Sequencing and Optimization Within an Embodied Task Dynamic Model

A model of gestural sequencing in speech is proposed that aspires to producing biologically plausible fluent and efficient movement in generating an utterance. We have previously proposed a modification of the well‐known task dynamic implementation of articulatory phonology such that any given articulatory movement can be associated with a quantification of effort ( Simko & Cummins, 2010 ). To this we add a quantitative cost that decreases as speech gestures become more precise, and hence intelligible, and a third cost component that places a premium on the duration of an utterance. Together, these three cost elements allow us to derive algorithmically optimal sequences of gestures and dynamical parameters for generating articulator movement. We show that the optimized movement displays many timing characteristics that are representative of real speech movement, capturing subtle details of relative timing between gestures. Optimal movement sequences also display invariances in timing that suggest syllable‐level coordination for CV sequences. We explore the behavior of the model as prosodic context is manipulated in two dimensions: clarity of articulation and speech rate. Smooth, fluid, and efficient movements result.     

A Dynamical Approach to Gestural Patterning in Speech Production

In this article, we attempt to reconcile the linguistic hypothesis that speech involves an underlying sequencing of abstract, discrete, context-independent units, with the empirical observation of continuous, context-dependent interleaving of articulatory movements. To this end, we first review a previously proposed task-dynamic model for the coordination and control of the speech articulators. We then describe an extension of this model in which invariant speech units (gestural primitives) are identified with context-independent sets of parameters in a dynamical system having two functionally distinct but interacting levels. The intergestural level is defined according to a set of activation coordinates; the interarticulator level is defined according to both model articulator and tractvariable coordinates. In the framework of this extended model, coproduction effects in speech are described in terms of the blending dynamics defined among a set of temporally overlapping active units; the relative timing of speech gestures is formulated in terms of the serial dynamics that shape the temporal patterning of onsets and offsets in unit activations. Implications of this approach for certain phonological issues are discussed, and a range of relevant experimental data on speech and limb motor control is reviewed.     

Multitimescale dynamical interactions between speech rhythm and gesture

Temporal patterns in human movement, and in speech in particular, occur on multiple timescales. Regularities in such patterns have been observed between speech gestures, which are relatively quick movements of articulators (e.g., tongue fronting and lip protrusion), and also between rhythmic units (e.g., syllables and metrical feet), which occur more slowly. Previous work has shown that patterns in both domains can be usefully modeled with oscillatory dynamical systems. To investigate how rhythmic and gestural domains interact, an experiment was conducted in which speakers performed a phrase repetition task, and gestural kinematics were recorded using electromagnetic articulometry. Variance in relative timing of gestural movements was correlated with variance in rhythmic timing, indicating that gestural and rhythmic systems interact in the process of planning and producing speech. A model of rhythmic and gestural planning oscillators with multifrequency coupling is presented, which can simulate the observed covariability between rhythmic and gestural timing.     

Achievement goals and emotions in athletes: The mediating role of challenge and threat appraisals

Although the relationships between achievement goals and discrete emotions have been examined in a few studies, the process through which these relationships occur has received little attention. The present study investigated whether task and ego achievement goals were related to excitement, hope, and anxiety and whether these relationships were mediated by challenge and threat appraisals. We also examined whether the two achievement goals interact to predict emotions. Undergraduate students (N = 344) completed a multi-section questionnaire assessing achievement goals, challenge and threat appraisals, perceived competence, hope, excitement, concentration disruption, worry, and somatic anxiety before taking part in a team sport trial. Results showed that task goal was positively related to excitement and hope, and these relationships were mediated by challenge appraisal. In addition, threat appraisal mediated the relationship between task goal and concentration disruption. Ego goal was indirectly related to excitement through challenge appraisal. Finally, ego goal positively predicted concentration disruption at low but not high levels of task goal. Our findings suggest that achievement goals may influence emotions through cognitive appraisals and the interaction between task and ego goals needs to be considered in future research.     

A flexible latent trait model for response times in tests

Latent trait models for response times in tests have become popular recently. One challenge for response time modeling is the fact that the distribution of response times can differ considerably even in similar tests. In order to reduce the need for tailor-made models, a model is proposed that unifies two popular approaches to response time modeling: Proportional hazard models and the accelerated failure time model with log–normally distributed response times. This is accomplished by resorting to discrete time. The categorization of response time allows the formulation of a response time model within the framework of generalized linear models by using a flexible link function. Item parameters of the proposed model can be estimated with marginal maximum likelihood estimation. Applicability of the proposed approach is demonstrated with a simulation study and an empirical application. Additionally, means for the evaluation of model fit are suggested.     

