Grounding Bayesian accounts of numerosity and variability effects in a similarity-based framework: the case of self-organising maps

ABSTRACT

In this paper, we propose self-organising maps as possible candidates to explain the psychological mechanisms underlying category generalisation. Self-organising maps are psychologically and biologically plausible neural network models that can learn after limited exposure to positive category examples, without any need of contrastive information. They reproduce human behaviour in category generalisation, in particular, the Numerosity and Variability effects, which are usually explained with Bayesian tools. Where category generalisation is concerned, self-organising maps deserve attention to bridge the gap between the computational level of analysis in Marr's hierarchy (where Bayesian models are often situated) and the algorithmic level of analysis in which plausible mechanisms are described.     

The role of body image in the prevention of eating disorders

This article reviews theory and research pertaining to prevention of negative body image and eating disorders. Research derived from the social cognitive model (SCM) and non-specific vulnerability-stressor (NSVS) model indicates that sustained prevention effects for attitudes and behaviors are possible, but not easy to achieve or explain. These limitations are considered in the context of promising research derived from a third model, critical social perspectives (CSP). We conclude that (1) research on practice should aim beyond the examination of efficacy in order to clarify the active ingredients contributing to prevention; and (2) research informed by each of the divergent perspectives can be used to enrich theory and practice in the field of eating disorders prevention.     

A study of Mind Image Drawings

This report dealt with a newly introduced method of drawing named, “Mind Image Drawings.” First, the subjects depicted images in their mind freely. Second, the subjects described their own pictures using three epithets. Third, the subjects added “I am” to these words, and read them aloud. Through these techniques, the subjects not only projected the unconscious side of their mind in the drawings, but also could obtain insight into their mind on the cognitive level. Last, the subjects judged their drawings using 17 semantic differential scales. The “originality factor,” the “evaluation factor,” and several types of “expressiveness factors” were extracted in the factor analyses of the scales.     

Heterogeneous factor analysis models: A bayesian approach

Multilevel factor analysis models are widely used in the social sciences to account for heterogeneity in mean structures. In this paper we extend previous work on multilevel models to account for general forms of heterogeneity in confirmatory factor analysis models. We specify various models of mean and covariance heterogeneity in confirmatory factor analysis and develop Markov Chain Monte Carlo (MCMC) procedures to perform Bayesian inference, model checking, and model comparison.We test our methodology using synthetic data and data from a consumption emotion study. The results from synthetic data show that our Bayesian model perform well in recovering the true parameters and selecting the appropriate model. More importantly, the results clearly illustrate the consequences of ignoring heterogeneity. Specifically, we find that ignoring heterogeneity can lead to sign reversals of the factor covariances, inflation of factor variances and underappreciation of uncertainty in parameter estimates. The results from the emotion study show that subjects vary both in means and covariances. Thus traditional psychometric methods cannot fully capture the heterogeneity in our data.     

Confirming the Factor Structure of Attention Deficit Hyperactivity Disorder Symptoms in Adult, Nonclinical Samples

Three separate models have been proposed to describe the factor structure of attention deficit hyperactivity disorder (ADHD) in the past 20 years. The Diagnostic and Statistical Manual of Mental Disorders-III (DSM-III, 1980) proposed 3 separate factors of inattention, hyperactivity, and impulsivity. The DSM-III-R (1987) proposed a single factor. The DSM-IV (1994) described the disorder as having 2 factors: hyperactivity/impulsivity and inattention. The following 2 studies employed confirmatory factor analysis to compare each of these models and 3 alternative models. University students completed questionnaires that assessed each of the 18 symptoms listed in the DSM-IV for ADHD. The 3-factor model fit the data significantly better than each of the other models in both studies. These findings suggest that a 3-factor model of inattention, hyperactivity, and impulsivity describes adult ADHD symptoms better than current alternatives.     

儿童早期数学认知能力的结构及其特点

从北京市10所幼儿园中选取234名3、4岁的儿童为被试,采用个别测查的方法对儿童早期数学认知能力的结构及其特点进行了考察。经验证性因素分析发现：(1)儿童早期数学认知能力的结构模型是合理的,可接受的,具有较好的构想效度,具体讲,数、计算、测量、空间／几何和模式认知能力五个维度共同解释着儿童早期的数学认知能力;(2)不同年龄儿童早期数学认知能力的结构具有稳定性,但是结构模型并不完全一致,某些项目的解释率有所不同;(3)男、女儿童早期数学认知能力的结构模型具有一致性。     

The First-Order Theories of Dedekind Algebras

A Dedekind Algebra is an ordered pair (B,h) where B is a non-empty set and h is an injective unary function on B. Each Dedekind algebra can be decomposed into a family of disjoint, countable subalgebras called configurations of the Dedekind algebra. There are N₀ isomorphism types of configurations. Each Dedekind algebra is associated with a cardinal-valued function on omega called its configuration signature. The configuration signature of a Dedekind algebra counts the number of configurations in the decomposition of the algebra in each isomorphism type.The configuration signature of a Dedekind algebra encodes the structure of that algebra in the sense that two Dedekind algebras are isomorphic iff their configuration signatures are identical. Configuration signatures are used to establish various results in the first-order model theory of Dedekind algebras. These include categoricity results for the first-order theories of Dedekind algebras and existence and uniqueness results for homogeneous, universal and saturated Dedekind algebras. Fundamental to these results is a condition on configuration signatures that is necessary and sufficient for elementary equivalence.     

Validation of the Multidimensional Blood/Injury Phobia Inventory: Evidence for a Unitary Construct

The Multidimensional Blood/Injury Phobia Inventory (MBPI) was developed from a theoretical framework to characterize a broad range of feared stimuli and phobic reactions associated with this pathology. The MBPI consists of 40 items that cross 4 types of stimulus content (injections, hospitals, blood, injury), 5 types of phobic responses (fear, avoidance, worry, fainting, disgust), and a self versus other focus. This study reports on administration of the MBPI to 558 undergraduates, 9 of whom had blood/injury phobia. The instrument had a Cronbach's alpha of .91 and demonstrated good concurrent validity, convergent validity, and discriminant validity. One large factor emerged in an unrotated principal components analysis, suggesting that blood/injury phobia is a unitary psychometric construct. Exploratory factor analyses revealed a 6-factor solution defined by stimulus content domains and fainting, each of which may be important to consider clinically when assessing the unique concerns of treatment-seeking individuals.