Rapid decisions from experience

In many everyday decisions, people quickly integrate noisy samples of information to form a preference among alternatives that offer uncertain rewards. Here, we investigated this decision process using the Flash Gambling Task (FGT), in which participants made a series of choices between a certain payoff and an uncertain alternative that produced a normal distribution of payoffs. For each choice, participants experienced the distribution of payoffs via rapid samples updated every 50 ms. We show that people can make these rapid decisions from experience and that the decision process is consistent with a sequential sampling process. Results also reveal a dissociation between these preferential decisions and equivalent perceptual decisions where participants had to determine which alternatives contained more dots on average. To account for this dissociation, we developed a sequential sampling rank-dependent utility model, which showed that participants in the FGT attended more to larger potential payoffs than participants in the perceptual task despite being given equivalent information. We discuss the implications of these findings in terms of computational models of preferential choice and a more complete understanding of experience-based decision making.     

The speed and accuracy of perceptual decisions in a random-tone pitch task

Research in perceptual decision making is dominated by paradigms that tap the visual system, such as the random-dot motion (RDM) paradigm. In this study, we investigated whether the behavioral signature of perceptual decisions in the auditory domain is similar to those observed in the visual domain. We developed an auditory version of the RDM task, in which tones correspond to dots and pitch corresponds to motion (the random-tone pitch task, RTP). In this task, participants have to decide quickly whether the pitch of a “sound cloud” of tones is moving up or down. Stimulus strength and speed–accuracy trade-off were manipulated. To describe the relationship between stimulus strength and performance, we fitted the proportional-rate diffusion model to the data. The results showed a close coupling between stimulus strength and the speed and accuracy of perceptual decisions in both tasks. Additionally, we fitted the full drift diffusion model (DDM) to the data and showed that three of the four participants had similar speed–accuracy trade-offs in both tasks. However, for the RTP task, drift rates were larger and nondecision times slower, suggesting that some DDM parameters might be dependent on stimulus modality (drift rate and nondecision time), whereas others might not be (decision bound). The results illustrate that the RTP task is suitable for investigating the dynamics of auditory perceptual choices. Future studies using the task might help to investigate modality-specific effects on decision making at both the behavioral and neuronal levels.     

Cells,circuits, and choices: Social influences on perceptual decision making

Making decisions is an integral part of everyday life. Social psychologists have demonstrated in many studies that humans’ decisions are frequently and strongly influenced by the opinions of others—even in simple perceptual decisions, where, for example, participants have to judge what an image looks like. However, because the effect of other people’s opinions on decision making has remained largely unaddressed by the neuroimaging and neurophysiology literature, we are only beginning to understand how social influence is integrated into the decision-making process. We put forward the thesis that by probing the neurophysiology of social influence with perceptual decisionmaking tasks similar to those used in the seminal work of Asch (1952, 1956), this gap could be remedied. Perceptual paradigms are already widely used to probe neuronal mechanisms of decision making in nonhuman primates. There is also increasing evidence about how nonhuman primates’ behavior is influenced by observing conspecifics. The high spatial and temporal resolution of neurophysiological recordings in awake monkeys could provide insight into where and how social influence modulates decision making, and thus should enable us to develop detailed functional models of the neural mechanisms that support the integration of social influence into the decision-making process.     

风险决策和跨期决策的过程比较：以确定效应和即刻效应为例

风险决策和跨期决策与人类生存发展密切相关, 且两类决策在理论发展、行为效应及神经基础等方面具有相似性。为检验二者是否具有共同过程机制, 本研究以风险决策中的确定效应和跨期决策中的即刻效应为例, 采用眼动追踪技术比较了它们的局部、整体过程及模型拟合。辅以贝叶斯因子分析实验数据表明：二者的主要过程特征均相似, 且更符合非折扣模型假设; 二者在加工复杂程度等少数特征上有所不同; 确定和即刻信息在加工方向等特征上存在特异性。这表明二者可能具有共同的核心决策规则：两类决策更可能遵循非折扣模型预期的简捷、启发式规则, 而不是折扣模型所假设的补偿性、基于选项规则。本研究为建立两类决策的共同解释框架做出了有益尝试, 并为决策比较研究方法提供新的方向。     

