Testing the predictions of the central capacity sharing model

The divergent predictions of 2 models of dual-task performance are investigated. The central bottleneck and central capacity sharing models argue that a central stage of information processing is capacity limited, whereas stages before and after are capacity free. The models disagree about the nature of this central capacity limitation. The central bottleneck model claims that central processing acts on only 1 task at a time and, therefore, constitutes a bottleneck that processes tasks serially. The central capacity sharing model postulates that the central stage is a limited-capacity parallel processor that divides resources among to-be-performed tasks. As a result of this difference, in the psychological refractory period paradigm, the central capacity sharing model predicts that lengthening Task 2 precentral processing will improve Task 1 performance at short stimulus onset asynchronies, whereas the central bottleneck model does not. Results of 2 experiments confirm the prediction of the central capacity sharing model.     

Generalized bilinear models

Generalized bilinear models are presented for the statistical analysis of two-way arrays. These models combine bilinear models and generalized linear modeling, and yield a family of models that includes many existing models, as well as suggest other potentially useful ones. This approach both unifies and extends models for two-way arrays, including the ability to treat response and explanatory variables differently in the models, and the incorporation of external information about the variables directly into the analysis. A unifying framework for the generalized bilinear models is provided by considering four particular cases which have been proposed and used in the existing statistical literature. A three-step procedure is proposed to analyze data sets by generalized bilinear models. Two data sets of different nature are analyzed.     

Mathematical models and the experimental analysis of behavior

The use of mathematical models in the experimental analysis of behavior has increased over the years, and they offer several advantages. Mathematical models require theorists to be precise and unambiguous, often allowing comparisons of competing theories that sound similar when stated in words. Sometimes different mathematical models may make equally accurate predictions for a large body of data. In such cases, it is important to find and investigate situations for which the competing models make different predictions because, unless two models are actually mathematically equivalent, they are based on different assumptions about the psychological processes that underlie an observed behavior. Mathematical models developed in basic behavioral research have been used to predict and control behavior in applied settings, and they have guided research in other areas of psychology. A good mathematical model can provide a common framework for understanding what might otherwise appear to be diverse and unrelated behavioral phenomena. Because psychologists vary in their quantitative skills and in their tolerance for mathematical equations, it is important for those who develop mathematical models of behavior to find ways (such as verbal analogies, pictorial representations, or concrete examples) to communicate the key premises of their models to nonspecialists.     

Keeping quiet on the ontology of models

Stein once urged us not to confuse the means of representation with that which is being represented. Yet that is precisely what philosophers of science appear to have done at the meta-level when it comes to representing the practice of science. Proponents of the so-called ‘syntactic’ view identify theories as logically closed sets of sentences or propositions and models as idealised interpretations, or ‘theoruncula, as Braithwaite called them. Adherents of the ‘semantic’ approach, on the other hand, are typically characterised as taking them to be families of models that are set-theoretic, according to Suppes and others, or abstract, as Giere has argued. da Costa and French (Science and Partial Truth. OUP, Oxford, 2003) suggested that we should refrain from ontological speculation as to the nature of scientific theories and models and focus on their appropriate representation for various purposes within the philosophy of science. Such an approach allows both linguistic and non-linguistic resources to play their appropriate role (see also French and Saatsi, Philosophy of Science, Proceedings of the 2004 PSA Meeting, 78:548–559, 2006) and can be supported by recent case studies illustrating the heterogeneity of scientific practice. My aim in this paper is to further develop this ‘quietist’ view, and to indicate how it offers a fruitful way forward for the philosophy of science.     

Response style analysis with threshold and multi‐process IRT models: A review and tutorial

Two different item response theory model frameworks have been proposed for the assessment and control of response styles in rating data. According to one framework, response styles can be assessed by analysing threshold parameters in Rasch models for ordinal data and in mixture‐distribution extensions of such models. A different framework is provided by multi‐process item response tree models, which can be used to disentangle response processes that are related to the substantive traits and response tendencies elicited by the response scale. In this tutorial, the two approaches are reviewed, illustrated with an empirical data set of the two‐dimensional ‘Personal Need for Structure’ construct, and compared in terms of multiple criteria. Mplus is used as a software framework for (mixed) polytomous Rasch models and item response tree models as well as for demonstrating how parsimonious model variants can be specified to test assumptions on the structure of response styles and attitude strength. Although both frameworks are shown to account for response styles, they differ on the quantitative criteria of model selection, practical aspects of model estimation, and conceptual issues of representing response styles as continuous and multidimensional sources of individual differences in psychological assessment.     

