Nonlinear model of attention focus during accumulated effort

ObjectivesThe emergent nature and dynamics of Task-Related Thoughts (TRT) during accumulated physical effort was used to test a model of attention focus based on the application of nonlinear dynamic systems theory (NDST).DesignA one-group two-trials quasi experimental design was employed.MethodsEleven physically active participants ran twice on a treadmill at an intensity of 80% of their HR_max until voluntary exhaustion. During the first run their intrinsic dynamics of attention focus was established. Accordingly, during the second run they were asked to intentionally maintain Task-Unrelated Thoughts (TUT), and reporting back about spontaneous switches from TUT to TRT, and vice versa.ResultsResults revealed that the intentionally imposed TUT was stable at the beginning of the test, switched spontaneously to TRT with accumulated effort, competing with TUT and showing metastability, until a final TRT state prevails.ConclusionsThe observed phenomena points to a nonlinear dynamic self-regulation of attention focus during accumulated effort.     

One and Done? Optimal Decisions From Very Few Samples

In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling‐based approximations are a common way to implement Bayesian inference, the very limited numbers of samples often used by humans seem insufficient to approximate the required probability distributions very accurately. Here, we consider this discrepancy in the broader framework of statistical decision theory, and ask: If people are making decisions based on samples—but as samples are costly—how many samples should people use to optimize their total expected or worst‐case reward over a large number of decisions? We find that under reasonable assumptions about the time costs of sampling, making many quick but locally suboptimal decisions based on very few samples may be the globally optimal strategy over long periods. These results help to reconcile a large body of work showing sampling‐based or probability matching behavior with the hypothesis that human cognition can be understood in Bayesian terms, and they suggest promising future directions for studies of resource‐constrained cognition.     

Functional Mental Representation of Volleyball Routines in German Youth Female National Players

The purpose of this study was to examine the overhand volleyball service routines of the German Youth Female National Team. Mental representations of this movement were reconstructed using the Structure Dimensional Analysis-Motoric method. The Routine Questionnaire was administered to collect self-report data. Results indicated that the mental representations of routines are organized in a hierarchical, tree-like structure. The movement mental representations of players not selected to the national team were organized in a less hierarchical manner. The coach's performance ranking was significantly correlated to the athlete's mental representation invariance values (structure quality), indicating a close relationship between mental representation and performance.     

Fluctuating dynamics of perceived exertion in constant-power exercise

ObjectivesTo reveal and study the fluctuating dynamics of perceived exertion (PE) during constant-power exercise performed under different conditions (duration, intensity, and termination).DesignA pilot and two subsequent experimental studies were performed. The studies consisted of manipulating workload and measuring fluctuating perceived exertion dynamics throughout the cycling task.MethodsIn a pilot study Borg's rating of perceived exertion (RPE) was measured every 15 s in 2 groups of 9 participants each (using RPE 6-20 and CR10 scales, respectively) cycling at heavy intensity until volitional exhaustion. The percentage of participants alternating increased and decreased RPE values (fluctuating dynamics) was calculated. In 2 subsequent experiments PE changes (increase/decrease perceptions) were reported when occurring in 2 groups of 13 participants cycling at a moderate intensity for 30 and 60 min, respectively (Experiment 1), and in another group of 12 participants cycling at heavy intensity until volitional exhaustion (Experiment 2). The individual time series of “increase”/“decrease” reports were divided into 5 non-overlapping temporal windows, and the percentages of “PE increase” were calculated for each window.ResultsIn the pilot study 66.6% (RPE 6-20 group) and 33.3% (CR10 group) of the participants showed an RPE fluctuating dynamics during the exercise. However, all participants showed a clear PE fluctuating dynamics during the moderate and heavy intensity exercises performed in Experiment 1 and Experiment 2, respectively. Nevertheless, a transition towards a PE non-fluctuating dynamics (dominated by “PE increase” reports) was noticed in Experiment 2 while approaching volitional exhaustion.ConclusionsPE seems to have a dominant fluctuating dynamics during constant-power cycling performed under different conditions (duration, intensity, and termination) that changes towards a non-fluctuating dynamics when approaching the volitional exhaustion point.     

Optimal predictions in everyday cognition

Human perception and memory are often explained as optimal statistical inferences that are informed by accurate prior probabilities. In contrast, cognitive judgments are usually viewed as following error-prone heuristics that are insensitive to priors. We examined the optimality of human cognition in a more realistic context than typical laboratory studies, asking people to make predictions about the duration or extent of everyday phenomena such as human life spans and the box-office take of movies. Our results suggest that everyday cognitive judgments follow the same optimal statistical principles as perception and memory, and reveal a close correspondence between people's implicit probabilistic models and the statistics of the world.     

Theory-based Bayesian models of inductive learning and reasoning

Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction emphasize either the power of statistical learning, or the importance of strong constraints from structured domain knowledge, intuitive theories or schemas. We argue that both components are necessary to explain the nature, use and acquisition of human knowledge, and we introduce a theory-based Bayesian framework for modeling inductive learning and reasoning as statistical inferences over structured knowledge representations.     

Probabilistic models of cognition: conceptual foundations

Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, 'sophisticated' probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore how the approach relates to studies of explicit probabilistic reasoning, and give a brief overview of the field as it stands today.     

Pattern of psychological fitness as related to pattern of physical fitness among older adults

The purpose of the present study was to investigate psychological fitness as well as physical fitness among late middle-aged normal men and women before, during, and after a 12-wk. physical activity program. Heart-rate of each subject was measured on a graded treadmill four times, and four psychological measures were taken: self-esteem, body-image, trait-anxiety, and well-being. Improvement of fitness was gradual and significant for both sexes, whereas no effects of time or sex were found on the first three psychological measures. Significant differences in pattern of change between women and men on well-being confirm previous findings that women report more depression and less satisfaction than men and thus are more sensitive to change.