The psychometric function: I. Fitting, sampling, and goodness of fit

The psychometric function relates an observer’s performance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. This paper, together with its companion paper (Wichmann & Hill, 2001), describes an integrated approach to (1) fitting psychometric functions, (2) assessing the goodness of fit, and (3) providing confidence intervals for the function’s parameters and other estimates derived from them, for the purposes of hypothesis testing. The present paper deals with the first two topics, describing a constrained maximum-likelihood method of parameter estimation and developing several goodness-of-fit tests. Using Monte Carlo simulations, we deal with two specific difficulties that arise when fitting functions to psychophysical data. First, we note that human observers are prone to stimulus-independent errors (orlapses). We show that failure to account for this can lead to serious biases in estimates of the psychometric function’s parameters and illustrate how the problem may be overcome. Second, we note that psychophysical data sets are usually rather small by the standards required by most of the commonly applied statistical tests. We demonstrate the potential errors of applying traditionalX ² methods to psychophysical data and advocate use of Monte Carlo resampling techniques that do not rely on asymptotic theory. We have made available the software to implement our methods.     

Statistical Learning of Unfamiliar Sounds as Trajectories Through a Perceptual Similarity Space

In typical statistical learning studies, researchers define sequences in terms of the probability of the next item in the sequence given the current item (or items), and they show that high probability sequences are treated as more familiar than low probability sequences. Existing accounts of these phenomena all assume that participants represent statistical regularities more or less as they are defined by the experimenters—as sequential probabilities of symbols in a string. Here we offer an alternative, or possibly supplementary, hypothesis. Specifically, rather than identifying or labeling individual stimuli discretely in order to predict the next item in a sequence, we need only assume that the participant is able to represent the stimuli as evincing particular similarity relations to one another, with sequences represented as trajectories through this similarity space. We present experiments in which this hypothesis makes sharply different predictions from hypotheses based on the assumption that sequences are learned over discrete, labeled stimuli. We also present a series of simulation models that encode stimuli as positions in a continuous two‐dimensional space, and predict the next location from the current location. Although no model captures all of the data presented here, the results of three critical experiments are more consistent with the view that participants represent trajectories through similarity space rather than sequences of discrete labels under particular conditions.     

A Quantitative Empirical Analysis of the Abstract/Concrete Distinction

This study presents original evidence that abstract and concrete concepts are organized and represented differently in the mind, based on analyses of thousands of concepts in publicly available data sets and computational resources. First, we show that abstract and concrete concepts have differing patterns of association with other concepts. Second, we test recent hypotheses that abstract concepts are organized according to association, whereas concrete concepts are organized according to (semantic) similarity. Third, we present evidence suggesting that concrete representations are more strongly feature‐based than abstract concepts. We argue that degree of feature‐based structure may fundamentally determine concreteness, and we discuss implications for cognitive and computational models of meaning.     

Posttraumatic stress and physical health among adults: The role of coping mechanisms

The purpose of the present study was to examine whether coping mechanisms predict physical health, after controlling for posttraumatic stress disorder (PTSD) symptom clusters in a non-clinical sample of adults. Data were collected from 483 adults through an online survey. Most of the participants (66.7%) reported lifetime exposure to at least one traumatic event. The final sample of this study included 319 trauma-exposed individuals. Results indicated that PTSD symptoms on the avoidance and hyperarousal clusters had significant positive relationships with self-reported physical health symptoms. After controlling for gender and PTSD, denial, behavioral disengagement, and self-blame significantly and positively predicted physical health symptoms.     

Investigating the Links Between Cultural Values and Belief in Conspiracy Theories: The Key Roles of Collectivism and Masculinity

Research suggests that belief in conspiracy theories (CT) stems from basic psychological mechanisms and is linked to other belief systems (e.g., religious beliefs). While previous research has extensively examined individual and contextual variables associated with CT beliefs, it has not yet investigated the role of culture. In the current research, we tested, based on a situated cultural cognition perspective, the extent to which culture predicts CT beliefs. Using Hofstede's model of cultural values, three nation-level analyses of data from 25, 19, and 18 countries using different measures of CT beliefs (Study 1, N = 5323; Study 2a, N = 12,255; Study 2b, N = 30,994) revealed positive associations between masculinity, collectivism, and CT beliefs. A cross-sectional study among U.S. citizens (Study 3, N = 350), using individual-level measures of Hofstede's values, replicated these findings. A meta-analysis of correlations across studies corroborated the presence of positive links between CT beliefs, collectivism, r = .31, 95% CI = [.15; .47], and masculinity, r = .39, 95% CI = [.18; .59]. Our results suggest that in addition to individual differences and contextual variables, cultural factors also play an important role in shaping CT beliefs.     

Emotional appraisal is influenced by cardiac afferent information

Influential models highlight the central integration of bodily arousal with emotion. Some emotions, notably disgust, are more closely coupled to visceral state than others. Cardiac baroreceptors, activated at systole within each cardiac cycle, provide short-term visceral feedback. Here we explored how phasic baroreceptor activation may alter the appraisal of brief emotional stimuli and consequent cardiovascular reactions. We used functional MRI (fMRI) to measure brain responses to emotional face stimuli presented before and during cardiac systole. We observed that the processing of emotional stimuli was altered by concurrent natural baroreceptor activation. Specifically, facial expressions of disgust were judged as more intense when presented at systole, and rebound heart rate increases were attenuated after expressions of disgust and happiness. Neural activity within prefrontal cortex correlated with emotionality ratings. Activity within periaqueductal gray matter reflected both emotional ratings and their interaction with cardiac timing. Activity within regions including prefrontal and visual cortices correlated with increases in heart rate evoked by the face stimuli, while orbitofrontal activity reflected both evoked heart rate change and its interaction with cardiac timing. Our findings demonstrate that momentary physiological fluctuations in cardiovascular afferent information (1) influence specific emotional judgments, mediated through regions including the periaqueductal gray matter, and (2) shape evoked autonomic responses through engagement of orbitofrontal cortex. Together these findings highlight the close coupling of visceral and emotional processes and identify neural regions mediating bodily state influences on affective judgment.