Common region wins the competition between extrinsic grouping cues: Evidence from a task without explicit attention to grouping

The competition between perceptual grouping factors is a relatively ignored topic, especially in the case of extrinsic grouping cues (e.g., common region or connectedness). Recent studies have examined the integration of extrinsic cues using tasks that induce selective attention to groups based on different grouping cues. However, this procedure could generate alternative strategies for task performance, which are non-related to the perceptual grouping operations. In the current work, we used an indirect task, i.e. repetition discrimination task, without explicit attention to grouping cues to further examine the rules that govern dominance between competing extrinsic grouping factors. This procedure allowed us to obtain an unbiased measure of the competition between common region and connectedness cues acting within the same display. The results corroborate previous data showing that grouping by common region dominated the perceived organization of the display, even though the phenomenological strength of the grouping cues was equated for each participant by means of a preliminary scaling task. Our results highlight the relevance of using indirect tasks as an essential tool for the systematic study of the integration of extrinsic grouping cues.     

Strategic influence on the time course of predictive inferences in reading

In the present study, we investigated how reading strategies affect the time course of online predictive inferences. Participants read sentences under instructions either to anticipate the outcomes of described events or to understand the sentences. These were followed by a target word to be named, with stimulus onset asynchronies (SOAs) of 500 or 1,000 msec (50- or 550-msec interstimulus interval, respectively). Sentences either were predictive of events or were lexically matched control sentences. There was facilitation in naming latencies for predictable target words in the strategic-anticipation condition at both SOAs, but not in the read-to-understand condition, with a significant improvement in the former condition in comparison with the latter. This suggests that predictive inferences, which are typically considered to be resource demanding, can be speeded up by specific goals in reading. Moreover, this can occur at no cost to comprehension of explicit information, as was revealed by a comprehension test.     

Shared, not unique, components of personality and psychosocial functioning predict depression severity after acute-phase cognitive therapy

In a sample of 100 patients with recurrent major depression, we collected depression severity data early and late in acute-phase cognitive therapy, plus a wide range of psychosocial variables that have been studied extensively in depression research, including measures of interpersonal, cognitive, and social functioning, and personality traits using an inventory that is linked with the Big-Three tradition in personality assessment theory. By assessing this broad range of variables in a single study, we could examine the extent to which relations of these variables with depression were due to (a) a common factor shared across this diverse set of constructs, (b) factors shared among each type of construct (personality vs. psychosocial measures), or (c) specific aspects of the individual measures. Only the most general factor shared across the personality and psychosocial variables predicted later depression.     

Are cognitive symptoms of schizophrenia mediated by abnormalities in emotional arousal?

We tested 28 individuals with schizophrenia (SZ) and 16 healthy individuals on a test of logical reasoning and "cognitive gating," defined as the ability to discriminate between relevant and irrelevant information in confirming or disconfirming a given belief. The Logical Reasoning and Cognitive Gating Task tests both processes under neutral and affect-laden conditions. This is done by presenting formally identical constructs using benign and emotionally arousing language. When separated by symptom profiles, we found statistically significant differences for performance and arousal response between patients with delusions, patients with formal thought disorder, and patients with neither delusions nor formal thought disorder, as well as between patients and healthy controls. When analyzed by error type, we found that nearly all errors by delusional patients were caused by overly restrictive information choice, a pattern that may be related to a delusional patient's tendency to "jump to conclusions" on Bayesian probabilistic tasks. This is in contrast to patients with formal thought disorder, whose low performance resulted also from overly extensive information choice. The tendencies towards restriction were exacerbated by arousal, which is consistent with studies on cognition and arousal in healthy individuals. After briefly examining research on emotional arousal and SZ, and the interaction between emotional arousal and restriction of perceptual cues in healthy individuals, we conclude by suggesting a model which accounts for the distinctive cognitive characteristics of delusional patients by their possessing distinct vulnerabilities to emotional arousal. Specifically, these results suggest the possibility that delusional patients process information in a manner that is essentially intact. However, delusional patients may possess an acute vulnerability to emotional arousal that might cause delusional individuals to behave cognitively as if they were healthy individuals under significantly more severe forms of stress.     

Enhancing Interpretability in Factor Analysis by Means of Mathematical Optimization

Abstract

Exploratory Factor Analysis (EFA) is a widely used statistical technique to discover the structure of latent unobserved variables, called factors, from a set of observed variables. EFA exploits the property of rotation invariance of the factor model to enhance factors’ interpretability by building a sparse loading matrix. In this paper, we propose an optimization-based procedure to give meaning to the factors arising in EFA by means of an additional set of variables, called explanatory variables, which may include in particular the set of observed variables. A goodness-of-fit criterion is introduced which quantifies the quality of the interpretation given this way. Our methodology also exploits the rotational invariance of EFA to obtain the best orthogonal rotation of the factors, in terms of the goodness-of-fit, but making them match to some of the explanatory variables, thus going beyond traditional rotation methods. Therefore, our approach allows the analyst to interpret the factors not only in terms of the observed variables, but in terms of a broader set of variables. Our experimental results demonstrate how our approach enhances interpretability in EFA, first in an empirical dataset, concerning volumes of reservoirs in California, and second in a synthetic data example.