The Influence of the BDNF Val66Met Polymorphism on Mechanisms of Semantic Priming: Analyses with Drift-Diffusion Models of Masked and Unmasked Priming

Automatic and strategic processes in semantic priming can be investigated with masked and unmasked priming tasks. Unmasked priming is thought to enable strategic processes due to the conscious processing of primes, while masked priming exclusively depends on automatic processes due to the invisibility of the prime. Besides task properties, interindividual differences may alter priming effects. In a recent study, masked and unmasked priming based on mean response time (RT) and error rate (ER) differed as a function of the BDNF Val66Met polymorphism (Sanwald et al., 2020). The BDNF Val66Met polymorphism is related to the integrity of several cognitive executive functions and might thus influence the magnitude of priming. In the present study, we reanalyzed this data with drift-diffusion models. Drift-diffusion models conjointly analyze single trial RT and ER data and serve as a framework to elucidate cognitive processes underlying priming. Masked and unmasked priming effects were observed for the drift rates ν, presumably reflecting semantic preactivation. Priming effects on nondecision time t0 were especially pronounced in unmasked priming, suggesting additional conscious processes to be involved in the t0 modulation. Priming effects on the decision thresholds a may reflect a speed-accuracy tradeoff. Considering the BDNF Val66Met polymorphism, we found lowered drift rates and decision thresholds for Met allele carriers, possibly reflecting a superficial processing style in Met allele carriers. The present study shows that differences in cognitive tasks between genetic groups can be elucidated using drift-diffusion modeling.     

How Stories in Memory Perpetuate the Continued Influence of False Information

People often encounter information that they subsequently learn is false. Past research has shown that people sometimes continue to use this misinformation in their reasoning, even if they remember that the information is false, which researchers refer to as the continued influence effect. The current work shows that the continued influence effect depends on the stories people have in memory: corrected misinformation was found to have a stronger effect on people's beliefs than information that was topically related to the story if it helped to provide a causal explanation of a story they had read previously. We argue this effect occurs because information that can fill a causal “gap” in a story enhances comprehension of the story event, which allows people to build a complete (if inaccurate) event model that they prefer over an accurate but incomplete event model. This effect is less likely to occur for stories in memory that end in a negative way, presumably because people are more motivated to accurately understand negative outcome events.     

Does exercise-induced muscle damage impair subsequent motor skill learning?

Motor skill learning is a fundamental aspect of human behavior based on the calibration of internal models via sensory information such as proprioception. Some conditions, as exercise-induced muscle damage (EIMD), disrupt proprioceptive information, and may cause learning impairment. Such possible relation between EIMD and motor skill learning has not yet been investigated and it is the aim of this study. For this purpose, thirty male university students (19.3 ± 1.8 years) were equally assigned to two groups: EIMD and CON group. The EIMD group received a treatment to induce muscle damage consisting of a weight lifting protocol directed to the agonist muscles related to the task prior to the pretest and to the learning sessions. EIMD was verified and compared between groups and along the process (0–168 h) by means of the degree of delayed onset muscle soreness (DOMS), perceived total quality recovery and maximal isometric strength (MIS). To investigate motor skill learning, both groups practiced a dart throwing task for four sessions with 150 trials in each session. Recovery status and DOMS were recovered at 96 h in the EIMD group, and MIS was not recovered throughout 168 h. In contrast, muscle damage parameters were not altered across 168 h in the CON group. Accuracy and consistency were compared within and between groups in a pretest posttest design. The EIMD group showed less accurate and consistent results on the long term (delayed posttest). Results confirmed our hypothesis that EIMD, a common condition in sports and in rehab practices, may hinder motor skill learning, possibly due to neurological aspects such as proprioceptive information, its relation to central nervous system reorganization and internal model consolidation.     

