthermore, the neurostructural basis of PL in children remains unclear. We investigated PL in children with DCD while controlling for inattention symptoms, and examined the role of fronto-basal ganglia-cerebellar morphology in PL. Fifty-nine children (6-14 years; nDCD = 19, ncontrol = 40) completed the serial reaction time (SRT) task to measure PL. The Attention-Deficit Hyperactivity Disorder Rating Scale-IV was administered to measure inattention symptoms. Structural T1 images were acquired for a subset of participants (nDCD = 10, ncontrol = 28), and processed using FreeSurfer. Volume was extracted for the cerebellum, basal ganglia, and frontal regions. After controlling for inattention symptoms, the reaction time profile of controls was consistent with learning on the SRT task. This was not the case for those with DCD. SRT task performance was positively correlated with cerebellar cortical volume, and children with DCD trended towards lower cerebellar volume compared to controls. Children with DCD may not engage in PL during the SRT task in the same manner as controls, with this differential performance being associated with atypical cerebellar morphology.

The combination of accent method and phonemic contrast: an innovative strategy to improve speech production on post-stroke dysarthria

Introduction

Speech production includes segmental and suprasegmental features, which interact and cooperate with each other. Impaired speech production is common in individuals with post-stroke dysarthria. The commonly used phonemic contrast therapy and Accent Method in clinical practice can improve the segmental and suprasegmental aspects, respectively. This study aimed to explore the feasibility and immediate effectiveness of the combination of specific rhythm patterns of the Accent Method and phonemic contrast on speech production.

Methods

Fifteen poststroke dysarthria patients (12 males and three females) first received accentuation task of three rhythm patterns (Largo-slow, Andante-medium, Allegro-fast) and later received speech task in appropriate rhythm patterns combined with phonemic contrast materials and non-phonemic contrast materials. Speech parameters were analyzed by considering speech clarity and prosody.

Results

The results showed that the number of correct target syllables, sentence clarity, and standard deviation of intensity increased significantly, and the average length of pauses and abnormal pause times decreased significantly in Andante (medium) compared to other rhythms. The number of correct target syllables, sentence clarity, and standard deviation of intensity increased significantly compared with those in the non-phonemic contrast in Andante (medium).

Conclusion

The combination of phonemic contrast and Accent Method was verified to have an immediate effect on speech production in Mandarin speakers with post-stroke dysarthria and could be further validated in other diseases with impaired speech production in the clinic in the future.

Modulating Visuomotor Sequence Learning by Repetitive Transcranial Magnetic Stimulation: What Do We Know So Far?

Predictive processes and numerous cognitive, motor, and social skills depend heavily on sequence learning. The visuomotor Serial Reaction Time Task (SRTT) can measure this fundamental cognitive process. To comprehend the neural underpinnings of the SRTT, non-invasive brain stimulation stands out as one of the most effective methodologies. Nevertheless, a systematic list of considerations for the design of such interventional studies is currently lacking. To address this gap, this review aimed to investigate whether repetitive transcranial magnetic stimulation (rTMS) is a viable method of modulating visuomotor sequence learning and to identify the factors that mediate its efficacy. We systematically analyzed the eligible records (n = 17) that attempted to modulate the performance of the SRTT with rTMS. The purpose of the analysis was to determine how the following factors affected SRTT performance: (1) stimulated brain regions, (2) rTMS protocols, (3) stimulated hemisphere, (4) timing of the stimulation, (5) SRTT sequence properties, and (6) other methodological features. The primary motor cortex (M1) and the dorsolateral prefrontal cortex (DLPFC) were found to be the most promising stimulation targets. Low-frequency protocols over M1 usually weaken performance, but the results are less consistent for the DLPFC. This review provides a comprehensive discussion about the behavioral effects of six factors that are crucial in designing future studies to modulate sequence learning with rTMS. Future studies may preferentially and synergistically combine functional neuroimaging with rTMS to adequately link the rTMS-induced network effects with behavioral findings, which are crucial to develop a unified cognitive model of visuomotor sequence learning.

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.

Intact predictive processing in autistic adults: evidence from statistical learning

Impairment in predictive processes gained a lot of attention in recent years as an explanation for autistic symptoms. However, empirical evidence does not always underpin this framework. Thus, it is unclear what aspects of predictive processing are affected in autism spectrum disorder. In this study, we tested autistic adults on a task in which participants acquire probability-based regularities (that is, a statistical learning task). Twenty neurotypical and 22 autistic adults learned a probabilistic, temporally distributed regularity for about 40 min. Using frequentist and Bayesian methods, we found that autistic adults performed comparably to neurotypical adults, and the dynamics of learning did not differ between groups either. Thus, our study provides evidence for intact statistical learning in autistic adults. Furthermore, we discuss potential ways this result can extend the scope of the predictive processing framework, noting that atypical processing might not always mean a deficit in performance.

Implicit and explicit learning of socio-emotional information in a dynamic interaction with a virtual avatar

Implicit learning (IL) deals with the non-conscious acquisition of structural regularities from the environment. IL is often deemed essential for acquiring regularities followed by social stimuli (e.g., other persons' behavior), hence is hypothesized to play a role in typical social functioning. However, our understanding of how this process might operate in social contexts is limited for two main reasons. First, while IL is highly sensitive to the characteristics of the surface stimuli upon which it operates, most IL studies have used surface stimuli with limited social validity (e.g., letters, symbols, etc.). Second, while the social environment is dynamic (i.e., our behaviors and reactions influence those of our social partners and vice-versa), the bulk of IL research employed noninteractive paradigms. Using a novel task, we examine whether IL is involved in the acquisition of regularities from a dynamic interaction with a realistic real-life-like agent. Participants (N = 115) interacted with a cinematic avatar that displayed different facial expressions. Their task was to regulate the avatar's expression to a specified level. Unbeknownst to them, an equation mediated the relationship between their responses and the avatar's expressions. Learning occurred in the task, as participants gradually increased their ability to bring the avatar in the target state. Subjective measures of awareness revealed that participants acquired both implicit and explicit knowledge from the task. This is the first study to show that IL operates in interactive situations upon socially relevant surface stimuli, facilitating future investigations of the role that IL plays in (a)typical social functioning.