Instance-based learning: integrating sampling and repeated decisions from experience

In decisions from experience, there are 2 experimental paradigms: sampling and repeated-choice. In the sampling paradigm, participants sample between 2 options as many times as they want (i.e., the stopping point is variable), observe the outcome with no real consequences each time, and finally select 1 of the 2 options that cause them to earn or lose money. In the repeated-choice paradigm, participants select 1 of the 2 options for a fixed number of times and receive immediate outcome feedback that affects their earnings. These 2 experimental paradigms have been studied independently, and different cognitive processes have often been assumed to take place in each, as represented in widely diverse computational models. We demonstrate that behavior in these 2 paradigms relies upon common cognitive processes proposed by the instance-based learning theory (IBLT; Gonzalez, Lerch, & Lebiere, 2003) and that the stopping point is the only difference between the 2 paradigms. A single cognitive model based on IBLT (with an added stopping point rule in the sampling paradigm) captures human choices and predicts the sequence of choice selections across both paradigms. We integrate the paradigms through quantitative model comparison, where IBLT outperforms the best models created for each paradigm separately. We discuss the implications for the psychology of decision making.     

Processes of patient decision making: Theoretical and methodological issues

Abstract

There is a paucity of research studying patients' decision making processes. Traditional normative approaches investigating human decision have presented rational, analytic processing as a ‘gold standard’ for decision making with decision aids developed to facilitate such thinking. This paradigm has been challenged by the recent emergence of naturalistic decision making. Naturalistic approaches argue for techniques modelled closer to how decisions are actually made in ‘real life’. Early work in this evolving field suggests the importance of more automatic, intuitive processing such as the use of heuristic short-cuts. This paper discusses the contribution of naturalistic decision theory and assesses its usefulness as an alternative to classical decision approaches in investigating patient decision making. Approaches for measuring underlying cognitive processes are also critically discussed.     

决策者的认知特征对决策过程及企业战略选择的影响

在不确定环境下,企业的最高决策者的个人特性和行为对于企业的战略决策起着关键的作用。本研究探讨决策者的认知特征对于战略决策的过程以及最终形成的战略决策的影响。研究采用情境实验法,根据某企业的实际情形编写了一个商业案例,案例提供了决策者所需要的信息,并制造出高不确定的情境。148名来自大学管理学院的学生被要求对于该案例进行分析并填写有关量表。对数据进行结构方程模型的分析后得到如下结果：决策者的认知复杂性和认知需要与他们对企业内外环境的周密分析具有显著的正向关系,而且通过后者影响到对于环境中蕴含的机会的判断,并最终影响是否进入某项业务的决策。     

The dynamics of deferred decision

Decision makers are often unable to choose between the options that they are offered. In these settings they typically defer their decision, that is, delay the decision to a later point in time or avoid the decision altogether. In this paper, we outline eight behavioral findings regarding the causes and consequences of choice deferral that cognitive theories of decision making should be able to capture. We show that these findings can be accounted for by a deferral-based time limit applied to existing sequential sampling models of preferential choice. Our approach to modeling deferral as a time limit in a sequential sampling model also makes a number of novel predictions regarding the interactions between choice probabilities, deferral probabilities, and decision times, and we confirm these predictions in an experiment. Choice deferral is a key feature of everyday decision making, and our paper illustrates how established theoretical approaches can be used to understand the cognitive underpinnings of this important behavioral phenomenon.     