Suicide as an interpersonal phenomenon: Dyadic methodological and statistical considerations in suicide research

Interpersonal risk and resilience factors are prominent in current conceptual models of suicide. A growing body of empirical evidence links suicidal thoughts and behaviors to a range of interpersonal phenomenon adding further support to the value of this line of inquiry. At present, research on interpersonal phenomenon focuses on assessing individuals' perceptions of interpersonal phenomenon, such as appraisals of burdensomeness, experienced loneliness, and thwarted belongingness. As this line of research continues to develop, we argue that it would be valuable to consider incorporating conceptual models of interpersonal phenomenon and corresponding methodological approaches from closely allied fields. After providing a brief overview of interpersonal models of suicide, we present an introduction to conceptual models of interpersonal phenomenon developed in relationship science, describe how these models can be applied to the study of interpersonal phenomenon in suicide research, and close with a guided tutorial on data collection and statistical analysis methods for testing hypotheses derived from these conceptual approaches. References for additional reading are provided, and the Appendix S1 provides simulated data sets and statistical code for the analyses in the tutorial section.     

The role of attitudes in perceptions of bicycle facilities: A latent-class regression approach

While many professionals support bicycling for transportation to reduce traffic congestion and improve public health, many potential cyclists see the risks from traffic injuries as a major barrier. The purpose of this paper is to investigate the impact of bicycle facilities on perceptions of bikeability, and how these perceptions vary among different groups. Data comes from surveys (N = 2157) deployed in ten study neighborhoods as part of two research projects. Respondents were asked to rate a series of images of hypothetical roadways in terms of perceived comfort, perceived safety, and willingness to try bicycling. Latent-class regression was used to model these responses, with bicycle facility type and roadway characteristics as explanatory variables and sociodemographics and attitudinal factors (car preference, bike enjoyment, risk tolerance, and anti-exercise) as covariates for class membership. A recurring theme among the presented solutions is the emergence of two pro-bicycle classes - risk-embracing and risk-cautious - together with a pro-car class. Results indicate that the impact of protected bicycle facilities on perceptions are much higher for the pro-bike/risk-cautious group. The major implication of these findings is that there likely exists a sizeable segment of the population that, although perhaps just as interested in bicycling as the typical pro-bicycle class, is more cautious in their perceptions of comfort and safety. Those belonging to this subgroup generally view minimal facilities as much more unsafe and uncomfortable than their risk-accepting counterparts, but have comparable perceptions regarding high-quality protected bicycle facilities.     

Fatigue risk management based on self-reported fatigue: Expanding a biomathematical model of fatigue-related performance deficits to also predict subjective sleepiness

Biomathematical models of fatigue can be used to predict neurobehavioral deficits during sleep/wake or work/rest schedules. Current models make predictions for objective performance deficits and/or subjective sleepiness, but known differences in the temporal dynamics of objective versus subjective outcomes have not been addressed. We expanded a biomathematical model of fatigue previously developed to predict objective performance deficits as measured on the Psychomotor Vigilance Test (PVT) to also predict subjective sleepiness as self-reported on the Karolinska Sleepiness Scale (KSS). Four model parameters were re-estimated to capture the distinct dynamics of the KSS and account for the scale difference between KSS and PVT. Two separate ensembles of datasets – drawn from laboratory studies of sleep deprivation, sleep restriction, simulated night work, napping, and recovery sleep – were used for calibration and subsequent validation of the model for subjective sleepiness. The expanded model was found to exhibit high prediction accuracy for subjective sleepiness, while retaining high prediction accuracy for objective performance deficits. Application of the validated model to an example scenario based on cargo aviation operations revealed divergence between predictions for objective and subjective outcomes, with subjective sleepiness substantially underestimating accumulating objective impairment, which has important real-world implications. In safety-sensitive operations such as commercial aviation, where self-ratings of sleepiness are used as part of fatigue risk management, the systematic differences in the temporal dynamics of objective versus subjective measures of functional impairment point to a potentially significant risk evaluation sensitivity gap. The expanded biomathematical model of fatigue presented here provides a useful quantitative tool to bridge this previously unrecognized gap.     