An overview of machine learning methods in enabling IoMT-based epileptic seizure detection

The healthcare industry is rapidly automating, in large part because of the Internet of Things (IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of Medical Things (IoMT). Data collecting and processing are the fundamental components of all IoMT applications. Machine learning (ML) algorithms must be included into IoMT immediately due to the vast quantity of data involved in healthcare and the value that precise forecasts have. In today's world, together, IoMT, cloud services, and ML techniques have become effective tools for solving many problems in the healthcare sector, such as epileptic seizure monitoring and detection. One of the biggest hazards to people's lives is epilepsy, a lethal neurological condition that has become a global issue. To prevent the deaths of thousands of epileptic patients each year, there is a critical necessity for an effective method for detecting epileptic seizures at their earliest stage. Numerous medical procedures, including epileptic monitoring, diagnosis, and other procedures, may be carried out remotely with the use of IoMT, which will reduce healthcare expenses and improve services. This article seeks to act as both a collection and a review of the different cutting-edge ML applications for epilepsy detection that are presently being combined with IoMT.

Meaning in life through work: A cognitive-experiential self-theory (CEST) perspective

This article explores existential meaning-making from work using the cognitive-experiential self-theory (CEST). To start with, we use the tenets of CEST to elaborate on how the cues from archetype work environments—a realization facilitating work environment (RfWE) and justification facilitating work environment (JfWE)—are interpreted by information-processing systems to imbue meaning in life (MiL) as internal or external manifestations of coherence, purpose, and significance. Next, we explain how individual differences in work centrality and proactive meaning-crafting ability moderate the impact of JfWE, but not of RfWE, on MiL. Finally, we create a nomological network of existential meaning states emerging from the simultaneous presence or absence of RfWE and JfWE. In summary, by applying the information-processing lens of CEST, we develop an integrated model that explains how work drives MiL, elucidates the resultant existential states, and assesses the role of individual differences in meaning-making.

Plain Language Summary

This article develops an integrated model that outlines how work environments can augur human well-being by fostering a sense of meaning in life (MiL). Based on the cognitive-experiential self-theory (CEST), expounding parallel-competitive processing of information through the working of the experiential and rational system, we explore how the cues from archetype work environments—a realization facilitating work environment (RfWE) and justification facilitating work environment (JfWE)—influence the varied flavors of MiL and meaninglessness in life. We build the argument that RfWE activates the functioning of the experiential system to induce a feeling of internal MiL as internal coherence, internal purpose, and internal value significance. At the same time, JfWE triggers the functioning of the rational system to construct a judgment of external MiL as external coherence, external worthy purpose, and external value significance. However, the interaction between RfWE and JfWE can result in intricate scenarios, including favorable states such as holistic meaning, positive existential feelings, and positive existential narratives. Still, it can also lead individuals into meaninglessness in life through existential fatigue, existential cocoon, or existential futility. Nonetheless, individual differences in work centrality and proactive behavior to craft meaning can act as moderators to alter the intensity of work’s impact on MiL in a JfWE but not in an RfWE.

Implicit learning of regularities followed by realistic body movements in virtual reality

The existence of implicit (unconscious) learning has been demonstrated in several laboratory paradigms. Researchers have also suggested that it plays a role in complex real-life human activities. For instance, in social situations, we may follow unconscious behaviour scripts or intuitively anticipate the reaction of familiar persons based on nonconscious cues. Still, it is difficult to make inferences about the involvement of implicit learning in realistic contexts, given that this phenomenon has been demonstrated, almost exclusively, using simple artificial stimuli (e.g., learning structured patterns of letters). In addition, recent analyses show that the amount of unconscious knowledge learned in these tasks has been overestimated by random measurement error. To overcome these limitations, we adapted the artificial grammar learning (AGL) task, and exposed participants (N = 93), in virtual reality, to a realistic agent that executed combinations of boxing punches. Unknown to participants, the combinations were structured by a complex artificial grammar. In a subsequent test phase, participants accurately discriminated novel grammatical from nongrammatical combinations, showing they had acquired the grammar. For measuring awareness, we used trial-by-trial subjective scales, and an analytical method that accounts for the possible overestimation of unconscious knowledge due to regression to the mean. These methods conjointly showed strong evidence for implicit and for explicit learning. The present study is the first to show that humans can implicitly learn, in VR, knowledge regarding realistic body movements, and, further, that implicit knowledge extracted in AGL is robust when accounting for its possible inflation by random measurement error.

White matter microstructural correlates of associative learning in the oldest-old

The ability to learn associations between events is critical for everyday functioning (e.g., decision making, social interactions) and has been attributed to structural differences in white matter tracts connecting cortical regions to the hippocampus (e.g., fornix) and striatum (e.g., internal capsule) in younger-old adults (ages 65-85 years). However, evidence of associative learning has not been assessed within oldest-old adults (ages 90+ years), despite its relevance to other extensively characterized cognitive abilities in the oldest-old and the relatively large effect of advanced age on the microstructural composition of these white matter tracts. We acquired multicompartment diffusion-weighted magnetic resonance imaging data from 22 oldest-old adults without dementia (mean age = 92.91 ± 1.44 years) who also completed an associative learning task. Behavioral results revealed significantly better associative learning performance during later task stages, as expected if participants incidentally learned the cue-cue-target associations for frequently occurring event triplets. Moreover, better learning performance was significantly predicted by better microstructure of cortico-striatal white matter (posterior limb of the internal capsule). Finding that associative learning abilities in the 10^th decade of life are supported by better microstructure of white matter tracts connecting the cortex to the striatum underscores their importance to learning performance across the entire lifespan.

