Semi-sparse PCA

It is well known that the classical exploratory factor analysis (EFA) of data with more observations than variables has several types of indeterminacy. We study the factor indeterminacy and show some new aspects of this problem by considering EFA as a specific data matrix decomposition. We adopt a new approach to the EFA estimation and achieve a new characterization of the factor indeterminacy problem. A new alternative model is proposed, which gives determinate factors and can be seen as a semi-sparse principal component analysis (PCA). An alternating algorithm is developed, where in each step a Procrustes problem is solved. It is demonstrated that the new model/algorithm can act as a specific sparse PCA and as a low-rank-plus-sparse matrix decomposition. Numerical examples with several large data sets illustrate the versatility of the new model, and the performance and behaviour of its algorithmic implementation.

     

Deriving ultrametric tree structures from proximity data confounded by differential stimulus familiarity

This paper presents a new procedure called TREEFAM for estimating ultrametric tree structures from proximity data confounded by differential stimulus familiarity. The objective of the proposed TREEFAM procedure is to quantitatively filter out the effects of stimulus unfamiliarity in the estimation of an ultrametric tree. A conditional, alternating maximum likelihood procedure is formulated to simultaneously estimate an ultrametric tree, under the unobserved condition of complete stimulus familiarity, and subject-specific parameters capturing the adjustments due to differential unfamiliarity. We demonstrate the performance of the TREEFAM procedure under a variety of alternative conditions via a modest Monte Carlo experimental study. An empirical application provides evidence that the TREEFAM outperforms traditional models that ignore the effects of unfamiliarity in terms of superior tree recovery and overall goodness-of-fit.     

Part perception in infancy: Sensitivity to the short-cut rule

Research indicates that object perception involves the decomposition of images into parts. A critical principle that governs part decomposition by adults is the short-cut rule, which states that, all else being equal, the visual system parses objects using the shortest possible cuts. We examined whether 6.5-month-olds’ parsing of images also follows the short-cut rule. Infants in the experimental conditions were habituated to cross shapes and then tested for their preference between segregated patterns produced using long cuts versus short cuts. Infants in the control conditions were directly tested with the segregated patterns. Infants in the experimental conditions exhibited a greater novelty preference for the long-cut over the short-cut patterns than did those in the control conditions, thereby indicating that they are more likely to segregate cross shapes using short cuts rather than long cuts. This sensitivity to the short-cut rule was evident when two alternative parameters, part area and protrusion, were controlled in Experiments 1 and 2, respectively. Thus, a critical principle that governs part segregation in adulthood is operational by 6.5 months of age.     

Morphological learning in a novel language: A cross-language comparison

Being able to extract and interpret the internal structure of complex word forms such as the English word dance+r+s is crucial for successful language learning. We examined whether the ability to extract morphological information during word learning is affected by the morphological features of one's native tongue. Spanish and Finnish adult participants performed a word–picture associative learning task in an artificial language where the target words included a suffix marking the gender of the corresponding animate object. The short exposure phase was followed by a word recognition task and a generalization task for the suffix. The participants' native tongues vary greatly in terms of morphological structure, leading to two opposing hypotheses. On the one hand, Spanish speakers may be more effective in identifying gender in a novel language because this feature is present in Spanish but not in Finnish. On the other hand, Finnish speakers may have an advantage as the abundance of bound morphemes in their language calls for continuous morphological decomposition. The results support the latter alternative, suggesting that lifelong experience on morphological decomposition provides an advantage in novel morphological learning.     

Neural correlates of morphological decomposition in a morphologically rich language: an fMRI study

By employing visual lexical decision and functional MRI, we studied the neural correlates of morphological decomposition in a highly inflected language (Finnish) where most inflected noun forms elicit a consistent processing cost during word recognition. This behavioral effect could reflect suffix stripping at the visual word form level and/or subsequent meaning integration at the semantic-syntactic level. The first alternative predicts increased activation for inflected vs. monomorphemic words in the left occipitotemporal cortex while the second alternative predicts left inferior frontal gyrus and/or left posterior temporal activation increases. The results show significant activation effects in the latter areas. This provides support for the second alternative, i.e., that the morphological processing cost stems from the semantic-syntactic level.     

