The fast and the slow of skilled bimanual rhythm production: parallel versus integrated timing

Professional pianists performed 2 bimanual rhythms at a wide range of different tempos. The polyrhythmic task required the combination of 2 isochronous sequences (3 against 4) between the hands; in the syncopated rhythm task successive keystrokes formed intervals of identical (isochronous) durations. At slower tempos, pianists relied on integrated timing control merging successive intervals between the hands into a common reference frame. A timer-motor model is proposed based on the concepts of rate fluctuation and the distinction between target specification and timekeeper execution processes as a quantitative account of performance at slow tempos. At rapid rates expert pianists used hand-independent, parallel timing control. In alternative to a model based on a single central clock, findings support a model of flexible control structures with multiple timekeepers that can work in parallel to accommodate specific task constraints.     

The Gesture as an Autonomous Nonlinear Dynamical System

ABSTRACT

We propose a theory of how the speech gesture determines change in a functionally relevant variable of vocal tract state (e.g., constriction degree). A core postulate of the theory is that the gesture determines how the variable evolves in time independent of any executive timekeeper. That is, the theory involves intrinsic timing of speech gestures. We compare the theory against others in which an executive timekeeper determines change in vocal tract state. Theories that employ an executive timekeeper have been proposed to correct for disparities between theoretically predicted and experimentally observed velocity profiles. Such theories of extrinsic timing make the gesture a nonautonomous dynamical system. For a nonautonomous dynamical system, the change in state depends not just on the state but also on time. We show that this nonautonomous extension makes surprisingly weak kinematic predictions both qualitatively and quantitatively. We propose instead that the gesture is a theoretically simpler nonlinear autonomous dynamical system. For the proposed nonlinear autonomous dynamical system, the change in state depends nonlinearly on the state and does not depend on time. This new theory provides formal expression to the notion of intrinsic timing. Furthermore, it predicts experimentally observed relations among kinematic variables.     

Le momentum psychologique en sport : vers une perspective complexe et dynamique

Psychological momentum (PM) is a social phenomenon that has triggered the curiosity of sport psychologists since the early 1980s. From early to recent conceptualizations, PM has been considered as a complex construct, inherently related to variations in sport performance. Over the past 30 years, several models have been proposed to untangle how PM is triggered, which psychological changes are involved in PM experiences, and how PM relates to performance. While linear (causal) models have dominated past research on PM, researchers have recently found that PM can change nonlinearly, depending on the performance history of the competition. This systematic review aims to provide an overview of different PM models that have been proposed in the past to increase insights into the complexity of PM, including the transition from linear causal models to nonlinear dynamical models. Moreover, based on the current state of affairs, perspectives for future research are provided.     

“I'd like to be that attractive,but at least I'm smart”: How exposure to ideal advertising models motivates improved decision‐making

The use of idealized advertising models has been heavily criticized in recent years. Existing research typically adopts a social comparison framework and shows that upward comparisons with models can lower self-esteem and affect, as well as produce maladaptive behavior. However, the alternative possibility that consumers can cope with threatening advertising models by excelling in other behavioral domains has not been examined. The present research draws on fluid compensation theory (Tesser, 2000) and shows that idealized models motivate improved performance in consumer domains that fall outside that of the original comparison. These more positive coping effects operate through self-discrepancies induced by idealized models, rather than self-esteem or negative affect. Specifically, self-discrepancies motivate consumers to improve decision-making by: 1) making more optimal choices from well-specified consideration sets, and 2) better self-regulating indulgent choices. More broadly, the current research integrates and extends theories of fluid compensation and self-discrepancy, as well as provides a more complete picture of the ways in which consumers cope with idealized advertising models.     

Relapse as a nonlinear dynamic system: application to patients with alcohol use disorders

Understanding the relapse process is one of the most important issues in addictive behaviors research. To date, most studies have taken a linear approach toward predicting relapse based on risk factors. Nonlinear dynamical systems theory can be used to describe processes that are not adequately modeled using a linear approach. In particular, the authors propose that catastrophe theory, a subset of nonlinear dynamical systems theory, can be used to describe the relapse process in addictive behaviors. Two small prospective studies using 6-month follow-ups of patients with alcohol use disorders (inpatient, n = 51; outpatient, n = 43) illustrate how cusp catastrophe theory may be used to predict relapse. Results from these preliminary studies indicate that a cusp catastrophe model has more predictive utility than traditional linear models.     

Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice

Most empirical models of choice in economics and consumer research assume that the decision maker assesses all alternatives and information in a perfect information-processing sense. The complexity of the choice environment, the ability of the individual to make complex decisions, and the effect of choice context on the decision strategy are generally not considered in statistical model development. One of the reasons for this omission is that theoretical literature on choice complexity and imperfect ability to choose that has developed in psychology and behavioral decision theory (BDT) literatures has not been translated into empirical econometric analysis. Second, the data used in economics and consumer research studies tend to be somewhat different from the data structures used in psychology and BDT literatures. In this paper we outline a theoretical model that simultaneously considers task complexity, effort applied by the consumer, ability to choose, and choice. We then construct a measure of task complexity and incorporate this in an analysis of a number of data series based on the random utility framework. We also examine the performance of our measure of task complexity in a composite data set that allows for increased variability in factors affecting decision context. Our approach provides a mechanism to link research in BDT and econometric modeling of consumer choice. Our findings suggest that task complexity does affect inferences about choice model parameters and that context effects, such as complexity, have a systematic impact on the parameters of econometric models of choice. The modeling approach provides a mechanism for inclusion of results from psychology and BDT in traditional economic models of consumer choice.     

Spatial Conceptions in Chinese and Canadian Children

Four-, five-, and six-year-old Chinese and Canadian boys and girls were presented a series of 11 graphic models and were asked to draw them. Supporting Piaget's theory, the data indicated that drawing performance on the topological dimension was better than the performance on the Euclidean dimension, and that there were neither gender nor cultural differences in performance. The research offers strong support for a main effect of biological or maturational factors as the foundation for the developmental influences in the acquisition of spatial conceptions.     

Spatial conceptions in Chinese and Canadian children

Four-, five-, and six-year-old Chinese and Canadian boys and girls were presented a series of 11 graphic models and were asked to draw them. Supporting Piaget's theory, the data indicated that drawing performance on the topological dimension was better than the performance on the Euclidean dimension, and that there were neither gender nor cultural differences in performance. The research offers strong support for a main effect of biological or maturational factors as the foundation for the developmental influences in the acquisition of spatial conceptions.     

Understanding Workaholism: Data Synthesis, Theoretical Critique, and Future Design Strategies

Workaholism involves a personal reluctance to disengage from work, which is evidenced by the tendency to work irrespective of external demands. While the term workaholism has been widely used by the public for over 30 years, scientists are only beginning to explore the behavior in depth. To date, most research has occurred on an ad hoc basis, emerging from a wide variety of paradigms without being explicitly linked to theory. The current article presents three methods for defining workaholism and a précis of relevant measures, then provides an integrated overview of research relating workaholism to individual well-being. Three models implicit in existing workaholism research (addiction, learning, and trait theory) are expounded and critiqued, and four new procedures for researching workaholism are suggested. Finally, an integrated, multidisciplinary approach is proposed as an essential element in encouraging rigorous debate and continued development of workaholism theory.     

The use of artificial neural networks and multiple linear regression in modelling work–health relationships: Translating theory into analytical practice

Although psychological theory acknowledges the existence of complex systems and the importance of nonlinear effects, linear statistical models have been traditionally used to examine relationships between environmental stimuli and outcomes. The way we analyse these relationships does not seem to reflect the way we conceptualize them. The present study investigated the application of connectionism (artificial neural networks) to modelling the relationships between work characteristics and employee health by comparing it with a more conventional statistical linear approach (multiple linear regression) on a sample of 1003 individuals in employment. Comparisons of performance metrics indicated differences in model fit, with neural networks to some extent outperforming the linear regression models, such that R ² for worn-out and job satisfaction were significantly higher in the neural networks. Most importantly, comparisons revealed that the predictors in the two approaches differed in their relative importance for predicting outcomes. The improvement is attributed to the ability of the neural networks to model complex nonlinear relationships. Being unconstrained by assumptions of linearity, they can provide a better approximation of such psychosocial phenomena. Nonlinear approaches are often better fitted for purpose, as they conform to the need for correspondence between theory, method, and data.     