Multiple mechanisms regulate statistical learning of orthographic regularities in school-age children: Neurophysiological evidence

Using event-related potentials (ERPs), this study investigated how the brains of Chinese children of different ages extract and encode relational patterns contained in orthographic input. Ninety-nine Chinese children in Grades 1-3 performed an artificial orthography statistical learning task that comprised logographic components embedded in characters with high (100%), moderate (80%), and low (60%) positional consistency. The behavioral results indicated that across grades, participants more accurately recognized characters with high rather than low consistency. The neurophysiological results revealed that in each grade, the amplitude of some ERP components differed, with a larger P1 effect in the high consistency condition and a larger N170 and left-lateralized P300 effect in the low consistency condition. A smaller N170 effect occurred in Grade 3 than in Grade 1, and a larger P300 effect occurred in Grade 1 than in either Grade 2 or 3. These findings suggest the dynamic nature of statistical learning by showing that neural adaptation associated with N170, and attention and working memory related to P1 and P300, regulate different types of structural input, and that children's abilities to prioritize these mechanisms vary with context and age.

Indispensable skills for human employees in the age of robots and AI

Purpose

Based on sociotechnical systems theory, social (human) and technological sub-systems in an organization should be taken in account when making strategic decisions and designed to fit the demands of the environment for organizational effectiveness. Yet there is very limited information in literature on whether employees are well equipped with indispensable (human) skills to prepare them combating challenges caused by advanced technology. The purpose of this study is to empirically investigate employees’ human skills that are critical for success in the Age of Robots and Artificial Intelligence from human resource development’s perspective.

Design/methodology/approach

A questionnaire was developed for the purpose of this exploratory study. A total of 422 US Midwest employees were surveyed on their human skills level that are critical for success in the Industry 4.0 transformation.

Findings

In general, the respondents could perform all the measured human skills (which can be categorized into social skillset and decision-making skillset) more than adequate but may vary by education level and gender. To strengthen one’s human skills, organizations may begin with facilitating employees on relationship building to create a support system and a strong sense of belonging, which will promote their social sensitivity and collaboration skill development, as well as decision-making skillset.

Originality/value

The findings of this study can be used for techno-structural interventions and employee development programs. This study highlights the importance of investigating human skills to cope with the changing nature of work and make upskilling more feasible and flexible for workers to be robot-proof.

Learning and generalization of repetition-based rules in autism

Rule Learning (RL) allows us to extract and generalize high-order rules from a sequence of elements. Despite the critical role of RL in the acquisition of linguistic and social abilities, no study has investigated RL processes in Autism Spectrum Disorder (ASD). Here, we investigated RL in high-functioning autistic adolescents with ASD, examining whether their ability to extract and generalize rules from a sequence of visual elements is affected by the social vs. non-social nature of the stimulus and by visual working memory (WM). Using a forced-choice paradigm, ASD adolescents and typically developing (TD) peers were tested for their ability to detect and generalize high-order, repetition-based rules from visual sequences of simple non-social stimuli (shapes), complex non-social stimuli (inverted faces), and social stimuli (upright face). Both ASD and TD adolescents were able to generalize the rule they had learned to new stimuli, and their ability was modulated by the social nature of the stimuli and the complexity of the rule. Moreover, an association between RL and WM was found in the ASD, but not TD group, suggesting that ASD might have used additional or alternative strategies that relied on visual WM resources.

Speed and accuracy instructions affect two aspects of skill learning differently

Procedural learning is key to optimal skill learning and is essential for functioning in everyday life. The findings of previous studies are contradictory regarding whether procedural learning can be modified by prioritizing speed or accuracy during learning. The conflicting results may be due to the fact that procedural learning is a multifaceted cognitive function. The purpose of our study is to determine whether and how speed and accuracy instructions affect two aspects of procedural learning: the learning of probability-based and serial-order-based regularities. Two groups of healthy individuals were instructed to practice on a cued probabilistic sequence learning task: one group focused on being fast and the other on being accurate during the learning phase. The speed instruction resulted in enhanced expression of probability-based but not serial-order-based knowledge. After a retention period, we instructed the participants to focus on speed and accuracy equally, and we tested their acquired knowledge. The acquired knowledge was comparable between groups in both types of learning. These findings suggest that different aspects of procedural learning can be affected differently by instructions. However, only momentary performance might be boosted by speed instruction; the acquired knowledge remains intact. In addition, as the accuracy instruction resulted in accuracy near ceiling level, the results illustrate that response errors are not needed for humans to learn in the procedural domain and draw attention to the fact that different instructions can separate competence from performance.

Evaluation of a tablet-based assessment tool for measuring cognition among children 4-6 years of age in Ghana

OBJECTIVES

To investigate several basic psychometric properties, including construct, convergent and discriminant validity, of the tablet-based Rapid Assessment of Cognitive and Emotional Regulation (RACER) among children aged 4-6 years in Ghana.

METHODS

We investigated whether RACER tasks administered to children in Ghana could successfully reproduce expected patterns of performance previously found in high-income countries on similar tasks assessing inhibitory control (e.g., slower responses on inhibition trials), declarative memory (e.g., higher accuracy on previously seen items), and procedural memory (e.g., faster responses on sequence blocks). Next, we assessed the validity of declarative memory and inhibitory control scores by examining associations of these scores with corresponding paper-based test scores and increasing child age. Lastly, we examined whether RACER was more sensitive than paper-based tests to environmental risk factors common in low- and middle-income countries (LMICs).

RESULTS

Of the 966 children enrolled, more than 96% completed the declarative memory and inhibitory control tasks; however, around 30% of children were excluded from data analysis on the procedural memory task due to missing more than half of trials. The performance of children in Ghana replicated previously documented patterns of performance. RACER inhibitory control accuracy score was significantly correlated with child age (r (929) = .09, p = .007). However, our findings did not support other hypotheses.

CONCLUSIONS

The high task completion rates and replication of expected patterns support that certain RACER sub-tasks are feasible for measuring child cognitive development in LMIC settings. However, this study did not provide evidence to support that RACER is a valid tool to capture meaningful individual differences among children aged 4-6 years in Ghana.

