Nonlinear Dynamics Psychology and Life Sciences最新文献

In this paper, we take one of the most emblematic models of the economic orthodoxy, the representative agent optimal growth problem, and discuss the adaptations it needs to go through to be reflective of a virtual world of interacting agents. The rational agent that maximizes intertemporal utility is replaced by a profusion of heterogeneous households, who are endowed with distinct productivity and confidence levels, who interact locally, and who make consumption-savings decisions based on a boundedly rational rule (a heuristic). We show that the three highlighted features (heterogeneity, local interaction, and non-optimality) are intertwined, and that the transformation of the standard optimal growth problem into a complexity framework requires their simultaneous consideration. Heterogeneous productivity levels trigger different technology absorption capabilities and, as a consequence, a slow process of innovation diffusion; the consumption heuristic introduces flexibility into consumption-savings choices, allowing for the coexistence of those who save with those who consume their entire current income; random contact across a population of agents makes sentiments of optimism or pessimism to spread in unpredictable ways. These processes tend to reinforce one another, provoking a change of scenery, with the conventional equilibrium growth model giving place to a multi-agent decentralized interaction platform where emergent results, rather than mechanic outcomes, are the norm. Ultimately, the new theoretical framework preserves the fundamental concept of what an economic growth model should be, at the same time it offers a richer structure of analysis, allowing for a deeper debate on the dynamics of the aggregate economy.

Many real-world tasks require people to forecast chaotic events in order to take adaptive action. This ability is considered rare, and less understood than other cognitive processes. The present study examined how the performance dynamics in a chaotic forecasting task would be affected by stressors such as cognitive workload and fatigue using two cusp catastrophe models. Participants were 147 undergraduates who were shown graphs and brief chaotic number series for which they needed to forecast the next four values. Performance data were complemented by variables known to represent cognitive elasticity versus rigidity, compensatory abilities for fatigue, and NASA TLX ratings of subjective workload. R2 for the workload cusp was .56, which compared favorably to the next best linear alternative model (.12); it contained six bifurcation variables and three measures of workload (asymmetry). R2 for the fatigue cusp was .54, which also compared favorably to the next best linear alternative (.07); it contained one bifurcation variable and two compensatory abilities. The role of field independence as an elasticity variable in the workload model and as a compensatory ability in fatigue was particularly noteworthy. Several elasticity-rigidity variables have now been identified over a series of studies. They appear to be operating in unison to produce a bifurcation effect, and different variables become salient depending on the task. Future research should consider how the ability to forecast chaos and its susceptibility to workload and fatigue carry over to dynamical decisions made while managing a complex system. Key Words.

Reading is an emerging process from human brain activity. This process sometimes is subject to disorders which has been studied from the performance of studies that provide data that are treated with qualitative and quantitative linear tools to obtain the average behavior determined and the causality of it. This research focuses on the nonlinear quantitative study of reading disorder and in this way fractal geometry and roughness interface growth theory approach were selected to be used in the processing of brain wave quantification (EEG). From the EEG of children with and without reading disorders in the State of Mexico (experimental and control group) were built time series of standard deviation for each of the 19 channels distributed in cerebral cortex. The self-affinity of these time series (treated as interfaces in motion) is studied by the scaling behavior of their structure functions. It was found that the behavior of the time series of children with reading problems (experimental group) and without them (control group) is similar to the Family-Vicsek scaling dynamic for a kinetic roughening of moving interface.

Psychologists have had a long-standing interest in the connections between group processes and team performance. The biopsychosocial perspective has piqued an interest in the connection between team processes and performance and coordinated and synchronized physiological arousal levels among team members. Studies of synchronization in work teams have been stalled by the lack of a metric that captures the total synchronization within teams of three or more people. This study examined how synchronized physiological arousal does in fact connect to team performance and related group process outcomes by utilizing the SE coefficient developed by Guastello and Peressini. Forty-three groups of 3 to 8 participants (total N = 197) participated in a survival simulation. Synchroniza-tion coefficients were produced for three task segments: watching an orientation video together, an individual decision task, and a group decision task. Primary results showed: (a) Synchronization was greater in larger groups across the three task segments. (b) A combination of the three synchronization coefficients - higher during the team task and lower otherwise - was correlated with higher workload ratings for performance demands, greater team dissatisfaction, and lower demands for time-sharing between the individual and the team.

We consider a standard macroeconomic model of a small open economy in which the flow of capital on the international foreign exchange market crucially depends on the expected exchange rate. These expectations about the exchange rate are modelled to be either homogeneous or heterogeneous, i.e., all agents may form naive expectations, or they may switch between different simple linear extrapolative or regressive predictors with respect to changing market circumstances. Using a mixture of analytical and numerical tools, we attempt to describe the characteristics of our model's dynamical systems we obtain with these different assumptions and analyse the impact of exchange rate expectations on short-term business cycle fluctuations. Our results suggest that fluctuations in both national income and the exchange rate are crucially driven by speculators' expectations. With respect to these expectations, our numerical results additionally show an ambiguous effect of extrapolative expectations on stability. Due to coexisting attractors, an increase in the strength of extrapolative expectations may have both a destabilising and a stabilising impact on dynamics. I n contrast, regressive expectations have a stabilising effect on the business cycle.