Task specificity and the timing of discrete aiming movements

In discrete aiming movements the task criteria of time-minimization to a spatial target (e.g., Fitts, 1954) and time-matching to a spatial-temporal goal (e.g., Schmidt et al., 1979) tend to produce different functions of the speed-accuracy trade-off. Here we examined whether the task-related movement speed-accuracy characteristics were due to differential space-time trade-offs in time-matching, velocity-matching and time-minimizing task goals. Twenty participants performed 100 aiming trials for each of 15 combinations of task-type (3) and space-time condition (5). The prevalence of the primary types of sub-movement (none, pre-peak, post-peak, undershooting and overshooting) was determined from the kinematics of the movement trajectory. There were comparable distributions of trajectory sub-movement profiles and space-time movement outcomes across the three tasks at the short movement duration that became increasingly dissimilar over decreasing movement velocity and increasing movement time conditions. Movement time was the most influential variable in mediating sub-movement characteristics and the spatial/temporal outcome accuracy and variability of discrete aiming tasks – a role that was magnified in the explicit task demands of time-matching. The time-matching and time-minimization task goals in discrete aiming induce qualitatively different control processes that progressively contribute beyond the minimal time conditions to task-specific space-time accuracy and variability characteristics of the respective movement speed-accuracy functions.     

Timing, clocks, and dynamical systems.

Theoretical and experimental issues for our understanding of the timing of motor acts are reviewed, contrasting stochastic and dynamic timing models. It is argued that the theory of dynamical systems and, in particular, of limit cycle attractors, provides a unified framework within which these issues can be appreciated. The strength of stochastic timing models in the domain of absolute timing is contrasted with the strength of dynamic timing models in the domain of relative timing, the unification of the two domains being currently under way. It is further argued that accounts of timing must examine the interrelation between timing and other levels of processing involved in movement generation, in particular, the representation of spatial aspects of movement and the control of movement. The emergence of discrete event structure in timing skills is discussed from a dynamical systems perspective. Finally, the understanding of the timing structure of discrete movement is raised as a further challenge for future work.     

Information entropy analysis of discrete aiming movements

Information entropy and mutual information were investigated in discrete movement aiming tasks over a wide range of spatial (20-160 mm) and temporal (250-1250 ms) constraints. Information entropy was calculated using two distinct analyses: (1) with no assumption on the nature of the data distribution; and (2) assuming the data have a normal distribution. The two analyses showed different results in the estimate of entropy that also changed as a function of task goals, indicating that the movement trajectory data were not from a normal distribution. It was also found that the information entropy of the discrete aiming movements was lower than the task defined indices of difficulty (ID) that were selected for the congruence with Fitts' law. Mutual information between time points of the trajectory was strongly influenced by the average movement velocity and the acceleration/deceleration segments of the movement. The entropy analysis revealed structure to the variability of the movement trajectory and outcome that has been masked by the traditional distributional analyses of discrete aiming movements.     

A neurally plausible parallel distributed processing model of event-related potential word reading data

The Parallel Distributed Processing (PDP) framework has significant potential for producing models of cognitive tasks that approximate how the brain performs the same tasks. To date, however, there has been relatively little contact between PDP modeling and data from cognitive neuroscience. In an attempt to advance the relationship between explicit, computational models and physiological data collected during the performance of cognitive tasks, we developed a PDP model of visual word recognition which simulates key results from the ERP reading literature, while simultaneously being able to successfully perform lexical decision—a benchmark task for reading models. Simulations reveal that the model’s success depends on the implementation of several neurally plausible features in its architecture which are sufficiently domain-general to be relevant to cognitive modeling more generally.     

Challenge versus threat effects on the goal–performance relationship

This study tested the situational effects of goals and stress on the performance of complex tasks and on adaptation to change in the task. Difficult goals often exceed the individual's resources and thus create stress. However, stress may be appraised as either challenge or threat. Challenge is experienced when there is an opportunity for self-growth with available coping strategies, whereas threat is experienced when the situation is perceived as leading to failure with no available strategies to cope with it. We hypothesized that participants who appraised the situation as a challenge would perform better and adapt better to changes under difficult goal conditions, as compared with general goals or strategy goals. By contrast, threat appraisals would be better addressed by strategy goals rather than difficult goals. One hundred and fifty five students performed a task, which required their making predictions concerning the value of 120 companies' stocks based on three manipulated cues. We used a three by three by two factorial design in which goals, stress, and change (as a repeated factor) were varied to test the hypotheses. Results supported the main hypotheses and demonstrated that the same level of goal difficulty may lead to high or low performance and adaptation to change depending on the appraisal of the situation as challenging or threatening. The theoretical and practical implications of these findings are further discussed.     

