An experimental and simulation study of the impact of emotional information on analogical reasoning

We investigated whether and how emotional information would affect analogical reasoning. We hypothesized that task-irrelevant emotional information would impair performance whereas task-relevant emotional information would enhance it. In Study 1, 233 undergraduates completed a novel version of the People Pieces Task (Emotional Faces People Task), an analogical reasoning task in which the task characters displayed emotional or neutral facial expressions (within-participants). The emotional faces were relevant or irrelevant to the task (between-participants). We simulated the behavioral results using the Learning and Inference with Schemas and Analogies (LISA) model of relational reasoning. LISA is a neurally plausible, symbolic-connectionist computational model of analogical reasoning. In comparison to neutral trials, participants were slower but more accurate on emotion-relevant trials, and were faster but less accurate on emotion-irrelevant trials. Simulations using the LISA model demonstrated that it is possible to account for the effects of emotional information on reasoning in terms of how emotional stimuli attract attention during a reasoning task. In Study 2, 255 undergraduates completed the Emotional Faces People Task at either a high- or low-working memory load. The high working memory load condition of Study 2 replicated the findings of Study 1, showing that participants were more accurate on emotion-relevant trials than on emotion-irrelevant trials; in Study 2, this increased accuracy could not be accounted for by a speed-accuracy tradeoff. The working memory manipulation influenced the manner in which the congruence (with the correct answer) of emotion-irrelevant emotion influenced performance. Simulations using the LISA model showed that manipulating the salience of emotion, the error penalty, as well as vigilance (which determines the likelihood that LISA will notice it has attended to an irrelevant relation), could reasonably reproduce the behavioral results of both low and high working memory load conditions of Study 2.

Discounting and Augmentation in Causal Conditional Reasoning: Causal Models or Shallow Encoding?

Recent research comparing mental models theory and causal Bayes nets for their ability to account for discounting and augmentation inferences in causal conditional reasoning had some limitations. One of the experiments used an ordinal scale and multiple items and analysed the data by subjects and items. This procedure can create a variety of problems that can be resolved by using an appropriate cumulative link function mixed models approach in which items are treated as random effects. Experiment 1 replicated this earlier experiment and analysed the results using appropriate data analytic techniques. Although successfully replicating earlier research, the pattern of results could be explained by a much simpler "shallow encoding" hypothesis. Experiment 2 introduced a manipulation to critically test this hypothesis. The results favoured the causal Bayes nets predictions and not shallow encoding and were not consistent with mental models theory. Experiment 1 provided qualified support for the causal Bayes net approach using appropriate statistics because it also replicated the failure to observe one of the predicted main effects. Experiment 2 discounted one plausible explanation for this failure. While within the limited goals that were set for these experiments they were successful, more research is required to account for the pattern of findings using this paradigm.

Cognitive Reactivity: Cultural Adaptation and Psychometric Testing of the Persian Version of the Leiden Index of Depression Sensitivity Revised (LEIDS-R) in an Iranian Sample

Cognitive reactivity (CR) to the experimental induction of sad mood has been found to predict relapse in recovered depressed patients. The Leiden Index of Depression Sensitivity Revised (LEIDS-R) is a self-report measure of CR. The aim of the present study was to establish the validity and reliability of the Persian version of the LEIDS-R. The participants were recovered depressed and non-depressed Iranian individuals (n = 833). The analyses included content validation, factor analysis, construct validity, and reliability testing. Preliminary construct validation analysis confirmed that factor analysis was appropriate for the Persian version of the LEIDS-R. Factor analysis displayed similar factor loadings to the original English version. The total internal consistency of the translated version, which was assessed using Cronbach’s alpha coefficient, was equal to 0.90. The test-retest reliability of the total score was equal to that of the test-retest conducted after a two-week interval at 0.94. Content validity, face validity, and construct validity, as well as reliability analysis were all found to be satisfactory for the Persian version of the LEIDS-R. The Persian version of the LEIDS-R appears to be valid and reliable for use in future studies, and has properties comparable to the original version and to that obtained in previous studies.

Defeasible reasoning with legal conditionals

Valid conclusions can be defeated if people can think of conditions that prevent the consequent to occur although the antecedent is given. The goal of the present research was to investigate how people consider these conditions when reasoning with legal conditionals such as "If a person kills another human, then this person should be punished for manslaughter." In Experiments 1 and 2 legal conditionals were presented to participants together with exculpatory circumstances, i.e., counterexamples. The participants' task was to decide whether they would adhere to the legal conditional rule and punish the offender. Participants were either lawyers (i.e., advanced law students and graduate lawyers) or legal laypeople. We found that laypeople often ignore exculpatory circumstances and adhere to the conditional rule when offences evoked high levels of moral outrage. Lawyers did not show this effect. In Experiment 3 laypeople showed difficulties even when asked to simply imagine exculpatory circumstances for highly morally outrageous offences. Results provide new evidence for the role of emotions--like moral outrage--in the consideration of counterexamples to legal conditionals.

Précis of bayesian rationality: The probabilistic approach to human reasoning

According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic--the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive development; and contemporary psychology of reasoning has focussed on comparing human reasoning against logical standards. Bayesian Rationality argues that rationality is defined instead by the ability to reason about uncertainty. Although people are typically poor at numerical reasoning about probability, human thought is sensitive to subtle patterns of qualitative Bayesian, probabilistic reasoning. In Chapters 1-4 of Bayesian Rationality (Oaksford & Chater 2007), the case is made that cognition in general, and human everyday reasoning in particular, is best viewed as solving probabilistic, rather than logical, inference problems. In Chapters 5-7 the psychology of "deductive" reasoning is tackled head-on: It is argued that purportedly "logical" reasoning problems, revealing apparently irrational behaviour, are better understood from a probabilistic point of view. Data from conditional reasoning, Wason's selection task, and syllogistic inference are captured by recasting these problems probabilistically. The probabilistic approach makes a variety of novel predictions which have been experimentally confirmed. The book considers the implications of this work, and the wider "probabilistic turn" in cognitive science and artificial intelligence, for understanding human rationality.

When can we say 'if'?

In this study, we focus on the conditions which permit people to assert a conditional statement of the form 'if p then q' with conversational relevance. In a broadly decision-theoretic approach, also drawing on hypothetical thinking theory [Evans, J. St. B. T. (2007). Hypothetical thinking: Dual processes in reasoning and judgement. Hove, UK: Psychology Press.], we predicted that conditional tips and promises would appear more useful and persuasive and be more likely to encourage an action p when (a) the conditional link from p to q was stronger, (b) the cost of the action p was lower and (c) the benefit of the consequence q was higher. Similarly, we predicted that conditional warnings and threats would be seen as more useful and persuasive and more likely to discourage an action p when (a) the conditional link from p to q was stronger, (b) the benefit of the action p was lower and (c) the cost of the consequence q was higher. All predictions were strongly confirmed, suggesting that such conditionals may best be asserted when they are of high relevance to the goals of the listener.