Memories of real-life decisions

Three studies investigated decision makers’ memory representations of choice alternatives in most important real-life decisions. In Study 1, each participant recalled the most important decision that she or he had ever made and rated to what degree a number of characteristics could describe the decisions. In Study 2, the participants were asked to think about an important decision that they had made during the last 7–10 days. In Study 3, the memory representations of decisions of a group of action-oriented participants were compared with those of a group of state-oriented participants (Kuhl, 1983). Characteristics related to standard decision theory, like consequences, values, and likelihood, had high ratings of applicability as well as affect/feeling. When testing the applicability of a circumplex model, the fuzzy-trace theory of memory, and differences between state- and action-oriented decision makers, we found (1) that there was no support for the circumplex model of emotions. Instead, an important decision problem was characterised by both positive and negative affect/emotion and thus, a bipolar mapping was found inadequate; (2) that a comparison of abstract and concrete aspects showed that the abstract characteristics scored higher, thereby supporting the fuzzy-trace theory; and (3) that the prediction that action-oriented participants would score higher than state-oriented participants on the characteristic of activity was not supported. However, state-oriented decision makers rated passivity higher than action-oriented decision makers for the important decision of leaving a partner. State-oriented decision makers used perceptual/cognitive scenario representations to a greater extent than action-oriented participants. Finally, it was stressed that in the development of decision theories it is essential to find theoretical representations as close as possible to how decision makers themselves represent the decisions. The method used in this contribution is focused on the role of memory in decision making and gives further insights into how important real-life decisions are represented by different decision makers.     

Integrating Cognitive Process and Descriptive Models of Attitudes and Preferences

Discrete choice experiments—selecting the best and/or worst from a set of options—are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive processes. We extend a well‐established cognitive model, which has successfully explained both choices and response times for simple decision tasks, to complex, multi‐attribute discrete choice data. The fits, and parameters, of the extended model for two sets of choice data (involving patient preferences for dermatology appointments, and consumer attitudes toward mobile phones) agree with those of standard choice models. The extended model also accounts for choice and response time data in a perceptual judgment task designed in a manner analogous to best–worst discrete choice experiments. We conclude that several research fields might benefit from discrete choice experiments, and that the particular accumulator‐based models of decision making used in response time research can also provide process‐level instantiations for random utility models.     

Vocational choice: A decision making perspective

We propose a model of vocational choice that can be used for analyzing and guiding the decision processes underlying career and job choices. Our model is based on research in behavioral decision making (BDM), in particular the choice goals framework developed by Bettman, Luce, and Payne (1998). The basic model involves two major processes. First, the selection of a decision strategy according to four choice goals: maximizing decision accuracy, minimizing cognitive effort, minimizing negative emotion, and maximizing justifiability of the decision. Second, the construction of situation-specific preferences, which can reflect irrelevant task and context factors such as the evaluation mode. This basic model is extended to account for social influences and the long decision time typical of most career and job decisions. We review research on vocational choice in light of this model, discuss normative implications for counseling, and outline a research agenda for studying vocational choice from a behavioral decision making perspective.     

Hybrid route choice model incorporating latent cognitive effects of real-time travel information using physiological data

The proliferation of information systems is enabling drivers to receive en route real-time travel information, often from multiple sources, for making informed routing decisions. A robust understanding of route choice behavior under information provision can be leveraged by traffic operators to design information and its delivery systems for managing network-wide traffic. However, most existing route choice models lack the ability to consider the latent cognitive effects of information on drivers and their implications on route choice decisions. This paper presents a hybrid route choice modeling framework that incorporates the latent cognitive effects of real-time information and the effects of several explanatory variables that can be measured directly (i.e., route characteristics, information characteristics, driver attributes, and situational factors). The latent cognitive effects are estimated by analyzing drivers’ physiological data (i.e., brain electrical activity patterns) measured using an electroencephalogram (EEG). Data was collected for 95 participants in driving simulator experiments designed to elicit realistic route choices using a network-level setup featuring routes with different characteristics (in terms of travel time and driving environment complexity) and dynamic ambient traffic. Averaged EEG band powers in multiple brain regions were used to extract two latent cognitive variables that capture driver’s cognitive effort during and immediately after the information provision, and cognitive inattention before implementing the route choice decision. A Multiple Indicators Multiple Causes model was used to test the effects of several explanatory factors on the latent cognitive variables, and their combined impacts on route choice decisions. The study results highlight the significant effects of driver attributes and information characteristics on latent cognitive effort and of route characteristics on latent cognitive inattention. They also indicate that drivers who are more attentive and exert more cognitive effort are more likely to switch from their current route by complying with the information provided. The study insights can aid traffic operators and information service providers to incorporate human factors and cognitive aspects while devising strategies for designing and disseminating real-time travel information to influence drivers’ route choices.     