The posterior cerebellum and temporoparietal junction support explicit learning of social belief sequences

This study tests the hypothesis that the posterior cerebellum is involved in social cognition by identifying and automatizing sequences of social actions. We applied a belief serial reaction time task (Belief SRT task), which requires mentalizing about two protagonists' beliefs about how many flowers they receive. The protagonists' beliefs could either be true or false depending on their orientation (true belief: oriented towards and directly observing the flowers; or false belief: oriented away and knowing only prior information about flowers). A Control SRT task was created by replacing protagonists and their beliefs with shapes and colors. Participants were explicitly told that there was a standard sequence related to the two protagonists' belief orientations (Belief SRT task) or the shapes' colors (Control SRT task). Both tasks included a Training phase where the standard sequence was repeated and a Test phase where this standard sequence was interrupted by random sequences. As hypothesized, compared with the Control SRT task, the Belief SRT task recruited the posterior cerebellar Crus II and the temporoparietal junction (TPJ) more. Faster response times were correlated with less Crus II activation and with more TPJ activation, suggesting that the Crus II supported automatizing the belief sequence while the TPJ supported inferring the protagonists' beliefs. Also as hypothesized, compared with an implicit version of the Belief SRT task (i.e., participants did not know about the existence of sequences; Ma, Pu, et al., 2021b), the cerebellar Crus I &II was engaged less during initial training and automatic application of the sequence, and the cortical TPJ was activated more in processing random sequences.

Man vs. machine: A comparison of human and computer assessment of nonverbal behavior in social anxiety disorder

Social anxiety disorder (SAD) is a common psychological disorder associated with broad interpersonal impairment. Most previous studies have examined nonverbal behavior in SAD using human coders. However, one recent study utilized a machine-based analysis of nonverbal behavior and dyadic synchrony in SAD (Asher, Kauffmann, & Aderka, 2020). In the present study, we compared human and computer assessments of nonverbal behavior in social anxiety to enhance our knowledge about their commonalities and unique differences in capturing nonverbal behavior in the context of SAD. Specifically, the present study included 152 individuals: 38 individuals diagnosed with SAD and 114 individuals without SAD. Participants formed 76 opposite-sex interaction dyads comprising either two individuals without SAD (n = 39 control dyads) or one individual with SAD and one individual without SAD (n = 37 SAD dyads). All participants underwent a getting-acquainted task and were videotaped during the conversation. Half of the interactions were small talk interactions and half were closeness-generating interactions that required significant self-disclosure. We found that both types of coding were associated with self-reported social anxiety but that machine-based coding was superior in capturing social anxiety in closeness-generating contexts. Implications for research on nonverbal behavior in SAD are discussed.

Memory for facial expressions on the autism spectrum: The influence of gaze direction and type of expression

Face memory research in autism has largely neglected memory for facial expressions, in favor of memory for identity. This study in three experiments examined the role of gaze direction and type of expression on memory for facial expressions in relation to the autism spectrum. In the learning phase, four combinations of facial expressions (joy/anger) and gaze direction (toward/away), displayed by 16 different identities, were presented. In a subsequent surprise test the same identities were presented displaying neutral expressions, and the expression of each identity had to be recalled. In Experiment 1, typically-developed (TD) individuals with low and high Autism Quotient (AQ) scores were tested with three repetitions of each emotion/gaze combination, which did not produce any modulations. In Experiment 2, another group of TD individuals with low and high AQ scores were tested with eight repetitions, resulting in a "happy advantage" and a "direct gaze advantage", but no interactions. In Experiment 3, individuals with high-functioning autism (HFA) and a matched TD group were tested using eight repetitions. The HFA group revealed no emotion or gaze effects, while the matched TD group showed both a happy and a direct gaze advantage, and again no interaction. The results suggest that in autistic individuals the memory for facial expressions is intact, but is not modulated by the person's expression type and gaze direction. We discuss whether anomalous implicit learning of facial cues could have contributed to these findings, its relevance for social intuition, and its possible contribution to social deficits in autism. LAY SUMMARY: It has often been found that memory for someone's face (facial identity) is less good in autism. However, it is not yet known whether memory for someone's facial expression is also less good in autism. In this study, the memory for expressions of joy and anger was investigated in typically-developed (TD) individuals who possessed either few or many autistic-like traits (Experiments 1 and 2), and in individuals with high-functioning autism (Experiment 3). The gaze direction was also varied (directed either toward, or away from, the observer). We found that TD individuals best remembered expressions of joy, and remembered expressions of both joy and anger better when the gaze was directed at them. These effects did not depend on the extent to which they possessed autistic-like traits. Autistic participants remembered the facial expression of a previously encountered person as good as TD participants did. However, in contrast to the TD participants, the memory of autistic participants was not influenced by the expression type and gaze direction of the previously encountered persons. We discuss whether this may lead to difficulties in the development of social intuition, which in turn could give rise to difficulties in social interaction that are characteristic for autism.

Intuition as Emergence: Bridging Psychology, Philosophy and Organizational Science

Accelerating environmental uncertainty and the need to cope with increasingly complex market and social demands, combine to create high value for the intuitive approach to decision-making at the strategic level. Research on intuition suffers from marked fragmentation, due to the existence of disciplinary silos based on diverse, apparently irreconcilable, ontological and epistemological assumptions. Not surprisingly, there is no integrated interdisciplinary framework suitable for a rich account of intuition, contemplating how affect and cognition intertwine in the intuitive process, and how intuition scales up from the individual to collective decision-making. This study contributes to the construction of a broad conceptual framework, suitable for a multi-level account of intuition and for a fruitful dialogue with distant research areas. It critically discusses two mainstream conceptualizations of intuition which claim to be grounded in a cross-disciplinary consensus. Drawing on the complexity paradigm, it then proposes a conceptualization of intuition as emergence. Finally, it explores the theoretical and practical implications.

