The CHIC Model: A Global Model for Coupled Binary Data

Often problems result in the collection of coupled data, which consist of different N-way N-mode data blocks that have one or more modes in common. To reveal the structure underlying such data, an integrated modeling strategy, with a single set of parameters for the common mode(s), that is estimated based on the information in all data blocks, may be most appropriate. Such a strategy implies a global model, consisting of different N-way N-mode submodels, and a global loss function that is a (weighted) sum of the partial loss functions associated with the different submodels. In this paper, such a global model for an integrated analysis of a three-way three-mode binary data array and a two-way two-mode binary data matrix that have one mode in common is presented. A simulated annealing algorithm to estimate the model parameters is described and evaluated in a simulation study. An application of the model to real psychological data is discussed. T. Wilderjans is a Research Assistant of the Fund for Scientific Research—Flanders (Belgium). The research reported in this paper was partially supported by the Research Council of K.U. Leuven (GOA/2005/04). We are grateful to Kristof Vansteelandt for providing us with an interesting data set. We also thank three anonymous reviewers for their useful comments.     

Neural Representations of Nondeclarative Memories

ABSTRACT— Nondeclarative learning refers to abilities characterized by a lack of awareness of what has been learned and an independence from medial temporal lobe structures that support conscious memories of facts and events. Neuroimaging approaches have been used extensively in two domains of nondeclarative learning—priming and skill learning—to investigate the neural substrates supporting performance. Recent neuroimaging studies have attempted to understand what is being learned in different tasks in order to inform psychological theories of nondeclarative memory. For example, priming may be considered a form of perceptual learning or a form of stimulus–response learning, and correlations between performance and activation patterns in different regions may suggest the nature of the brain changes that support behavior. The attainment of expertise in a skill has been characterized as greater efficiency of processing in the same neural structures that support novice performance or, alternatively, as the recruitment of additional regions. Current research suggests that, within the domains of priming and skill learning, there is much heterogeneity in the underlying brain representations and psychological theories will need to account for these variations.     

双眼竞争研究现状与展望

双眼竞争是指当双眼所呈现的图像不一致而无法形成单一、稳定的知觉进而造成知觉动态交替变化的现象,其研究已有近200年的历史,至今仍是神经科学、心理学、生理学和临床医学中的研究热点。该文阐述了双眼竞争的概念、常用测量指标;总结了双眼竞争的特点及对双眼竞争的影响因素;讨论了双眼竞争与其他形式的多稳态知觉间的关系。行为实验、脑成像和电生理实验分别揭示了双眼竞争的早期加工模型和晚期加工模型的不足之处,Tong等人综合各方面的实验结果提出了双眼竞争的多层次–混合加工理论模型,这一模型将早期加工和晚期加工模型有机地结合起来,对于研究视觉意识的神经机制具有重要的理论指导意义。在总结已有研究的基础上,该文明确指出了双眼竞争的可应用领域及未来的研究方向     

视知觉学习的认知与神经机制研究

知觉学习是指由于训练或经验而引起的长期稳定的知觉变化,是一种内隐性的学习。近20年来,视知觉学习的大量研究结果提示大脑皮层的各个区域,甚至包括初级感觉皮层,在成熟之后仍然具有一定的可塑性。该文根据近年来的研究进展,对视知觉学习在大脑的什么地方,什么时候,以何种方式发生等热点问题进行了探讨。研究提示,视知觉学习涉及了包括初级视皮层在内的多个大脑皮层,并且存在一种自上而下的调控机制;视知觉学习可以在不同的时间尺度上发生,快速学习之后将伴随着慢速学习;通过视知觉学习,人们对于复杂物体的表征将从高级皮层区域移向低级皮层区域,任务执行也将趋于自动化     

EQUIVALENCE CLASS FORMATION: A METHOD FOR TEACHING STATISTICAL INTERACTIONS

Many students struggle with statistical concepts such as interaction. In an experimental group, participants took a paper‐and‐pencil test and then were given training to establish equivalent classes containing four different statistical interactions. All participants formed the equivalence classes and showed maintenance when probes contained novel negative exemplars. Thereafter, participants took a second paper‐and‐pencil test. Participants in the control group received two versions of the paper‐and‐pencil test without equivalence‐based instruction. All participants in the experimental group showed increased paper‐and‐pencil test scores after forming the interaction‐indicative equivalence classes. Class‐indicative responding also generalized to novel exemplars and the novel question format used in the paper‐and‐pencil test. Test scores did not change with repetition for control group participants. Implications for behavioral diagnostics and teaching technology are discussed.     

