Bouncing a ball: tuning into dynamic stability

Rhythmically bouncing a ball with a racket was investigated and modeled with a nonlinear map. Model analyses provided a variable defining a dynamically stable solution that obviates computationally expensive corrections. Three experiments evaluated whether dynamic stability is optimized and what perceptual support is necessary for stable behavior. Two hypotheses were tested: (a) Performance is stable if racket acceleration is negative at impact, and (b) variability is lowest at an impact acceleration between -4 and -1 m/s2. In Experiment 1 participants performed the task, eyes open or closed, bouncing a ball confined to a 1-dimensional trajectory. Experiment 2 eliminated constraints on racket and ball trajectory. Experiment 3 excluded visual or haptic information. Movements were performed with negative racket accelerations in the range of highest stability. Performance with eyes closed was more variable, leaving acceleration unaffected. With haptic information, performance was more stable than with visual information alone.     

Age-related differences in diffusion model boundary optimality with both trial-limited and time-limited tasks

In two-choice decision tasks, Starns and Ratcliff (Psychology and Aging 25: 377–390, 2010) showed that older adults are farther from the optimal speed–accuracy trade-off than young adults. They suggested that the age effect resulted from differences in task goals, with young participants focused on balancing speed and accuracy and older participants focused on minimizing errors. We compared speed–accuracy criteria with a standard procedure (blocks that had a fixed numbers of trials) to a condition in which blocks lasted a fixed amount of time and participants were instructed to get as many correct responses as possible within the time limit—a goal that explicitly required balancing speed and accuracy. Fits of the diffusion model showed that criteria differences persisted in the fixed-time condition, suggesting that age differences are not solely based on differences in task goals. Also, both groups produced more conservative criteria in difficult conditions when it would have been optimal to be more liberal.     

LGM模型中缺失数据处理方法的比较:ML方法与Diggle-Kenward选择模型

追踪研究中缺失数据十分常见。本文通过Monte Carlo模拟研究,考察基于不同前提假设的Diggle-Kenward选择模型和ML方法对增长参数估计精度的差异,并考虑样本量、缺失比例、目标变量分布形态以及不同缺失机制的影响。结果表明:(1)缺失机制对基于MAR的ML方法有较大的影响,在MNAR缺失机制下,基于MAR的ML方法对LGM模型中截距均值和斜率均值的估计不具有稳健性。(2)DiggleKenward选择模型更容易受到目标变量分布偏态程度的影响,样本量与偏态程度存在交互作用,样本量较大时,偏态程度的影响会减弱。而ML方法仅在MNAR机制下轻微受到偏态程度的影响。     

Reliability,stability, and relationships between infant and parent temperament

Reliability, stability, and relationships between infant and parent temperament were assessed using infant adaptations of 2 childhood temperament inventories. Both scales were moderately reliable, stability was moderate for the 4- to 18-month periods, and significant correlations were noted between mother and infant temperament ratings.     

The role of stability in the dynamics of learning, memorizing, and forgetting new coordination patterns

According to a dynamic theory of learning, how a new memory is formed depends on the stability of the nearest preexisting memories. To predict retention after practice, the authors analyzed how 15 participants memorized 2 bimanual coordination patterns (45 degrees or 135 degrees relative phase). The authors assessed (a) how participants memorized the required patterns with learning and (b) how the associated memory layout evolved. Results showed that a practiced 45 degrees pattern near a very stable memory (0 degrees ) persisted, whereas a 135 degrees pattern near a less stable memory (180 degrees ) was forgotten. Those findings corroborate the proposition that retention of coordination patterns depends on the stability of the extant motor memories. The authors discuss that proposal in terms of the coevolution of accuracy and stability with learning to predict persistence of required or false memories.     

Bouncing Back: How Salesperson Optimism and Self-Efficacy Influence Attributions and Behaviors Following Failure

Previous research reports a relationship between attributions and specific behaviors following a failed sales call. This study investigates the influence of individual differences on both the attribution process and the relationship between attribution and the behavioral intentions of sales representatives following a failure using a sample of financial services salespeople. This research reveals the important roles that optimism and self-efficacy play in shaping salespeople’s attributions for failed sales calls and in their behavioral responses to attributions for failure. Implications for managers and future research are discussed.     