Non-abstractive global-matching models: A framework for investigating the distinctiveness effect on explicit and implicit memory

One very well-known memory phenomenon is the observation that if a specific item seems to be different or rare in any way from other items present in the same encoding context, this item is likely to be remembered more accurately. This phenomenon, named the von Restorff effect or the isolation effect, has been known since 1933 and been considered today as one of the possible ways to create distinctiveness. The aim of this article is to report that the current debate concerning its non-emergence in implicit memory tasks is directly due to a theoretical disagreement about the nature of human memory. In this paper, we conclude that non-abstractive global-matching models can provide an effective theoretical framework for the study of the distinctiveness effect with isolation both in implicit and explicit memory tasks.     

The role of input and output modality pairings in dual-task performance: evidence for content-dependent central interference

Recent debate regarding dual-task performance has focused on whether costs result from limitations in central capacity, and whether central operations can be performed in parallel. While these questions are controversial, the dominant models of dual-task performance share the assumption that central operations are generic--that is, their interactions are independent of stimulus and response modalities. To examine these issues, we conducted a series of dual-task experiments with different input and output modality pairings. One condition combined a visual-manual task with an auditory-vocal task, and the other condition reversed the input-output pairings, combining a visual-vocal task with an auditory-manual task. Input/output modality pairings proved to be a key factor; throughout practice, dual-task costs were generally more than twice as large with visual-vocal/auditory-manual tasks than with the opposite arrangement of modalities (Experiments 1 and 2). These differences could be explained neither by competition for peripheral resources nor by differences in single-task response times (Experiment 3). Moreover, the persistent dual-task costs did not appear to stem from a central bottleneck. Contrary to the dominant models of dual-task performance, we propose that central interference between tasks depends not just on the duration of central operations, nor just strategic adaptation, but also on the content of those operations. Implications for structural and strategic accounts of dual-task interference are discussed.     

Ability, breadth, and parsimony in computational models of higher-order cognition

Computational models will play an important role in our understanding of human higher‐order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher‐order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do; (b) the breadth of situations in which it can do so; and (c) the parsimony of the mechanisms it posits. This article argues that fits of models to quantitative experimental data, although valuable for other reasons, do not address these criteria. Further, using analogies with other sciences, the history of cognitive science, and examples from modern‐day research programs, this article identifies five activities that have been demonstrated to play an important role in our understanding of human higher‐order cognition. These include modeling within a cognitive architecture, conducting artificial intelligence research, measuring and expanding a model's ability, finding mappings between the structure of different domains, and attempting to explain multiple phenomena within a single model.     

A test of Bayesian observer models of processing in the Eriksen flanker task

Two Bayesian observer models were recently proposed to account for data from the Eriksen flanker task, in which flanking items interfere with processing of a central target. One model assumes that interference stems from a perceptual bias to process nearby items as if they are compatible, and the other assumes that the interference is due to spatial uncertainty in the visual system (Yu, Dayan, & Cohen, 2009). Both models were shown to produce one aspect of the empirical data, the below-chance dip in accuracy for fast responses to incongruent trials. However, the models had not been fit to the full set of behavioral data from the flanker task, nor had they been contrasted with other models. The present study demonstrates that neither model can account for the behavioral data as well as a comparison spotlight-diffusion model. Both observer models missed key aspects of the data, challenging the validity of their underlying mechanisms. Analysis of a new hybrid model showed that the shortcomings of the observer models stem from their assumptions about visual processing, not the use of a Bayesian decision process.     