Linearity of Personality–Performance Relationships: A large‐scale examination

This paper reviews theory and past research concerning nonlinear relationships between personality tests and job performance. We compare linear and nonlinear regression models for each of the 32 Occupational Personality Questionnaire (OPQ32i) scales using job performance as the criterion variable. We evaluate linear, quadratic, and cubic relationships between personality and job performance by calculating changes in R (ΔR) between the linear and nonlinear models. We use 3 decision rules of varying levels for ΔR and divide a large sample randomly into 2 samples to cross‐validate any nonlinear effects found. Few scales exhibited nonlinearity and the magnitude of the departures from linearity were small.     

A nonlinear mixed model framework for item response theory

Mixed models take the dependency between observations based on the same cluster into account by introducing 1 or more random effects. Common item response theory (IRT) models introduce latent person variables to model the dependence between responses of the same participant. Assuming a distribution for the latent variables, these IRT models are formally equivalent with nonlinear mixed models. It is shown how a variety of IRT models can be formulated as particular instances of nonlinear mixed models. The unifying framework offers the advantage that relations between different IRT models become explicit and that it is rather straightforward to see how existing IRT models can be adapted and extended. The approach is illustrated with a self-report study on anger.     

Timing in the motor programming of typing

In developing a theory of motor programming of skilled performance it has been suggested that an abstract, structural representation in the program specifies both a sequence of responses and expressive features of the sequence, such as timing, stress and intonation, which are mapped separately into the response output. In the case of typing, which does not require expressive features, it has previously been assumed that response timing is governed more simply by a timekeeper providing a stochastically regular beat. Two sets of specially constructed texts were given to a fast typist and the results support the idea that skilled typing is paced by a regular beat. They also show that there were systematic rhythmic departures from the beat, which arose from contingencies of keyboard movement but were not the simple consequences of these; rather they may be regarded as structured anticipations of the contingencies, and as such are analogous to the expressive features of speech and playing music.     

The topological approach to perceptual organization

To address the fundamental question of “what are the primitives of visual perception”, a theory of topological structure and functional hierarchy in visual perception has been proposed. This holds that the global nature of perceptual organization can be described in terms of topological invariants, global topological perception is prior to the perception of other featural properties, and the primitives of visual form perception are geometric invariants at different levels of structural stability. In Part I of this paper, I will illustrate why and how the topological approach to perceptual organization has been advanced. In Part II, I will provide empirical evidence supporting the early topological perception, while answering some commonly considered counteraccounts. In Part III, to complete the theory, I will apply the mathematics of tolerance spaces to describe global properties in discrete sets. In Part IV, I will further present experimental data to demonstrate the global-to-local functional hierarchy in form perception, which is stratified with respect to structural stability defined by Klein's Erlangen Program. Finally, in Part V, I will discuss relations of the global-to-local topological model to other theories: The topological approach reformulates both classical Gestalt holism and Gibson's direct perception of invariance, while providing a challenge to computational approaches to vision based on the local-to-global assumption.     

The effect of varying the number of response alternatives in rating scales: Experimental evidence from intra-individual effects

Despite a hundred years of questionnaire testing, no consensus has been reached on the optimal number of response alternatives in rating scales. Differences in prior research may have been due to the use of various psychometric models (classical test theory, item factor analysis, and item response theory) and different performance criteria (reliability, convergent/discriminant validity, and internal structure of the questionnaire). Furthermore, previous empirical studies on this issue have tackled the experimental design from a between-subjects perspective, thus ignoring intra-individual effects. In contrast with this approach, we propose a within-subjects experimental design and a comprehensive statistical methodology using structural equation models for studying all of these aspects simultaneously, therefore increasing statistical power. To illustrate the method, two personality questionnaires were examined using a repeated measures design. Results indicated that as the number of response alternatives increased, (1) internal consistency increased, (2) there was no effect on convergent validity, and (3) goodness of fit worsened. Finally, the article assesses the practical consequences of this research for the design of future personality questionnaires.     