Shared dynamics of attentional cost and pattern stability.

This paper examines the informational activity devoted by the CNS to couple oscillating limbs in order to sustain and stabilize bimanual coordination patterns. Through a double-task paradigm associating a bimanual coordination task and a reaction time (RT) task, we investigated the relation between the stability of preferred bimanual coordination patterns and the central cost expended by the CNS for their stabilization. Ten participants performed in-phase and anti-phase coordination patterns in a dual task condition (coordination + RT) at several frequencies (0.5, 0.75, 1.0, 1.5, and 2.0 Hz), thereby decreasing the stability of the bimanual patterns. Results showed a U-shaped evolution of pattern stability and attentional cost, as a function of oscillation frequency, exhibiting a minimum value at the same frequency. These findings indicate that central cost and pattern stability covary and may share common, high order dynamics. Moreover, the attentional focus given to the bimanual coordination and the RT task was also manipulated by requiring either shared attention or priority to the coordination task. Such a manipulation led to a tradeoff between pattern stability and RT performance: The more stable the pattern, the more costly it is to stabilize. This suggests that stabilizing a coordination pattern incurs a central cost that depends on its intrinsic stability. Conceptual consequences of these results for understanding the relationship between attention and coordination are drawn, and the mechanisms putatively at work in dual tasks are discussed.     

EMA: A process model of appraisal dynamics

A computational model of emotion must explain both the rapid dynamics of some emotional reactions as well as the slower responses that follow deliberation. This is often addressed by positing multiple levels of appraisal processes such as fast pattern directed vs. slower deliberative appraisals. In our view, this confuses appraisal with inference. Rather, we argue for a single and automatic appraisal process that operates over a person’s interpretation of their relationship to the environment. Dynamics arise from perceptual and inferential processes operating on this interpretation (including deliberative and reactive processes). This article discusses current developments in a computational model of emotion processes and illustrates how a single-level model of appraisal obviates a multi-level approach within the context of modeling a naturalistic emotional situation.     

Modelling non‐normal data: The relationship between the skew‐normal factor model and the quadratic factor model

Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality by means of a skew‐normally distributed factor model or a quadratic factor model. We show that the item distributions under a skew‐normal factor are equivalent to those under a quadratic model up to third‐order moments. The reverse only holds if the quadratic loadings are equal to each other and within certain bounds. We illustrate that observed data which follow any skew‐normal factor model can be so well approximated with the quadratic factor model that the models are empirically indistinguishable, and that the reverse does not hold in general. The choice between the two models to account for deviations of normality is illustrated by an empirical example from clinical psychology.     

On the relationship between the redundant signals effect and temporal order judgments: parametric data and a new model

Paradigms used to study the time course of the redundant signals effect (RSE; J. O. Miller, 1986) and temporal order judgments (TOJs) share many important similarities and address related questions concerning the time course of sensory processing. The author of this article proposes and tests a new aggregate diffusion-based model to quantitatively explain both the RSE and TOJs and the relationship between them. Parametric data (13 stimulus onset asynchronies) from an experiment with pairs of visual stimuli (626-nm LEDs) confirm that, relative to central signals (3 degrees), peripheral signals (35 degrees) yield slower reaction times, more strongly modulated RSE time-course functions, and flatter TOJ psychometric functions. All of these qualitative features are well captured, even in quantitative detail, by the aggregate diffusion model.     

A hybrid model using neural networks and ACT-R

How do people make decisions given contradictory information? This paper presents a model of how expert DSOs (defensive system operators) on a B1 bomber examine a complex series of signals, categorize whether those signals are dangerous or not, and then make a decision on the basis of those signals. This decision is made more difficult because an automatic on-board computer sometimes identifies the signal incorrectly. Therefore, the DSO must compare the actual signal to the system ID “guess.” The proposed model is a hybrid model, combining a standard neural network and ACT-R, a production system, which achieves a high degree of success.