Accuracy of body size estimation: Role of biopsychosocial variables

This study evaluated factors related to the perceptual disturbances of body image. Using a digital body image computer program, 191 participants (107 women, 82 men) adjusted an image of their body to the perceived actual size at five body regions; chest, waist, hips, thighs and calves. A neutral object (a vase) was also adjusted to partial out the level of perceptual distortion present with a neutral object. Men and women overestimated the size of the neutral object and their body image. Among women, overestimation was primarily predicted by high levels of depression, and media and peer influences to be thinner and increase muscles. Among men, overestimation was predicted by high BMI, media influences to lose weight and increase muscles, and peer influences to increase muscles. These findings suggest that perceptual accuracy of body image is primarily predicted by biopsychosocial influences.     

Person identification from biological motion: effects of structural and kinematic cues

Human observers are able to identify a person based on his or her gait. However, little is known about the underlying mechanisms and the kind of information used to accomplish such a task. In this study, participants learned to discriminate seven male walkers shown as point-light displays from frontal, half-profile, or profile view. The displays were gradually normalized with respect to size, shape, and walking frequency, and identification performance was measured. All observers quickly learned to discriminate the walkers, but there was an overall advantage in favor of the frontal view. No effect of size normalization was found, but performance deteriorated when shape or walking frequency was normalized. Presenting the walkers from novel viewpoints resulted in a further decrease in performance. However, even after applying all normalization steps and rotating the walker by 90 degrees, recognition performance was still nearly three times higher than chance level.     

The relative merit of empirical priors in non-identifiable and sloppy models: Applications to models of learning and decision-making

Formal modeling approaches to cognition provide a principled characterization of observed responses in terms of a set of postulated processes, specifically in terms of parameters that modulate the latter. These model-based characterizations are useful to the extent that there is a clear, one-to-one mapping between parameters and model expectations (identifiability) and that parameters can be recovered from reasonably sized data using a typical experimental design (recoverability). These properties are sometimes not met for certain combinations of model classes and data. One suggestion to improve parameter identifiability and recoverability involves the use of “empirical priors”, which constrain parameters according to a previously observed distribution of values. We assessed the efficacy of this proposal using a combination of real and artificial data. Our results showed that a point-estimate variant of the empirical-prior method could not improve parameter recovery systematically. We identified the source of poor parameter recovery in the low information content of the data. As a follow-up step, we developed a fully Bayesian variant of the empirical-prior method and assessed its performance. We find that even such a method that takes the covariance structure of the parameter distributions into account cannot reliably improve parameter recovery. We conclude that researchers should invest additional efforts in improving the informativeness of their experimental designs, as many of the problems associated to impoverished designs cannot be alleviated by modern statistical methods alone.     

Cross-linguistic differences in the use of durational cues for the segmentation of a novel language

It is widely accepted that duration can be exploited as phonological phrase final lengthening in the segmentation of a novel language, i.e., in extracting discrete constituents from continuous speech. The use of final lengthening for segmentation and its facilitatory effect has been claimed to be universal. However, lengthening in the world languages can also mark lexically stressed syllables. Stress-induced lengthening can potentially be in conflict with right edge phonological phrase boundary lengthening. Thus the processing of durational cues in segmentation can be dependent on the listener’s linguistic background, e.g., on the specific correlates and unmarked location of lexical stress in the native language of the listener. We tested this prediction and found that segmentation by both German and Basque speakers is facilitated when lengthening is aligned with the word final syllable and is not affected by lengthening on either the penultimate or the antepenultimate syllables. Lengthening of the word final syllable, however, does not help Italian and Spanish speakers to segment continuous speech, and lengthening of the antepenultimate syllable impedes their performance. We have also found a facilitatory effect of penultimate lengthening on segmentation by Italians. These results confirm our hypothesis that processing of lengthening cues is not universal, and interpretation of lengthening as a phonological phrase final boundary marker in a novel language of exposure can be overridden by the phonology of lexical stress in the native language of the listener.     

An overview of Bayesian reasoning in the analysis of delay‐discounting data

Statistical inference (including interval estimation and model selection) is increasingly used in the analysis of behavioral data. As with many other fields, statistical approaches for these analyses traditionally use classical (i.e., frequentist) methods. Interpreting classical intervals and p‐values correctly can be burdensome and counterintuitive. By contrast, Bayesian methods treat data, parameters, and hypotheses as random quantities and use rules of conditional probability to produce direct probabilistic statements about models and parameters given observed study data. In this work, we reanalyze two data sets using Bayesian procedures. We precede the analyses with an overview of the Bayesian paradigm. The first study reanalyzes data from a recent study of controls, heavy smokers, and individuals with alcohol and/or cocaine substance use disorder, and focuses on Bayesian hypothesis testing for covariates and interval estimation for discounting rates among various substance use disorder profiles. The second example analyzes hypothetical environmental delay‐discounting data. This example focuses on using historical data to establish prior distributions for parameters while allowing subjective expert opinion to govern the prior distribution on model preference. We review the subjective nature of specifying Bayesian prior distributions but also review established methods to standardize the generation of priors and remove subjective influence while still taking advantage of the interpretive advantages of Bayesian analyses. We present the Bayesian approach as an alternative paradigm for statistical inference and discuss its strengths and weaknesses.     

Undecidability of First-Order Modal and Intuitionistic Logics with Two Variables and One Monadic Predicate Letter

Studia Logica - We prove that the positive fragment of first-order intuitionistic logic in the language with two individual variables and a single monadic predicate letter, without functional...     

Universal moral grammar: theory, evidence and the future

Scientists from various disciplines have begun to focus attention on the psychology and biology of human morality. One research program that has recently gained attention is universal moral grammar (UMG). UMG seeks to describe the nature and origin of moral knowledge by using concepts and models similar to those used in Chomsky's program in linguistics. This approach is thought to provide a fruitful perspective from which to investigate moral competence from computational, ontogenetic, behavioral, physiological and phylogenetic perspectives. In this article, I outline a framework for UMG and describe some of the evidence that supports it. I also propose a novel computational analysis of moral intuitions and argue that future research on this topic should draw more directly on legal theory.     

The effects of establishing operations on preferences for tangible items

Researchers have demonstrated that both deprivation and satiation can affect the outcome of preference assessments for food. In the current study, paired-stimulus preference assessments for tangible items were conducted under three conditions: control, deprivation, and satiation. Three persons with developmental disabilities and 3 typically developing preschool children served as participants. The results demonstrated that deprivation and satiation influenced the outcome of preference assessments of leisure items or toys.