Effects of learning and movement frequency on polyrhythmic tapping performance

This study examined the effect of learning a complex bimanual coordination task at different movement frequencies. 30 subjects performed 5:3 polyrhythmic tapping at either high, medium, or low movement frequency on a rhythmic synchronization task and then reproduced the polyrhythmic pattern repeatedly in the spontaneous task. Analysis showed that practice on the synchronization task qualitatively changed correct responses into anticipatory ones. The synchronization learning of the polyrhythm caused the anticipatory responses and so, may involve memorization of serial positions within the polyrhythm. Also, more anticipatory responses were indicated in performance at the medium and low frequencies than at the high frequency on the synchronization task. In addition, deviations of taps from expected tapping positions were observed in performance of the spontaneous task at the high frequency. These results suggest that the movement frequency qualitatively influenced the learning of this bimanual coordination. Especially at the high frequency, frequent shifts to other coordination patterns occurred on the spontaneous task. This means that the performance at higher frequency is more strongly affected by entrainment between the two hands.     

Revealed Indifference and Models of Choice Behavior

This paper introduces an approach to the study of rational choice behavior which is based on the concept of subjective indifference, as well as its relationships with both the classical preference-based approach and the choice behavior approach. With regard to the first relationship (which has already been studied in Alcantud, 2001, as a purely topological and order-theoretical problem) new considerations are now put forward in the decision theory context. In short, if a decisionmaker has some indifference classes defined on a choice set, then we know the conditions under which his/her tastes can be modeled by a continuous preference yielding these indifference classes. The second problem is posed and tackled here and gives place to a theory of revealed indifference, where both the decisive, and indecisive cases will be considered.     

Model Implied Instrumental Variables (MIIVs): An Alternative Orientation to Structural Equation Modeling

Few dispute that our models are approximations to reality. Yet when it comes to structural equation models (SEMs), we use estimators that assume true models (e.g. maximum likelihood) and that can create biased estimates when the model is inexact. This article presents an overview of the Model Implied Instrumental Variable (MIIV) approach to SEMs from Bollen (1996). The MIIV estimator using Two Stage Least Squares (2SLS), MIIV-2SLS, has greater robustness to structural misspecifications than system wide estimators. In addition, the MIIV-2SLS estimator is asymptotically distribution free. Furthermore, MIIV-2SLS has equation-based overidentification tests that can help pinpoint misspecifications. Beyond these features, the MIIV approach has other desirable qualities. MIIV methods apply to higher order factor analyses, categorical measures, growth curve models, dynamic factor analysis, and nonlinear latent variables. Finally, MIIV-2SLS permits researchers to estimate and test only the latent variable model or any other subset of equations. In addition, other MIIV estimators beyond 2SLS are available. Despite these promising features, research is needed to better understand its performance under a variety of conditions that represent empirical applications. Empirical and simulation examples in the article illustrate the MIIV orientation to SEMs and highlight an R package MIIVsem that implements MIIV-2SLS.     

Exploring Nonlinear Models in Personality Assessment: Development and Preliminary Validation of a Negative Emotionality Scale

ABSTRACT In this article we discuss the applicability of several new measurement models to the construction of personality scales, and we contrast these models with more traditional approaches in common usage, such as the principal factor analysis model. Our goal is to illustrate how nonlinear item-response models can be profitably used in personality research. We describe the development of a 30-item Negative Emotionality scale that was constructed using nonlinear factor analysis and item-response theory. We also show how traditional (linear) factor analysis can produce misleading results when it is applied to personality items with dichotomous response formats (e.g., true/false, agree/disagree). No formal training in modern measurement theory is assumed of the reader as we describe the nonlinear models that are used in this study in nontechnical language with a minimum of mathematics.