An alternative approach to calculating Area‐Under‐the‐Curve (AUC) in delay discounting research

Applied to delay discounting data, Area‐Under‐the‐Curve (AUC) provides an atheoretical index of the rate of delay discounting. The conventional method of calculating AUC, by summing the areas of the trapezoids formed by successive delay‐indifference point pairings, does not account for the fact that most delay discounting tasks scale delay pseudoexponentially, that is, time intervals between delays typically get larger as delays get longer. This results in a disproportionate contribution of indifference points at long delays to the total AUC, with minimal contribution from indifference points at short delays. We propose two modifications that correct for this imbalance via a base‐10 logarithmic transformation and an ordinal scaling transformation of delays. These newly proposed indices of discounting, AUC_{log d} and AUC_{or d,} address the limitation of AUC while preserving a primary strength (remaining atheoretical). Re‐examination of previously published data provides empirical support for both AUC_{log d} and AUC_{or d} . Thus, we believe theoretical and empirical arguments favor these methods as the preferred atheoretical indices of delay discounting.     

Syntax for calculation of discounting indices from the monetary choice questionnaire and probability discounting questionnaire

The 27‐item Monetary Choice Questionnaire (MCQ; Kirby, Petry, & Bickel, 1999) and 30‐item Probability Discounting Questionnaire (PDQ; Madden, Petry, & Johnson, 2009) are widely used, validated measures of preferences for immediate versus delayed rewards and guaranteed versus risky rewards, respectively. The MCQ measures delayed discounting by asking individuals to choose between rewards available immediately and larger rewards available after a delay. The PDQ measures probability discounting by asking individuals to choose between guaranteed rewards and a chance at winning larger rewards. Numerous studies have implicated these measures in addiction and other health behaviors. Unlike typical self‐report measures, the MCQ and PDQ generate inferred hyperbolic temporal and probability discounting functions by comparing choice preferences to arrays of functions to which the individual items are preconfigured. This article provides R and SPSS syntax for processing the MCQ and PDQ. Specifically, for the MCQ, the syntax generates k values, consistency of the inferred k, and immediate choice ratios; for the PDQ, the syntax generates h indices, consistency of the inferred h, and risky choice ratios. The syntax is intended to increase the accessibility of these measures, expedite the data processing, and reduce risk for error.     

Judging the Probability of Hypotheses Versus the Impact of Evidence: Which Form of Inductive Inference Is More Accurate and Time‐Consistent?

Inductive reasoning requires exploiting links between evidence and hypotheses. This can be done focusing either on the posterior probability of the hypothesis when updated on the new evidence or on the impact of the new evidence on the credibility of the hypothesis. But are these two cognitive representations equally reliable? This study investigates this question by comparing probability and impact judgments on the same experimental materials. The results indicate that impact judgments are more consistent in time and more accurate than probability judgments. Impact judgments also predict the direction of errors in probability judgments. These findings suggest that human inductive reasoning relies more on estimating evidential impact than on posterior probability.     

Learning Orthographic Structure With Sequential Generative Neural Networks

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high‐order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high‐quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non‐connectionist probabilistic models (n‐grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain.     

Sex Differences in Psychological Factors Associated with Social Discounting

The social discounting paradigm is a powerful means of quantifying altruism in humans, who are typically willing to forgo some amount of personal earnings in exchange for increased earnings for another person. The amount of money that people are willing to forgo decreases with increasing social distance. In this study, we examined variables related to sex, intolerance of uncertainty, and empathy, all of which are theorized to affect the social discounting rate. Participants (27 men and 28 women) completed measures of intolerance of uncertainty, empathy, and social discounting. We found sex differences in psychological predictors of social discounting: in women, empathy (but not intolerance of uncertainty) predicts the social discounting rate, while in men, social discounting is associated with intolerance of uncertainty (but not empathy). Possible neurobiological, social, and cognitive explanations for this sex difference are discussed. Copyright © 2015 John Wiley & Sons, Ltd.     