Face-specific capacity limits under perceptual load do not depend on holistic processing

Previous observations that face recognition may proceed automatically, without drawing on attentional resources, have been challenged by recent demonstrations that only a few faces can be processed at one time. However, a question remains about the nature of the stimulus properties that underlie face-specific capacity limits. Two experiments showed that speeded categorization of a famous face (such as a politician or pop star) is facilitated when it is congruent with a peripheral distractor face. This congruency effect is eliminated if the visual search is loaded with more than one face, unlike previous demonstrations of speeded classification using semantic information. Importantly, congruency effects are also eliminated when the search task is loaded with nontarget faces that are shown in an inverted orientation. These results indicate that face-specific capacity limits are not determined by the configural (“holistic”) properties of face recognition.     

Characterizing attentional resources

Other studies have found that it is easier to divide attention when messages can be discriminated on the basis of stimulus and response features. The present study extended these results and explored whether dual-task performance is a function of similarity of central processing and, more specifically, the semantic similarity of the competing messages. In a dichotic listening task, subjects detected targets in concurrent messages that either differed semantically and required different central processing (the mixed condition) or were semantically similar and required similar central processing (the same condition). Three criteria are developed to determine whether the tasks in the mixed condition call upon distinct resources. The results are discussed in terms of three metaphors for resources: fuel, structure, and skills.     

Mental models in the brain: On context-dependent neural correlates of mental models

In this paper, the concept of context-dependent realisation of mental models is introduced and discussed. Literature from neuroscience is discussed showing that different types of mental models can use different types of brain areas. Moreover, it is discussed that the same occurs for the formation and adaptation of mental models and the control of these processes. This makes that it is hard to claim that all mental models use the same brain mechanisms and areas. Instead, the notion of context-dependent realisation is proposed here as a better manner to relate neural correlates to mental models. It is shown in some formal detail how this context-dependent realisation approach can be related to well-known perspectives based on bridge principle realisation and interpretation mapping realisation.     

Short-term memory models for choice behavior

In this paper we consider the effect of imposing memory restrictions on the accumulator and random-walk models of choice behavior outlined by Audley (Psychological Review, 1960, 67, 1–15). Specifically, it is assumed that subjects apply criteria to the numbers of impulses received, and that if the criteria are not satisfied by the time w impulses have been received, then thereafter the criteria are only applied to w impulses, which could, for example, be the last w impulses received. Exact and approximate mathematical approaches and simulation techniques are presented in detail. The results obtained demonstrate that both the restricted accumulator and the restricted random-walk models can make qualitative predictions in line with much recent data.     

Minimax d-optimal designs for item response theory models

Various different item response theory (IRT) models can be used in educational and psychological measurement to analyze test data. One of the major drawbacks of these models is that efficient parameter estimation can only be achieved with very large data sets. Therefore, it is often worthwhile to search for designs of the test data that in some way will optimize the parameter estimates. The results from the statistical theory on optimal design can be applied for efficient estimation of the parameters.A major problem in finding an optimal design for IRT models is that the designs are only optimal for a given set of parameters, that is, they are locally optimal. Locally optimal designs can be constructed with a sequential design procedure. In this paper minimax designs are proposed for IRT models to overcome the problem of local optimality. Minimax designs are compared to sequentially constructed designs for the two parameter logistic model and the results show that minimax design can be nearly as efficient as sequentially constructed designs.     

Metamodeling Knowledge: Developing Students' Understanding of Scientific Modeling

We argue that learning about the nature and utility of scientific models and engaging in the process of creating and testing models should be a central focus of science education. To realize this vision, we created and evaluated the Model-Enhanced ThinkerTools (METT) Curriculum, which is an inquiry-oriented physics curriculum for middle school students in which they learn about the nature of scientific models and engage in the process of modeling. Key components of our approach include enabling students to create computer models that express their own theories of force and motion, evaluate their models using criteria such as accuracy and plausibility, and engage in discussions about models and the process of modeling. Curricular trials in four science classes of an urban middle school indicate that this approach can facilitate a significant improvement in students' understanding of modeling. Further analyses revealed that the approach was particularly successful in clarifying and broadening students' understanding of the nature and purpose of models. The METT Curriculum also led to significant improvements in inquiry skills and physics knowledge. Comparisons of METT students' performance with that of prior ThinkerTools students suggest that the acquisition of metamodeling knowledge contributed to these gains. In particular, METT students wrote significantly better conclusions on the inquiry test and performed better on some of the far-transfer problems on the physics test. Finally, correlational results, including significant correlations of pretest modeling and inquiry scores with posttest physics scores, suggests that developing knowledge of modeling and inquiry transfers to the learning of science content within such a curriculum. Taken together, the findings suggest that an emphasis on model-based inquiry, accompanied by the development of metamodeling knowledge, can facilitate learning science content while also developing students' understanding of the scientific enterprise.     