Electropulsing-induced strengthening of steel at high temperature

Electropulsing usually promotes a metastable phase to evolve towards its equilibrium state. This work reports an alternative case, where electropulsing promotes the decomposition of the stable δ-phase in duplex stainless steel at high temperature. This decomposition enables both the γ-phase and the σ-phase in the steel to survive and hence to strengthen it at high temperature. The hardness of the quenched sample with electropulsing treatment is 49.4% higher than that without electropulsing treatment. A fundamental understanding of the observation is developed.     

Tree inference with factors selectively influencing processes in a processing tree

We show how to systematically construct a processing tree using data from an experiment in which two experimental factors are intended to selectively influence two different processes. Only two arrangements are possible for the two selectively influenced processes: ordered and unordered. We show that there are only two standard trees that need be considered, one for each arrangement. Necessary and sufficient conditions are given for each tree to be applicable. If the conditions do not hold, no tree is possible. If the selectively influenced processes are ordered, their order is sometimes determined by the data. We consider two factors that selectively influence two processes in every tree in a set of trees, such that on a given trial, a tree is selected from the set at random. We show that if the influenced processes are ordered in every tree or unordered in every tree, then the mixture of trees is equivalent to one of the two standard trees. To illustrate the method, a tree is constructed from simulated data from a model of Batchelder and Riefer [Batchelder, W.H., Riefer, D.M. (1980). Separation of storage and retrieval factors in free recall of clusterable pairs. Psychological Review, 87, 375–397].     

Partial information or facilitation? Different interpretations of results from speed-accuracy decomposition.

The speed-accuracy decomposition technique was developed by Meyer, Irwin, Osman, and Kounios (1988) to examine the time course of information processing. The technique allows for the estimation of the accuracy of guesses that are induced by the presentation of a response signal on a proportion of trials. Estimated guessing accuracy has been found to be above chance and to increase as time of guessing increases, suggesting that guesses are based on partial information that has accumulated prior to a response decision (sophisticated guesses). In this paper, a different interpretation of these data is presented. Results suggest that response signals may enhance the speed of regular processes, thereby violating the temporal-independence assumption that underlies the decomposition technique. As shown by Monte Carlo simulations, such facilitating effects of response signals can explain the results from the decomposition technique at least in part and possibly in full, even when guesses are actually at chance accuracy (pure guesses). The pure-guess model was supported by the results from an experiment designed to test between the alternative interpretations. These results point to the need for great caution in the attempt to infer the time course of information processing from guessing accuracies as estimated by the speed-accuracy decomposition technique.     

Partial information or facilitation? Different interpretations of results from speed-accuracy decomposition

The speed-accuracy decomposition technique was developed by Meyer, Irwin, Osman, and Kounios (1988) to examine the time course of information processing. The technique allows for the estimation of the accuracy of guesses that are induced by the presentation of a response signal on a proportion of trials. Estimated guessing accuracy has been found to be above chance and to increase as time of guessing increases, suggesting that guesses are based on partial information that has accumulated prior to a response decision (sophisticated guesses). In this paper, a different interpretation of these data is presented. Results suggest that response signals may enhance the speed of regular processes, thereby violating the temporal-independence assumption that underlies the decomposition technique. As shown by Monte Carlo simulations, such facilitating effects of response signals can explain the results from the decomposition technique at least in part and possibly in full, even when guesses are actually at chance accuracy (pure guesses). The pure-guess model was supported by the results from an experiment designed to test between the alternative interpretations. These results point to the need for great caution in the attempt to infer the time course of information processing from guessing accuracies as estimated by the speed-accuracy decomposition technique.     

The Importance of Modeling Method Effects: Resolving the (Uni)Dimensionality of the Loneliness Questionnaire

In this study, we tested whether children and young adults varied the size and color of their tree drawings based on hypotheses related to the emotional characterization of the drawn topic. We asked a sample of 80 5- to 11-year-old children and adults to draw a tree (baseline drawing) and then a happy versus sad tree from their imagination. Results indicate that size, but not color, is used to express emotion under free drawing conditions. We discuss implications for clinical psychologists and practitioners interpreting drawings of the tree.     

