Confidence intervals for the parameters of psychometric functions

A Monte Carlo method for computing the bias and standard deviation of estimates of the parameters of a psychometric function such as the Weibull/Quick is described. The method, based on Efron's parametric bootstrap, can also be used to estimate confidence intervals for these parameters. The method's ability to predict bias, standard deviation, and confidence intervals is evaluated in two ways. First, its predictions are compared to the outcomes of Monte Carlo simulations of psychophysical experiments. Second, its predicted confidence intervals were compared with the actual variability of human observers in a psychophysical task. Computer programs implementing the method are available from the author.     

Content: Covariation,control and contingency

The Representational Theory of the Mind allows for psychological explanations couched in terms of the contents of propositional attitudes. Propositional attitudes themselves are taken to be relations to mental representations. These representations (partially) determine the contents of the attitudes in which they figure. Thus, Representationalism owes an explanation of the contents of mental representations. This essay constitutes an atomistic theory of the content of formally or syntactically simple mental representation, proposing that the content of such a representation is determined by the intersection of the representation's correlational and control properties. The theory is distinguished from standard information-based accounts of mental content in allowing that the relevant correlations be contingent while insisting on an efferent aspect to mental content. The theory on offer allows for a natural explanation of misrepresentation, finds a niche for the notion ofnarrow content, welcomes radical first person fallibility with respect to questions of content, admits of mental ambiguity and recognizes that the future of a psychological agent is a factor in determining the content of the agent's present psychological states.     

Math anxiety: who has it, why it develops, and how to guard against it

Basic math skills are important for success in school and everyday life. Yet many people experience apprehension and fear when dealing with numerical information, termed math anxiety. Recently, researchers have started to probe the antecedents of math anxiety, revealing some surprising insights into its onset, risk factors, and remediation.     

Conjoint measurement of gloss and surface texture

The image of a material's surface varies not only with viewing and illumination conditions, but also with the material's surface properties, including its 3-D texture and specularity. Previous studies on the visual perception of surface material have typically focused on single material properties, ignoring possible interactions. In this study, we used a conjoint-measurement design to determine how observers represent perceived 3-D texture ("bumpiness") and specularity ("glossiness") and modeled how each of these two surface-material properties affects perception of the other. Observers made judgments of bumpiness and glossiness of surfaces that varied in both surface texture and specularity. We quantified how changes in each surface-material property affected judgments of the other and found that a simple additive model captured visual perception of texture and specularity and their interaction. Conjoint measurement is potentially a powerful tool for analyzing perception of surface material in realistic environments.