Age group differences in learning-related activity reflect task stage, not learning stage

Healthy aging is accompanied by declines in the ability to learn associations between events, even when their relationship cannot be described. Previous functional magnetic resonance imaging (fMRI) studies have attributed these implicit associative learning (IAL) deficits to differential engagement of the hippocampus and basal ganglia in older relative to younger adults in early and late stages of the task, respectively. However, these task stages have been confounded with age group differences in learning performance that emerge later and to a lesser degree in older adults. To disentangle the effects of task stage from learning stage (i.e., when there is significant evidence of learning) on age group differences in the neural substrates of IAL, we acquired fMRI data while 28 younger (20.8 ± 2.3 years) and 22 older (73.6 ± 6.8 years) healthy adults completed the Triplets Learning Task, in which the location of two cues predicted the location of a target with high (HF) or low (LF) frequency. When matched for task stage, results revealed worse learning performance and increased IAL-related activity in the hippocampus during the early stage and in the globus pallidum during the late stage in older relative to younger adults. However, when matched for learning stage, there were no significant age group differences in learning performance or IAL-related activity. Thus, although learning emerges later for older adults, they are engaging similar brain regions as younger adults when learning the associations, suggesting that previous reports of age group differences reflect effects of age on task stage, but not learning stage.

Measuring statistical learning by eye-tracking

Statistical learning—the skill to pick up probability-based regularities of the environment—plays a crucial role in adapting to the environment and learning perceptual, motor, and language skills in healthy and clinical populations. Here, we developed a new method to measure statistical learning without any manual responses. We used the Alternating Serial Reaction Time (ASRT) task, adapted to eye-tracker, which, besides measuring reaction times (RTs), enabled us to track learning-dependent anticipatory eye movements. We found robust, interference-resistant learning on RT; moreover, learning-dependent anticipatory eye movements were even more sensitive measures of statistical learning on this task. Our method provides a way to apply the widely used ASRT task to operationalize statistical learning in clinical populations where the use of manual tasks is hindered, such as in Parkinson’s disease. Furthermore, it also enables future basic research to use a more sensitive version of this task to measure predictive processing.

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.

When Reflection Hurts: The Effect of Cognitive Processing Types on Organizational Adaptation to Discontinuous Change

Technological breakthroughs, institutional disruptions, and natural disasters often alter the course of organizations and entire industries. Such discontinuous changes threaten organizations’ survival by affecting the value of the knowledge accumulated in routines and capabilities. Although it is widely acknowledged that managerial cognition is a critical antecedent of organizational responses to discontinuous change, the role of type 1 (intuitive) and type 2 (reflective) processing in the adaptation of shared patterns of behavior, that is, routines, remains understudied. Drawing on dual-process theory, we propose that particular features of type 1 processing render this approach superior to type 2 processing, especially in highly ambiguous environments in which information is limited and difficult to verify. We tested our hypotheses in a longitudinal experiment linking individual-level factors with organizational-level practices of routine adaptation. Experienced managers, paired in 80 groups, developed routines in a first round of a simulation game; in a second round, we then introduced a discontinuous change making previous routines obsolete in order to observe how they adapted. The data show that priming type 1 processing facilitates organizational adaptation more than type 2 processing by providing faster, more routinized, efficiently coordinated, and optimal responses. In addition, type 1 appears to be more functional in highly ambiguous environments, whereas type 1 and type 2 processes yield similar levels of performance under low levels of ambiguity. Overall, our study advances the understanding of the nondeliberative dimension of organizational adaptation to discontinuous change.

Investigating Managers' Fine-Grained Evaluation Processes in Organizations: Exploring Two Dual-Process Perspectives

The dual-process theory is a significant theory in both organizational theory and social psychology and two conjectures about this theory are considered in this manuscript; the default-interventionist vs. parallel-competitive account. Our research goal is to empirically investigate these two views. In concrete terms, by using event-related potentials (ERPs), we seek to study the fine-grained brain processes and self-reported feelings involved in managers' evaluations of target employees within an economic context (firing employees) vs. a social network context (excluding employees). Using the stereotype content model categories, each target employee has high (or low) warmth and high (or low) levels of competence. In the fine-grained ERP analysis of the brain process, we focus on three time windows of interest: novelty detection (N2) and goal violation detection (N400) at the unconscious level, and we then evaluate conscious emotional arousal (late positive potential, LPP). Finally, we focus on the self-reported feelings when having to fire or exclude target employees. As goal pursuit theory predicts, the brain dynamics and self-reported measures differ widely across the two organizational contexts; in concrete terms, processes at a later stage overrule early stages depending on the context. This implies that the data bespeaks more for the parallel-competitive account than the default-interventionist account. We discuss the implications of these findings for research in management and management practice.

What’s not to like about evidence-based management: a hyper-rational fad?

Purpose

A topic currently receiving significant academic and practitioner attention is called evidence-based management. The purpose of this paper is to suggest that this approach is sometimes over-sold and may be a fad. Additionally, evidence-based management fails to fully recognize the importance of tacit knowledge, what Kahneman calls system 1. Evidence-based management does provide tools to better use what Kahneman calls system 2, rationality. Decision-makers need to take advantage of both rational and beyond rational processes.

Design/methodology/approach

This is an essay, it is not a report of a study. At this point in time, this paper needs thinking, reflection, pondering, more than a data-based study.

Findings

Advocates promote evidence-based management in part to help avoid fads, yet evidence-based management itself has many of the characteristics of a fad. Evidence-based management is based on an objective rational view of the world and suggests highly rational methods of decision-making. However, a rational fact-based might not give sufficient credit to instinct and feelings. Decision-makers should take into account facts, evidence, when making decisions, but not ignore intuition, hunches and feelings. This study is learning that decisions use a galaxy of approaches, with both cognitive and affective flexibility.

Research limitations/implications

As with any opinion-based paper, this lacks empirical support. Proponents ask us to believe in evidence-based management. Neither we, the authors of this paper, nor the proponents of evidence-based management can empirically support the ideas offered. An additional limitation is that the paper is written in one language, English. Translation into another language might yield different meanings.

Practical implications

There are advantages for scholars and practitioners to look at the best available evidence. There can be disadvantages in overlooking non-quantifiable factors.

Social implications

Those who use evidence-based management should also take into account feelings, ethics, aesthetics, creativity, for the betterment of society. To solve wicked problems one needs more than facts and rational analysis.