This year's cover artists are members of a newly formed team of designers and scientists known as the Science and Design Laboratory, along with flooring manufacturing experts from the Mohawk Group. This unique collab-oration creates patterns for installation on the floors of versatile commercial, public and private spaces including airports, hospitals, offices and homes. Their goal is to create human-centered designs based on psychology experiments that investigate the positive impacts of viewing fractal patterns. These include reduced physiological stress levels, enhanced cognitive skills, and heightened concentration. Here, the fractal construction process and the resulting fractal characteristics of these designs are explained.

An inverted U-shaped pattern in heart rate (HR) and a U-shaped pattern in heart rate variability (HRV) are easily recognizable when individuals experience any acute stressor. How cardiac complexity (scaling and entropy) changes under acute stress is not well known. Psychologically, emotion regulation (ER) style is likely to influence the individual's specific behavioral response when affronting stress. This study tested whether adolescents with distinct ER styles would show different patterns of linear and nonlinear cardiac changes under stressful conditions. We predicted less autonomic flexibility for adolescents with a highly negative emotional regulation (HNER) style (n = 10) than for those adolescents with a highly positive emotional regulation (HPER) style (n=10). Further, associations between linear and nonlinear measures during each condition were examined for each group. Repeated measures ANOVAs revealed that HR and HRV changed according to the predicted pattern. Higuchi's fractal dimension and Sample Entropy followed a U-shaped pattern, whereas the short-term scaling exponent followed the reverse pattern. Cardiac changes across conditions were larger in the HPER group. Significant associations between linear and nonlinear measures were found in the HPER group but not in the HNER group. Results are cautiously discussed within a multiscale framework of fluctuations of the different cardiac features.

The study presents further development and application of generalized multiplicative models (GMultM) for assessing outcomes in psychotherapy. GMultM is a flexible nonlinear regression method which is able to predict the impact of subjects' psychological variables (common factors) as well as theirchanges on the outcomes of cognitive-behavioral therapy and rhythmic-movement therapy. The main objectives of our present study are (a) to construct GMultM with the aim to predict the impact of pre-treatment scores of subject'psychological variables (common factors) on the outcome of cognitive-behavioral therapy (CBT) for disordered eating behaviors and obesity; (b) to employ GMultM to model the change of Body Mass Index (BMI) in each participant (non18 responders to CBT treatment) individually after sessions of rhythmic movement therapy (RMT); (c) to demonstrate that GMultM is able to predict whether intervention-related changes in several psychological variables are mechanisms underlying BMI change in each individual subject participating in RMT intervention program. The processes of model construction, identification of parameters and validation procedure using data from CBT program are described. Sensitivity analysis of the developed model was provided. Results revealed that: (a) the GMultM not only predicts the outcomes of psychotherapy satisfactorily but also allows obtaining the partial response functions of psychological predictors of weight loss directly as a result of estimation of model's parameters; (b) GMultM predicts the changes in BMI after RMT intervention in each participant satisfactorily and thus can be applied as the individualized assessment tool for psychotherapy's outcome.

In social contexts of racket sports, the interactive behaviour between players in the same team is supported by visual coupling. Visual cues allow the players to dynamically coordinate their movements and maintain a suitable interpersonal distance, thereby decreasing the odds of missing score a point. The dynamic feature of this interpersonal coordination requiring reciprocal nonlinear behavioural adjustments to stabilize a relative position may be considered an interpersonal synergy. We used the Uncontrolled Manifold Hypothesis (UCM) methodology to test this hypothesis and capture interpersonal synergies in badminton doubles. The variability of the distance between players was utilized as a performance variable and the variability of player velocities were used as task-relevant elements. To our knowledge, this is the first study to identify interpersonal synergies in a cooperative task in badminton doubles at different moments within the same rally. Eight male badminton players were randomly assigned in four doubles with similar technical and tactical level. The participants performed 154 trials over two matches. Interpersonal synergies were found on approximately half of the trials examined. Moreover, the results reveal that shortest interpersonal distances create better conditions for the nonlinear adjustments required for interpersonal synergy formation in badminton doubles.

The development of new theories, mathematical methods and models for effective control of complex systems is one of the main problems for modern science. Biological systems are complex and hierarchically organized, with the behaviour of higher levels influencing the dynamics of the lower ones and vice versa. Hierarchical organization can be observed from subcellular to supercellular levels. When biological systems are far from their steady states, then nonlinear dependences take place, and a slight external impact can cause unexpected and unpredictable (chaotic, irregular) behaviour in these systems, resulting in fractal hierarchical structures. By examining tumours as strange (chaotic) attractors, we define in this article the hypothesis that the cause of their occurrence, development and spread (metastasis) is due to disorders in the hierarchical structure and integration of cell signalling pathways in tumour cells. An essential point in this article is the thesis (contrary to the view that the only causality in hierarchical systems is physical causality, i.e. there is no "top-down,' "holistic causality,' "intelligent causality,' etc.) that hierarchical systems are built on the principle of communication. Intelligent systems (in particular biological) that do not interact as mechanical objects, but on the basis of different meanings of biochemical signals obtained after their interpretation, participate in this communication.