Deliberate Control of Continuous Motor Performance

The authors examined the means by which people vary movement parameters to satisfy more than 1 constraint at a time in a repetitive motor task. The authors expected that when participants (N = 12) were simultaneously confronted with spatial and temporal constraints in an ellipse-drawing task, they would either exploit the intrinsic amplitude-frequency relationships or activate less natural control regimes to prioritize their movement goals. By focusing on local amplitude and frequency errors and parameter changes from 1 movement to the next, the authors distinguished parameter changes that reflected exploitation of biomechanics from those that required deliberate control. The findings demonstrated that at low movement speeds, participants can pursue multiple movement goals simultaneously; at higher speeds, their capacity to satisfy multiple task goals is reduced. The authors used a new method of inferring deliberate control from movement kinematics in the present study.     

体感交互人因学研究回顾与展望

人-机体感交互是个体使用肢体动作直接与机器进行的交互,是新近发展起来的自然交互方式。人因学研究是体感交互研究中的核心问题之一。笔者从体感交互的发展历史、已有体感交互方式、基于体感设备Kinect的人因学评估三个方面系统总结了体感交互的已有人因学研究,并对体感交互中存在的人因学问题与潜在研究方向做了论述。     

From a single-level analysis to a multilevel analysis of single-case experimental designs

Multilevel modeling provides one approach to synthesizing single-case experimental design data. In this study, we present the multilevel model (the two-level and the three-level models) for summarizing single-case results over cases, over studies, or both. In addition to the basic multilevel models, we elaborate on several plausible alternative models. We apply the proposed models to real datasets and investigate to what extent the estimated treatment effect is dependent on the modeling specifications and the underlying assumptions. By considering a range of plausible models and assumptions, researchers can determine the degree to which the effect estimates and conclusions are sensitive to the specific assumptions made. If the same conclusions are reached across a range of plausible assumptions, confidence in the conclusions can be enhanced. We advise researchers not to focus on one model but conduct multiple plausible multilevel analyses and investigate whether the results depend on the modeling options.     

Deliberate control of continuous motor performance

The authors examined the means by which people vary movement parameters to satisfy more than 1 constraint at a time in a repetitive motor task. The authors expected that when participants (N = 12) were simultaneously confronted with spatial and temporal constraints in an ellipse-drawing task, they would either exploit the intrinsic amplitude-frequency relationships or activate less natural control regimes to prioritize their movement goals. By focusing on local amplitude and frequency errors and parameter changes from 1 movement to the next, the authors distinguished parameter changes that reflected exploitation of biomechanics from those that required deliberate control. The findings demonstrated that at low movement speeds, participants can pursue multiple movement goals simultaneously; at higher speeds, their capacity to satisfy multiple task goals is reduced. The authors used a new method of inferring deliberate control from movement kinematics in the present study.     

Vocational choice: A decision making perspective

We propose a model of vocational choice that can be used for analyzing and guiding the decision processes underlying career and job choices. Our model is based on research in behavioral decision making (BDM), in particular the choice goals framework developed by Bettman, Luce, and Payne (1998). The basic model involves two major processes. First, the selection of a decision strategy according to four choice goals: maximizing decision accuracy, minimizing cognitive effort, minimizing negative emotion, and maximizing justifiability of the decision. Second, the construction of situation-specific preferences, which can reflect irrelevant task and context factors such as the evaluation mode. This basic model is extended to account for social influences and the long decision time typical of most career and job decisions. We review research on vocational choice in light of this model, discuss normative implications for counseling, and outline a research agenda for studying vocational choice from a behavioral decision making perspective.     

Consistent reproduction of movement sequences during acquisition of a pursuit tracking task

A pursuit tracking task is used as a vehicle to investigate the manner in which response consistency is affected by practice. Detailed examination of movement patterns shows that subjects can reproduce the mid-phase of a movement relatively consistently while the accelerative and decelerative phases of the movement remain highly variable. The findings are discussed with reference to Sparrow's 1983 concept of efficiency in conjunction with Norman and Shallice's 1980 model of automated action.     