Originality/value

The overwhelming majority of those writing about evidence-based management are supporters. This study offers a different view. This paper brings new ideas and new thinking to both the extensive fad literature and the huge evidence-based management literature. Evidence-based management is discussed widely. Google Scholar lists more than two million papers in 2019, 2020 and 2021 on evidence-based management. Readers of this journal should critically evaluate this popular set of ideas.

Lower-level associations in Gilles de la Tourette syndrome: Convergence between hyperbinding of stimulus and response features and procedural hyperfunctioning theories

Gilles de la Tourette syndrome (GTS) can be characterized by enhanced cognitive functions related to creating, modifying and maintaining connections between stimuli and responses (S-R links). Specifically, two areas, procedural sequence learning and, as a novel finding, also event file binding, show converging evidence of hyperfunctioning in GTS. In this review, we describe how these two enhanced functions can be considered as cognitive mechanisms behind habitual behaviour, such as tics in GTS. Moreover, the presence of both procedural sequence learning and event file binding hyperfunctioning in the same disorder can be treated as evidence for their functional connections, even beyond GTS. Importantly though, we argue that hyperfunctioning of event file binding and procedural learning are not interchangeable: they have different time scales, different sensitivities to potential impairment in action sequencing and distinguishable contributions to the cognitive profile of GTS. An integrated theoretical account of hyperbinding and hyperlearning in GTS allows to formulate predictions for the emergence, activation and long-term persistence of tics in GTS.

The posterior cerebellum supports implicit learning of social belief sequences

Recent studies have documented the involvement of the posterior cerebellar Crus (I & II) in social mentalizing, when sequences play a critical role. We investigated for the first time implicit learning of belief sequences. We created a novel task in which true and false beliefs of other persons were alternated in an adapted serial reaction time (SRT) paradigm (Belief SRT task). Participants observed two protagonists whose beliefs concerning reality were manipulated, depending on their orientation toward the scene (true belief: directly observing the situation) or away from it (false belief: knowing only the prior situation). Unbeknownst to the participants, a fixed sequence related to the two protagonists' belief orientations was repeated throughout the task (Training phase); and to test the acquisition of this fixed sequence, it was occasionally interrupted by random sequences (Test phase). As a nonsocial control, the two protagonists and their orientations were replaced by two different shapes of different colors respectively (Control SRT task). As predicted, the posterior cerebellar Crus I & II were activated during the Belief SRT task and not in the Control SRT task. The Belief SRT task revealed that Crus I was activated during the initial learning of the fixed sequence (Training phase) and when this learned sequence was interrupted by random sequences (Test phase). Moreover, Crus II was activated during occasional reappearance of the learned sequence in the context of sequence violations (Test phase). Our results demonstrate the contribution of the posterior cerebellar Crus during implicit learning and predicting new belief sequences.

Should you follow your gut? The impact of expertise on intuitive hiring decisions for complex jobs

As jobs become increasingly complex, organizations are challenged with finding effective ways to select and hire successful employees. The high level of uncertainty generally associated with hiring decisions is greater for complex jobs where it is difficult to identify the predictors of good job performance. Intuition research has found expert intuition to be effective in highly uncertain decision environments. However, most employment selection research dismisses the use of intuition and argues that even expert interviewers should not rely on their intuition. To bridge the two research streams, this paper addresses the research question: for complex jobs, can the intuition of expert decision-makers enhance the effectiveness of hiring decisions? The hypotheses were tested via an experimental study design using expert and nonexpert interviewer samples. The results demonstrate that, when recruiting for complex jobs, interviewer expertise does increase the quality of intuitive hiring decisions.

Human moral decision-making through the lens of Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by the loss of dopaminergic neurons in the basal ganglia (BG) and thalamocortical circuitry. While defective motor control has long been considered the defining symptom of PD, mounting evidence indicates that the BG are fundamentally important for a multitude of cognitive, emotional, and motivational processes in addition to motor function. Here, we review alterations in moral decision-making in people with PD, specifically in the context of deceptive behavior. We report that PD patients exhibit two opposite behavioral patterns: hyper- and hypo-honesty. The hyper-honest subgroup engages in deception less often than matched controls, even when lying is associated with a monetary payoff. This behavioral pattern seems to be linked to dopaminergic hypo-activity, implying enhanced harm avoidance, risk aversion, non-impulsivity, and reduced reward sensitivity. On the contrary, the hypo-honest subgroup-often characterized by the additional diagnosis of impulse control disorders (ICDs) and dopamine dysregulation syndrome (DDS)-deceives more often than both PD patients without ICDs/DDS and controls. This behavioral pattern appears to be associated with dopaminergic hyperactivity, which underpins enhanced novelty-seeking, risk-proneness, impulsivity, and reward sensitivity. We posit that these two complementary behavioral patterns might be related to dysfunction of the dopaminergic reward system, leading to reduced or enhanced motivation to deceive. Only a few studies have directly investigated moral decision-making in PD and other neurodegenerative disorders affecting the BG, and further research on the causal role of subcortical structures in shaping moral behavior is needed.

Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review

With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researchers are striving towards employing these techniques for advancing clinical practice. One of the key objectives in healthcare is the early detection and prediction of disease to timely provide preventive interventions. This is especially the case for epilepsy, which is characterized by recurrent and unpredictable seizures. Patients can be relieved from the adverse consequences of epileptic seizures if it could somehow be predicted in advance. Despite decades of research, seizure prediction remains an unsolved problem. This is likely to remain at least partly because of the inadequate amount of data to resolve the problem. There have been exciting new developments in ML-based algorithms that have the potential to deliver a paradigm shift in the early and accurate prediction of epileptic seizures. Here we provide a comprehensive review of state-of-the-art ML techniques in early prediction of seizures using EEG signals. We will identify the gaps, challenges, and pitfalls in the current research and recommend future directions.

Future orientation in successful therapies: Expanding the concept of goal in the working alliance

OBJECTIVE

To better understand how therapists facilitate client goal attainment in therapy, we analyzed therapists' future-oriented actions in good outcome cases in which clients recorded high ratings on goal items in the Working Alliance Inventory-Short Revised.