Using models to correct data: paleodiversity and the fossil record

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of its epistemic reliability. Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate (or inadequate) for particular purposes.

     

The Implications of Prospect Theory for Human Nature and Values

Central to prospect theory are far-reaching claims about what people fear and what gratifies them. Subjective well-being is a topic that social science has been reluctant to discuss in recent years, but it is central to much of our lives. A loss inflicts more harm than a comparable gain produces pleasure; this fact and the related endowment effect are important parts of our psychological makeup. The importance of change rather than absolute value position, and the related significance of the reference point and how it can be altered, can be seen as integral to human nature.     

Interpretation and method

Abstract

Interpretation started as the central tool of psychoanalytic theory, but it has undergone changes, just as the theory it was based on has evolved. Not only have these significant changes been determined by cultural trends, but different authors have also contributed to their evolution through their approaches to various other pathologies besides neurosis. Today, the cure process is divided between those who believe that therapeutic efficiency should be based on the different interpretation models, and those who maintain that it can be only sustained by the modifying capacity of the therapeutic relationship. Both positions are supposedly upheld by the results of tests that both models believe are sufficient proof but that, in the current author's opinion, lead back to the type of pathology they arose from, although they may at times attempt to cover the entire theoretical spectrum. The position upheld by Gedo—who considers that the psychoanalyst's intervention will depend on the degree of evolution that the pathology has achieved—is of great interest for specific practice. Hence, the more primitive levels require a treatment founded on holding, whereas more evolved pathologies require a more classic level of interpretation. This implies that the stages of a particular patient's evolution may require interventions at different levels, even though these may be founded on different theoretical models. This model, which we may brand as eclectic, is basically the one we find underpinning different theoretical models, which effectively appear to integrate others.     

Getting from neuron to checkmark: models and methods in cognitive survey research

Since the 1980s much work has been done in the field of Cognitive Survey Research. In an interdisciplinary endeavour, survey methodologists and cognitive psychologists (as well as social psychologists and linguists) have worked to unravel the cognitive processes underlying survey responses: to improve survey measurement, but also to obtain fundamental insight into the process of question answering, the nature of attitudes, the functioning of human memory, etc. Yet, despite the amount of work that has been done, less progress has been made than was deemed possible. This paper suggests ways in which to develop cognitive theories that may help to obtain an integrated understanding of question answering in surveys. One way to build better theories is to focus on model construction. Different types of cognitive models are discussed that can be used to model question answering. Second, a larger variety of methods from the cognitive toolbox can be used to further develop and test these models. An overview is given of the various tools available to researchers of cognitive aspects of survey research, with a special focus on newer methods from cognitive neuroscience. To connect different tools and methods into an integrative theory of question answering, the idea of hierarchical modelling is proposed. Copyright © 2007 John Wiley & Sons, Ltd.     

Musings about beauty

In this essay, I explore how cognitive science could illuminate the concept of beauty. Two results from the extensive literature on aesthetics guide my discussion. As the term “beauty” is overextended in general usage, I choose as my starting point the notion of “perfect form.” Aesthetic theorists are in reasonable agreement about the criteria for perfect form. What do these criteria imply for mental representations that are experienced as beautiful? Complexity theory can be used to specify constraints on mental representations abstractly formulated as vectors in a high‐dimensional space. A central feature of the proposed model is that perfect form depends both on features of the objects or events perceived and on the nature of the encoding strategies or model of the observer. A simple example illustrates the proposed calculations. A number of interesting implications that arise as a consequence of reformulating beauty in this way are noted.