An availability bias in professional judgment

When branches of a fault tree are pruned, subjects do not fully transfer the probability of those branches to the ‘all other’ category. This underestimation of the catch-all probability has been interpreted as an ‘out of sight, out of mind’ form of the availability bias. The present work replicates this underestimation bias with professional managers. It then demonstrates the effectiveness of a corrective tactic, extending the tree by generating additional causes, and also reveals that more easily retrieved short-term causes dominate the generation process. These results do not differ across managers' culture, education or experience. After evaluating such alternative explanations as category redefinition, we conclude that availability is a major cause, though possibly not the sole cause, of the underestimation bias.     

Model selection for minimum‐diameter partitioning

The minimum‐diameter partitioning problem (MDPP) seeks to produce compact clusters, as measured by an overall goodness‐of‐fit measure known as the partition diameter, which represents the maximum dissimilarity between any two objects placed in the same cluster. Complete‐linkage hierarchical clustering is perhaps the best‐known heuristic method for the MDPP and has an extensive history of applications in psychological research. Unfortunately, this method has several inherent shortcomings that impede the model selection process, such as: (1) sensitivity to the input order of the objects, (2) failure to obtain a globally optimal minimum‐diameter partition when cutting the tree at K clusters, and (3) the propensity for a large number of alternative minimum‐diameter partitions for a given K. We propose that each of these problems can be addressed by applying an algorithm that finds all of the minimum‐diameter partitions for different values of K. Model selection is then facilitated by considering, for each value of K, the reduction in the partition diameter, the number of alternative optima, and the partition agreement among the alternative optima. Using five examples from the empirical literature, we show the practical value of the proposed process for facilitating model selection for the MDPP.     

A generalization of the representational change theory from insight to non-insight problems: the case of arithmetic word problems

This paper provides evidence for a possible generalization of Knoblich and colleagues’ representational change theory [Knoblich, G., Ohlsson, S., Haider, H., & Rhenius, D. (1999). Constraint relaxation and chunk decomposition in insight problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 1534-1555; Knoblich, G., Ohlsson, S., & Raney, G. E. (2001). An eye movement study of insight problem. Memory and Cognition, 29, 1000-1009] outside its original scope of application. While this theory has been proposed to explain insight problem solving, we demonstrate here that its main concepts, namely, constraint relaxation and chunk decomposition, are applicable to incremental problem solving. In a first experiment, we confirm, as already shown by problem solving and reasoning researchers, that individuals avoid the construction of alternative representations of the problems when possible. In the second and third experiments, we show that alternative representations of arithmetic problems are easier to construct and maintain when they violate constraints of narrow rather than wide scope. The specificity of insight problem solving is discussed in the light of these new findings.     

The Paradox of Abstraction: Precision Versus Concreteness

We introduce a novel measure of abstractness based on the amount of information of a concept computed from its position in a semantic taxonomy. We refer to this measure as precision. We propose two alternative ways to measure precision, one based on the path length from a concept to the root of the taxonomic tree, and another one based on the number of direct and indirect descendants. Since more information implies greater processing load, we hypothesize that nouns higher in precision will have a processing disadvantage in a lexical decision task. We contrast precision to concreteness, a common measure of abstractness based on the proportion of sensory-based information associated with a concept. Since concreteness facilitates cognitive processing, we predict that while both concreteness and precision are measures of abstractness, they will have opposite effects on performance. In two studies we found empirical support for our hypothesis. Precision and concreteness had opposite effects on latency and accuracy in a lexical decision task, and these opposite effects were observable while controlling for word length, word frequency, affective content and semantic diversity. Our results support the view that concepts organization includes amodal semantic structures which are independent of sensory information. They also suggest that we should distinguish between sensory-based and amount-of-information-based abstractness.     