First-Order Learning Models With the GDINA: Estimation With the EM Algorithm and Applications

In learning environments, understanding the longitudinal path of learning is one of the main goals. Cognitive diagnostic models (CDMs) for measurement combined with a transition model for mastery may be beneficial for providing fine-grained information about students’ knowledge profiles over time. An efficient algorithm to estimate model parameters would augment the practicality of this combination. In this study, the Expectation–Maximization (EM) algorithm is presented for the estimation of student learning trajectories with the GDINA (generalized deterministic inputs, noisy, “and” gate) and some of its submodels for the measurement component, and a first-order Markov model for learning transitions is implemented. A simulation study is conducted to investigate the efficiency of the algorithm in estimation accuracy of student and model parameters under several factors—sample size, number of attributes, number of time points in a test, and complexity of the measurement model. Attribute- and vector-level agreement rates as well as the root mean square error rates of the model parameters are investigated. In addition, the computer run times for converging are recorded. The result shows that for a majority of the conditions, the accuracy rates of the parameters are quite promising in conjunction with relatively short computation times. Only for the conditions with relatively low sample sizes and high numbers of attributes, the computation time increases with a reduction parameter recovery rate. An application using spatial reasoning data is given. Based on the Bayesian information criterion (BIC), the model fit analysis shows that the DINA (deterministic inputs, noisy, “and” gate) model is preferable to the GDINA with these data.     

Dynamic locomotor imagery in athletes with severe visual impairments

Motor imagery is a mental process not accompanied by movement and widely studied in healthy subjects, related to hand movements in terms of timing. This study compared static and dynamic motor imagery analyzing temporal and spatial features in different locomotor conditions in three different groups of subjects: high-skilled athletes with visual impairments, a group of sighted unprofessional athletes and a control group of sighted subjects. We found that dynamic motor imagery resulted in timely closer to real performance than static motor imagery. The discrepancies between dynamic motor imagery and real condition, in fact, resulted limited to uncommon locomotion, such as lateral walking. Motor imagery resulted closer to real performance in terms of timing than in terms of step length, with the exception of athletes with visual impairments that, differently from the other groups, did not show any significant differences between the numbers of imagined and performed steps. It opens a new question about the relationship between temporal and spatial imagination of locomotion.     

Self-efficacy,mental models and team adaptation: A first approach on football and futsal refereeing

ObjectiveWithin the football and futsal refereeing context, even though referees work within teams, there is very little research considering the implications of team dynamics. In response, this study starts to address this gap in the literature by investigating the moderating effect of mental models on the relationship between self-efficacy beliefs and perceptions of team adaptation within the exciting context of professional and national football and futsal refereeing.DesignWe obtained online questionnaires from 339 active football and futsal referees within the National and Professional league at two distinct points (April and May) within the football season.ResultsSelf-efficacy beliefs were positively associated with perceptions of team adaptation (only for football referees). Mental models were positively associated with team adaptation. Likewise, the moderation between mental models and self-efficacy beliefs was positively associated with perceptions of team adaptation. However, such an effect was only significant at the futsal referees’ level.ConclusionThis study emphasises the importance of mental models for team adaptation and the importance of self-efficacy beliefs in predicting perceptions of team adaptation. We hope that this study represents the first step in a greater appreciation of the salience of team dynamics and their impact on football and futsal referees’ performance and that future research can build upon our work.     

The illness perception questionnaire: A new method for assessing the cognitive representation of illness

Abstract

The Illness Perception Questionnaire (IPQ) is a new method for assessing cognitive representations of illness. The IPQ is a theoretically derived measure comprising five scales that provides information about the five components that have been found to underlie the cognitive representation of illness. The five scales assess identity - the symptoms the patient associates with the illness, cause - personal ideas about aetiology, time-line - the perceived duration of the illness, consequences - expected effects and outcome and cure control - how one controls or recovers from the illness. The IPQ has a specific number of core items but allows the user to add items for particular patient groups or health threats. Data is presented supporting the reliability and validity of the IPQ scales in different chronic illness populations.