The goal of locomotion: Separating the fundamental task from the mechanisms that accomplish it

Human locomotion has been well described but is still not well understood. This is largely true because the observable aspects of locomotion—neuromuscular activity that generates forces and motions—relate to both the task solution and the problem being solved. Identifying the fundamental task achieved in locomotion makes it possible to critically evaluate the motor control strategy used to accomplish the task goal. We contend that the readily observed movements and activities of locomotion should be considered mechanism(s). Our proposal is that the fundamental task of walking and running is analogous to flight, and should be defined in terms of the interaction of the individual’s mass with the medium in which it moves: a low-density fluid for flight, or the supporting substrate for legged locomotion. A rigorous definition of the fundamental task can help identify the constraints and opportunities that influence its solution and guide the selection of appropriate mechanisms to accomplish the task effectively. The results from robotics-based modeling studies have demonstrated how the interaction of the mass and substrate can be optimized, making the goal of movement a defined trajectory of the individual’s mass. We assessed these concepts by evaluating the ground reaction forces generated by an optimization model that satisfies the task but uses none of the mechanisms that are available to the human leg. Then we compared this model to normal human walking. Although it is obvious that the specific task of locomotion changes with a variety of movement challenges, clearly identifying the fundamental task of locomotion puts all other features in an interpretable context.     

Synthesis of asymmetric movement trajectories in timed rhythmic behaviour by means of frequency modulation

Results from different empirical investigations on gestural aspects of timed rhythmic movements indicate that the production of asymmetric movement trajectories is a feature that seems to be a common characteristic of various performances of repetitive rhythmic patterns. The behavioural or neural origin of these asymmetrical trajectories is, however, not identified. In the present study we outline a theoretical model that is capable of producing syntheses of asymmetric movement trajectories documented in empirical investigations by Balasubramaniam et al. (2004). Characteristic qualities of the extension/flexion profiles in the observed asymmetric trajectories are reproduced, and we conduct an experiment similar to Balasubramaniam et al. (2004) to show that the empirically documented movement trajectories and our modelled approximations share the same spectral components. The model is based on an application of frequency modulated movements, and a theoretical interpretation offered by the model is to view paced rhythmic movements as a result of an unpaced movement being “stretched” and “compressed”, caused by the presence of a metronome. We discuss our model construction within the framework of event-based and emergent timing, and argue that a change between these timing modes might be reflected by the strength of the modulation in our model.     

Multidimensional vector model of stimulus-response compatibility

The present study proposes and examines the multidimensional vector (MDV) model framework as a modeling schema for choice response times. MDV extends the Thurstonian model, as well as signal detection theory, to classification tasks by taking into account the influence of response properties on stimulus discrimination. It is capable of accounting for stimulus-response compatibility, which is known to be an influential task variable determining choice-reaction performance but has not been considered in previous mathematical modeling efforts. Specific MDV models were developed for 5 experiments using the Simon task, for which stimulus location is task irrelevant, to examine the validity of model assumptions and illustrate characteristic behaviors of model parameters. The MDV models accounted for the experimental data to a remarkable degree, demonstrating the adequacy of the framework as a general schema for modeling the latency of choice performance. Some modeling issues involved in the MDV model framework are discussed.     

Action relevance induces an attentional weighting of representations in visual working memory

Information maintained in visual working memory (VWM) can be strategically weighted according to its task-relevance. This is typically studied by presenting cues during the maintenance interval, but under natural conditions, the importance of certain aspects of our visual environment is mostly determined by intended actions. We investigated whether representations in VWM are also weighted with respect to their potential action relevance. In a combined memory and movement task, participants memorized a number of items and performed a pointing movement during the maintenance interval. The test item in the memory task was subsequently presented either at the movement goal or at another location. We found that performance was better for test items presented at a location that corresponded to the movement goal than for test items presented at action-irrelevant locations. This effect was sensitive to the number of maintained items, suggesting that preferential maintenance of action relevant information becomes particularly important when the demand on VWM is high. We argue that weighting according to action relevance is mediated by the deployment of spatial attention to action goals, with representations spatially corresponding to the action goal benefitting from this attentional engagement. Performance was also better at locations next to the action goal than at locations farther away, indicating an attentional gradient spreading out from the action goal. We conclude that our actions continue to influence visual processing at the mnemonic level, ensuring preferential maintenance of information that is relevant for current behavioral goals.