Cognitive processes in implicit attitude tasks: An experimental validation of the Trip Model

Implicit attitude tasks have become very popular in various areas of psychology. However, little is known about the cognitive processes they involve. To address this issue, we investigated the underlying processes of the Go/No‐go Association Task (GNAT), a go/no‐go variant of the well‐known Implicit Association Test (IAT). More precisely, we tested two alternative multinomial processing tree (MPT) models of GNAT performance, the Trip Model and the generalized Quad Model. Both models assume that GNAT performance is influenced not only by automatic associations but also by response biases and a controlled discrimination process. However, the two models differ with respect to an additional overcoming bias process. In contrast to the Quad Model, the Trip Model assumes that overcoming bias does not play a major role in GNAT performance. Instead, the Trip Model emphasizes the role of response biases. We report three experiments that demonstrate the validity of the Trip Model for GNAT data. Copyright © 2010 John Wiley & Sons, Ltd.     

Manipulation of walnuts to facilitate opening by the great spotted woodpecker (Picoides major): is it tool use?

True tool use has been documented in some bird species, but to our knowledge, it has not been shown in woodpeckers. Here, we investigated the ability of Picoides major to open nuts of Juglans mandshurica by consistently inserting walnuts between tree branches in a specific position that facilitated nut opening. As seen in these birds, we showed that woodpeckers removed 96 % of the nuts of J. mandshurica from experimental seed trays and inserted each nut in a precise position that specifically allowed nut cracking. When we inserted nuts in an alternative position, woodpeckers manipulated and repositioned nuts to allow nut opening. In contrast, when we inserted the nuts in positions preferred for nut opening, woodpeckers did not alter their position and instead opened the nuts. We suggest that the origin of this behavior, as in other forms of tool use, likely requires a higher cognitive ability in these birds.     

On the Reality of Illusory Conjunctions

The reality of illusory conjunctions in perception has been sometimes questioned, arguing that they can be explained by other mechanisms. Most relevant experiments are based on migrations along the space dimension. But the low rate of illusory conjunctions along space can easily hide them among other types of errors. As migrations over time are a more frequent phenomenon, illusory conjunctions can be disentangled from other errors. We report an experiment in which series of colored letters were presented in several spatial locations, allowing for migrations over both space and time. The distribution of frequencies were fit by several multinomial tree models based on alternative hypothesis about illusory conjunctions and the potential sources of free-floating features. The best-fit model acknowledges that most illusory conjunctions are migrations in the time domain. Migrations in space are probably present, but the rate is very low. Other conjunction errors, as those produced by guessing or miscategorizations of the to-be-reported feature, are also present in the experiment. The main conclusion is that illusory conjunctions do exist.     

Processing of the Korean Eojoel Ambiguity

Korean writing is a syllabary where spaces occur between phrases rather than between words. This characteristic of Korean allows different types of information in Korean sentences to be dissociated in ways that are not possible in the languages that have been the focus of most psycholinguistic research, thereby providing new opportunities to investigate mechanisms of ambiguity resolution during sentence comprehension. In experiments using eye-tracking and self-paced reading, we examined how readers resolve the Eojoel ambiguity, where the grouping of syllables is ambiguous with respect to whether a phrase-final syllable is a case marker or a part of a word. This Eojoel ambiguity offers an opportunity to test how relative frequency of the lexical entries and complexity of morphological decomposition affect ambiguity resolution. Overall, the results of the experiments presented here showed that readers noticed and processed the Eojoel ambiguity very rapidly using information about the relative frequency of alternative interpretations, while the complexity of the morphological decomposition had little effect. These results are discussed in terms of constraint-based accounts (MacDonald et al. Psychol Rev 101:676–703, 1994) of ambiguity resolution.     

Bicriterion seriation methods for skew‐symmetric matrices

The decomposition of an asymmetric proximity matrix into its symmetric and skew‐symmetric components is a well‐known principle in combinatorial data analysis. The seriation of the skew‐symmetric component can emphasize information corresponding to the sign or absolute magnitude of the matrix elements, and the choice of objective criterion can have a profound impact on the ordering. In this research note, we propose a bicriterion approach for seriation of a skew‐symmetric matrix incorporating both sign and magnitude information. Two numerical demonstrations reveal that the bicriterion procedure is an effective alternative to direct seriation of the skew‐symmetric matrix, facilitating favourable trade‐offs among sign and magnitude information.