METHOD

We selected clients who were within the clinical range (OQ-45.2) at pretreatment, demonstrated reliable change at the end of treatment, and recorded high WAI client goals scores early in treatment. Qualitative analyses of transcripts of the initial three sessions and client posttreatment interviews were integrated into a combined analysis to identify themes across the two separate sets of findings.

RESULTS

Therapist future-oriented activity included: (1) Picking up explicit and implicit intentions; (2) using linguistic devices, such as meta-communication, action language, and hedging; (3) using evocative interventions; and (4) nudging the client into practicing change. Core finding: Therapists aligned with clients' directionality in a forward-driven, gradually evolving process.

CONCLUSION

Conceptual and clinical implications are discussed.

Retrieval of a well-established skill is resistant to distraction: Evidence from an implicit probabilistic sequence learning task

The characteristics of acquiring new sequence information under dual-task situations have been extensively studied. A concurrent task has often been found to affect performance. In real life, however, we mostly perform a secondary task when the primary task is already well acquired. The effect of a secondary task on the ability to retrieve well-established sequence representations remains elusive. The present study investigates whether accessing well-acquired probabilistic sequence knowledge is affected by a concurrent task. Participants acquired non-adjacent regularities in an implicit probabilistic sequence learning task. After a 24-hour offline period, participants were tested on the same probabilistic sequence learning task under dual-task or single-task conditions. Here, we show that although the secondary task significantly prolonged the overall reaction times in the primary (sequence learning) task, access to the previously learned probabilistic representations remained intact. Our results highlight the importance of studying the dual-task effect not only in the learning phase but also during memory access to reveal the robustness of the acquired skill.

Assessment of multiple implicit self‐concept dimensions using the Extrinsic Affective Simon Task (EAST)

This study explored the psychometric properties of the Extrinsic Affective Simon Task (EAST; De Houwer, 2003a) as adapted for the measurement of the implicit self‐concept of personality. The EAST was adapted to allow the simultaneous assessment of the three traits shyness, anxiousness, and angriness. In order to test the EAST's psychometric properties, 100 participants completed a trait EAST, Implicit Association Tests (IATs), and direct self‐ratings. The EAST showed low internal consistencies and correlated neither with the IATs nor with the direct measures. The main problem of the EAST, namely its low reliability, is discussed, and general conclusions regarding the indirect assessment of the personality self‐concept by EASTs are derived. Copyright © 2004 John Wiley & Sons, Ltd.

Paranormal beliefs: their dimensionality and correlates

Lack of conceptual clarity and multivariate empirical studies has troubled research on superstitious, magical and paranormal beliefs. We defined paranormal beliefs as beliefs in physical, biological or psychological phenomena that feature core ontological properties of another ontological category. The aim was to bring together a range of beliefs and their potential correlates, to analyse whether the beliefs form independent subsets, and to test a structural model of the beliefs and their potential correlates. The results (N = 3261) showed that the beliefs could be best described by one higher‐order factor. There were also four lower‐order factors of paranormal beliefs but their explanatory power was low. Magico‐religious beliefs were best explained by high intuitive thinking, a humanistic world view and low analytical thinking. Copyright © 2006 John Wiley & Sons, Ltd.

Implicit associative learning relates to basal ganglia gray matter microstructure in young and older adults

Older adults are impaired at implicit associative learning (IAL), or the learning of relationships between stimuli in the environment without conscious awareness. These age effects have been attributed to differential engagement of the basal ganglia (e.g. caudate, globus pallidus) and hippocampus throughout learning. However, no studies have examined gray matter diffusion relations with IAL, which can reveal microstructural properties that vary with age and contribute to learning. In this study, young (18-29 years) and older (65-87 years) adults completed the Triplet Learning Task, in which participants implicitly learn that the location of cues predict the target location on some trials (high frequency triplets). Diffusion imaging was also acquired and multicompartment diffusion metrics were calculated using neurite orientation dispersion and density imaging (NODDI). As expected, results revealed age deficits in IAL (smaller differences in performance to high versus low frequency triplets in the late learning stage) and age-related differences in basal ganglia and hippocampus free, hindered, and restricted diffusion. Significant correlations were seen between restricted caudate diffusion and early IAL and between hindered globus pallidus diffusion and late IAL, which were not moderated by age group. These findings indicate that individual differences in basal ganglia, but not hippocampal, gray matter microstructure contribute to learning, independent of age, further supporting basal ganglia involvement in IAL.

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.

Frontal-midline theta frequency and probabilistic learning: A transcranial alternating current stimulation study

Probabilistic learning is a fundamental cognitive ability that extracts and represents regularities of our environment enabling predictive processing during perception and acquisition of perceptual, motor, cognitive, and social skills. Previous studies show competition between neural networks related to executive function/working memory vs. probabilistic learning. Theta synchronization has been associated with the former while desynchronization with the latter in correlational studies. In the present paper our aim was to test causal relationship between fronto-parietal midline theta synchronization and probabilistic learning with non-invasive transcranial alternating current (tACS) stimulation. We hypothesize that theta synchronization disrupts probabilistic learning performance by modulating the competitive relationship. Twenty-six young adults performed the Alternating Serial Reaction Time (ASRT) task to assess probabilistic learning in two sessions that took place one week apart. Stimulation was applied in a double-blind cross-over within-subject design with an active theta tACS and a sham stimulation in a counter-balanced order between participants. Sinusoidal current was administered with 1 mA peak-to-peak intensity throughout the task (approximately 20 min) for the active stimulation and 30 s for the sham. We did not find an effect of fronto-parietal midline theta tACS on probabilistic learning comparing performance during active and sham stimulation. To influence probabilistic learning, we suggest applying higher current intensity and stimulation parameters more precisely aligned to endogenous brain activity for future studies.