Discounting of food and water in rats shows trait- and state-like characteristics

Delay discounting is the loss in value of an outcome as a function of its delay. The present study focused on examining a trait-like characteristic of delay discounting in a preclinical animal model. Specifically, we were interested in whether there was a positive relation between discounting of 2 different outcomes in rats. That is, would rats that discount delayed food steeply also discount delayed water steeply? In addition, we examined how session-to-session variability in discounting could be attributed to differences between subjects (trait variability) and to differences within subjects (state variability). Finally, we measured discounting from early- to mid-adulthood, allowing us to examine changes in discounting as a function of age. Overall, we found a moderate, positive correlation between discounting of food and discounting of water in rats, providing further evidence that the relative consistency with which individuals discount different outcomes is a trait-like characteristic. In addition, we found a high degree of within-subject variability in discounting, indicating strong state-like differences from session to session. Finally, overall, discounting decreased as a function of age; however, individual-subject data showed variability in how discounting changed across time. Overall, our results show that differences in delay discounting between individuals reflect variability in both trait- and state-like characteristics.     

Dreading the pain of others? Altruistic responses to others' pain underestimate dread

A dislike of waiting for pain, aptly termed ‘dread’, is so great that people will increase pain to avoid delaying it. However, despite many accounts of altruistic responses to pain in others, no previous studies have tested whether people take delay into account when attempting to ameliorate others' pain. We examined the impact of delay in 2 experiments where participants (total N = 130) specified the intensity and delay of pain either for themselves or another person. Participants were willing to increase the experimental pain of another participant to avoid delaying it, indicative of dread, though did so to a lesser extent than was the case for their own pain. We observed a similar attenuation in dread when participants chose the timing of a hypothetical painful medical treatment for a close friend or relative, but no such attenuation when participants chose for a more distant acquaintance. A model in which altruism is biased to privilege pain intensity over the dread of pain parsimoniously accounts for these findings. We refer to this underestimation of others' dread as a ‘Dread Empathy Gap’.     

愤怒情绪对延迟折扣的影响：确定感和控制感的中介作用

本研究基于评估倾向理论, 通过3项实验考察了特定负性情绪(愤怒)对延迟折扣的影响, 并探究确定感和控制感评估倾向在这一关系中的作用。实验1考察愤怒情绪对延迟折扣的影响, 结果发现, 愤怒组被试的延迟满足倾向显著强于恐惧组和控制组。实验2采用实验因果链设计考察确定感和控制感评估倾向在愤怒情绪影响个体延迟折扣中的作用, 结果发现, 愤怒情绪可以有效增强个体的确定感和控制感(实验2a), 同时确定感和控制感能够增强个体的延迟满足倾向(实验2b)。实验3采用中介测量设计考察确定感和控制感评估倾向在愤怒情绪影响个体延迟折扣中的作用, 结果发现, 确定感和控制感评估倾向在愤怒情绪影响个体延迟折扣中起完全中介作用。本研究结果表明, 当个体进行跨期决策时, 体验到与确定感和控制感有关的偶然愤怒情绪会增强其延迟满足倾向。本研究对探究特定负性情绪对个体延迟折扣的影响具有一定的启示意义。     

跨期决策中的负折扣现象及其机制

主流跨期决策模型认为, 跨期决策存在一个时间折扣过程。时间折扣是指人们会根据将来获益或损失的延迟时间对其效用进行折扣, 折扣后的效用小于原来的效用, 而负折扣现象违背了时间折扣过程。负折扣现象出现在金钱、非金钱的获益与损失领域, 其可能的解释机制为预期情绪。目前关于负折扣现象的研究, 较少验证其影响机制, 未来的研究可以结合眼动追踪和fMRI技术探讨其机制, 并丰富对负折扣现象的影响因素研究。     

The roles of delay and probability discounting in texting while driving: Toward the development of a translational scientific program

A sample of 109 college students completed a survey to assess how frequently they send or read text messages while driving. In a novel discounting task with a hypothetical scenario in which participants receive a text message while driving, they rated the likelihood of replying to a text message immediately versus waiting to reply until arriving at a destination. The scenario presented several delays to a destination and probabilities of a motor vehicle crash. The likelihood of waiting to reply decreased as a function of both the delay until the destination and the probability of a motor vehicle crash. Self‐reported higher frequencies of texting while driving were associated with greater rates of both delay and probability discounting. The degree of delay discounting was altered as a function of the probability of a motor vehicle crash and vice versa. These results suggest that both delay and probability discounting are important underlying mechanisms of drivers' decision to text while driving.