Morphological priming by itself: A study of Portuguese conjugations

Does the language processing system make use of abstract grammatical categories and representations that are not directly visible from the surface form of a linguistic expression? This study examines stem-formation processes and conjugation classes, a case of ‘pure’ morphology that provides insight into the role of grammatical structure in language processing. We report results from a cross-modal priming experiment examining 1st and 3rd conjugation verb forms in Portuguese. Although items were closely matched with respect to a range of non-morphological factors, distinct priming patterns were found for 1st and 3rd conjugation stems. We attribute the observed priming patterns to different representations of conjugational stems, combinatorial morphologically structured ones for 1st conjugation and unanalyzed morphologically unstructured ones for 3rd conjugation stems. Our findings underline the importance of morphology for language comprehension indicating that morphological analysis goes beyond the identification of grammatical morphemes.     

When Walking Makes Perception Better

ABSTRACT— When we move, the visual world moves toward us. That is, self-motion normally produces visual signals (flow) that tell us about our own motion. But these signals are distorted by our motion: Visual flow actually appears slower while we are moving than it does when we are stationary and our surroundings move past us. Although for many years these kinds of distortions have been interpreted as a suppression of flow to promote the perception of a stable world, current research has shown that these shifts in perceived visual speed may have an important function in measuring our own self-motion. Specifically, by slowing down the apparent rate of visual flow during self-motion, our visual system is able to perceive differences between actual and expected flow more precisely. This is useful in the control of action.     

The Local Minima Problem in Hierarchical Classes Analysis: An Evaluation of a Simulated Annealing Algorithm and Various Multistart Procedures

Hierarchical classes models are quasi-order retaining Boolean decomposition models for N-way N-mode binary data. To fit these models to data, rationally started alternating least squares (or, equivalently, alternating least absolute deviations) algorithms have been proposed. Extensive simulation studies showed that these algorithms succeed quite well in recovering the underlying truth but frequently end in a local minimum. In this paper we evaluate whether or not this local minimum problem can be mitigated by means of two common strategies for avoiding local minima in combinatorial data analysis: simulated annealing (SA) and use of a multistart procedure. In particular, we propose a generic SA algorithm for hierarchical classes analysis and three different types of random starts. The effectiveness of the SA algorithm and the random starts is evaluated by reanalyzing data sets of previous simulation studies. The reported results support the use of the proposed SA algorithm in combination with a random multistart procedure, regardless of the properties of the data set under study. Eva Ceulemans is a post-doctoral fellow of the Fund for Scientific Research Flanders (Belgium). Iwin Leenen is a post-doctoral researcher of the Spanish Ministerio de Educación y Ciencia (programa Ramón y Cajal). The research reported in this paper was partially supported by the Research Council of K.U. Leuven (GOA/05/04).     

Hierarchical Classes Modeling of Rating Data

Hierarchical classes (HICLAS) models constitute a distinct family of structural models for N-way N-mode data. All members of the family include N simultaneous and linked classifications of the elements of the N modes implied by the data; those classifications are organized in terms of hierarchical, if–then-type relations. Moreover, the models are accompanied by comprehensive, insightful graphical representations. Up to now, the hierarchical classes family has been limited to dichotomous or dichotomized data. In the present paper we propose a novel extension of the family to two-way two-mode rating data (HICLAS-R). The HICLAS-R model preserves the representation of simultaneous and linked classifications as well as of generalized if–then-type relations, and keeps being accompanied by a comprehensive graphical representation. It is shown to bear interesting relationships with classical real-valued two-way component analysis and with methods of optimal scaling. The research reported in this paper was supported by the Research Fund of the University of Leuven (GOA/00/02 and GOA/05/04) and by the Fund for Scientific Research-Flanders (project G.0146.06). Eva Ceulemans is a Post-doctoral Researcher supported by the Fund for Scientific Research, Flanders. The authors gratefully acknowledge the help of Gert Quintiens and Kaatje Bollaerts in collecting the data used in Section 4 and of Jan Schepers in additional analyses of these data.     

Representationalism and indeterminate perceptual content

Representationalists currently cannot explain counter-examples that involve indeterminate perceptual content, but a double content (DC) view is more promising. Four related cases of perceptual imprecision are used to outline the DC view, which also applies to imprecise photographic content. Next, inadequacies in the more standard single content (SC) view are demonstrated. The results are then generalized so as to apply to the content of any kinds of non-conventional representation. The paper continues with evidence that a DC account provides a moderate rather than extreme realist account of perception, and it concludes with an initial analysis of the failure of nomic covariance accounts of information in indeterminacy cases.