Icebergs of Expertise-Based Leadership: The Role of Expert Leaders in Public Administration

There is a pressing need for public administration leaders to exhibit expertise-based intuitive leadership traits for developing countries to respond to sustainability challenges. While the importance of explicit and tacit knowledge to underpin expertise-based intuitive decision-making is known, public service leaders of developing countries can lack these traits. It is necessary to explore the reasons for leadership skills gaps in order to define remedial actions, such as better executive development training. This study conducts 28 in-depth interviews with public administration leaders, managers, and executive training professionals in Pakistan to address the challenge of how to build expertise-based intuitive leadership traits in public administration leaders. The main findings highlight deficiencies in domain-specific knowledge and soft skills. Deficits in the formal training of leaders and the negative contribution of cultural preconditions both result in explicit and tacit knowledge gaps that undermine expertise-based intuitive decision-making. An “iceberg of expertise-based leadership” model is conceptualized, extending on previous models, to describe the intangible role that explicit and tacit knowledge play in the visible expression of leadership skills. The relevance of this model for the success of public sector-led initiatives for sustainable development is highlighted.

Episodes of meeting in psychotherapy: an empirical exploration of patients' experiences of subjective change during their psychotherapy process

This study aims to assess moments of meeting in psychotherapy -understood as moments of intense connectedness and intimacy, shared between patient and therapist during any therapeutic encounter that enable a spin in the therapy process- using a qualitative interview with patients who were undergoing or had finished psychological treatment. Micro-pehenomenological interviews were conducted with nine patients who were undergoing or had finished psychological treatment. Transcriptions of the interviews were subject to micro-phenomenological analysis. A general structure of episodes of meeting showing their temporal evolution was identified and divided into six consecutive phases. These findings suggest that episodes of meeting in psychotherapy are lived and remembered by patients in a significant way; they are emotionally charged and have a meaning for each participant. Also, emotional and nonverbal cues seem to be highly relevant features. Moments of meeting could be understood as implicit mechanisms that allow changes in the implicit relational domain.

The relationship between subjective sleep quality and cognitive performance in healthy young adults: Evidence from three empirical studies

The role of subjective sleep quality in cognitive performance has gained increasing attention in recent decades. In this paper, our aim was to test the relationship between subjective sleep quality and a wide range of cognitive functions in a healthy young adult sample combined across three studies. Sleep quality was assessed by the Pittsburgh Sleep Quality Index, the Athens Insomnia Scale, and a sleep diary to capture general subjective sleep quality, and the Groningen Sleep Quality Scale to capture prior night’s sleep quality. Within cognitive functions, we tested working memory, executive functions, and several sub-processes of procedural learning. To provide more reliable results, we included robust frequentist as well as Bayesian statistical analyses. Unequivocally across all analyses, we showed that there is no association between subjective sleep quality and cognitive performance in the domains of working memory, executive functions and procedural learning in healthy young adults. Our paper can contribute to a deeper understanding of subjective sleep quality and its measures, and we discuss various factors that may affect whether associations can be observed between subjective sleep quality and cognitive performance.

The relationship between subjective sleep quality and cognitive performance in healthy young adults: Evidence from three empirical studies

The role of subjective sleep quality in cognitive performance has gained increasing attention in recent decades. In this paper, our aim was to test the relationship between subjective sleep quality and a wide range of cognitive functions in a healthy young adult sample combined across three studies. Sleep quality was assessed by the Pittsburgh Sleep Quality Index, the Athens Insomnia Scale, and a sleep diary to capture general subjective sleep quality, and the Groningen Sleep Quality Scale to capture prior night's sleep quality. Within cognitive functions, we tested working memory, executive functions, and several sub-processes of procedural learning. To provide more reliable results, we included robust frequentist as well as Bayesian statistical analyses. Unequivocally across all analyses, we showed that there is no association between subjective sleep quality and cognitive performance in the domains of working memory, executive functions and procedural learning in healthy young adults. Our paper can contribute to a deeper understanding of subjective sleep quality and its measures, and we discuss various factors that may affect whether associations can be observed between subjective sleep quality and cognitive performance.

Statistical Learning and Social Competency: The Mediating Role of Language

The current study sought to examine the contribution of auditory and visual statistical learning on language and social competency abilities as well as whether decreased statistical learning abilities are related to increased autistic traits. To answer these questions, participants' (N = 95) auditory and visual statistical learning abilities, language, social competency, and level of autistic traits were assessed. Although the relationships observed were relatively small in magnitude, our results demonstrated that visual statistical learning related to language and social competency abilities and that auditory learning was more related to autism symptomatology than visual statistical learning. Furthermore, the relationship between visual statistical learning and social competency was mediated by language comprehension abilities, suggesting that impairments in statistical learning may cascade into impairments in language and social abilities.

Thinking fast or slow? Functional magnetic resonance imaging reveals stronger connectivity when experienced neurologists diagnose ambiguous cases

For ∼40 years, thinking about reasoning has been dominated by dual-process theories. This model, consisting of two distinct types of human reasoning, one fast and effortless and the other slow and deliberate, has also been applied to medical diagnosis. Medical experts are trained to diagnose patients based on their symptoms. When symptoms are prototypical for a certain diagnosis, practitioners may rely on fast, recognition-based reasoning. However, if they are confronted with ambiguous clinical information slower, analytical reasoning is required. To examine the neural underpinnings of these two hypothesized forms of reasoning, 16 highly experienced clinical neurologists were asked to diagnose two types of medical cases, straightforward and ambiguous cases, while functional magnetic resonance imaging was being recorded. Compared with reading control sentences, diagnosing cases resulted in increased activation in brain areas typically found to be active during reasoning such as the caudate nucleus and frontal and parietal cortical regions. In addition, we found vast increased activity in the cerebellum. Regarding the activation differences between the two types of reasoning, no pronounced differences were observed in terms of regional activation. Notable differences were observed, though, in functional connectivity: cases containing ambiguous information showed stronger connectivity between specific regions in the frontal, parietal and temporal cortex in addition to the cerebellum. Based on these results, we propose that the higher demands in terms of controlled cognitive processing during analytical medical reasoning may be subserved by stronger communication between key regions for detecting and resolving uncertainty.