A new framework for modeling decisions about changing information: The Piecewise Linear Ballistic Accumulator model

In the real world, decision making processes must be able to integrate non-stationary information that changes systematically while the decision is in progress. Although theories of decision making have traditionally been applied to paradigms with stationary information, non-stationary stimuli are now of increasing theoretical interest. We use a random-dot motion paradigm along with cognitive modeling to investigate how the decision process is updated when a stimulus changes. Participants viewed a cloud of moving dots, where the motion switched directions midway through some trials, and were asked to determine the direction of motion. Behavioral results revealed a strong delay effect: after presentation of the initial motion direction there is a substantial time delay before the changed motion information is integrated into the decision process. To further investigate the underlying changes in the decision process, we developed a Piecewise Linear Ballistic Accumulator model (PLBA). The PLBA is efficient to simulate, enabling it to be fit to participant choice and response-time distribution data in a hierarchal modeling framework using a non-parametric approximate Bayesian algorithm. Consistent with behavioral results, PLBA fits confirmed the presence of a long delay between presentation and integration of new stimulus information, but did not support increased response caution in reaction to the change. We also found the decision process was not veridical, as symmetric stimulus change had an asymmetric effect on the rate of evidence accumulation. Thus, the perceptual decision process was slow to react to, and underestimated, new contrary motion information.     

决策信心在信息化从众中的作用

研究采用JAS范式,通过操纵群体信息的性质（支持和反对）以及一致性程度,考察了决策信心在信息化从众过程中的作用。结果表明：（1）个体仅在接收到反对信息时会发生决策的偏转,表现出从众;（2）群体参照信息能够显著影响个体的信心：支持性的群体信息使个体的信心显著增高,而反对性的群体信息使信心显著降低,且表现出一种“负性偏向”（即个体对来自群体的负性信息更加敏感）;（3）在反对条件下,个体信心降低的程度能够很好地预测其决策偏转的概率,即信息化从众行为。这说明,决策信心可能在信息化从众中起着核心的中介作用——反对性的群体信息使得决策信心下降,而决策信心的下降导致了决策的偏转,从而表现出从众行为。     

Reappraisal and expected value modulate risk taking

Decision making is informed by appraisals of appetitive cues and their associated opportunities for rewards. Such appraisals can be modulated by cognitive regulation strategies in order to promote goal-directed choices. Little is known about how cognitive regulation strategies, especially reappraisal, alter risk taking during decision making. To characterise the effect of reappraisal on risk taking, we systematically varied both the goal of regulation and the value of the decision options. Participants engaged in two reappraisal strategies with opposite goals, to increase (“emphasise”) or decrease (“de-emphasise”) the importance of an upcoming decision, during the presentation of cues signalling monetary decisions. The expected value of taking a risk was systematically varied across decisions such that a risky choice could be beneficial or disadvantageous. Reappraisal strategies increased or decreased risk taking in accordance both with regulation goals and expected value information. These results suggest that reappraisal can be used to flexibly alter behaviour associated with appetitive cues while maintaining value information.     

Memories of real-life decisions

Three studies investigated decision makers' memory representations of choice alternatives in most important real-life decisions. In Study 1, each participant recalled the most important decision that she or he had ever made and rated to what degree a number of characteristics could describe the decisions. In Study 2, the participants were asked to think about an important decision that they had made during the last 7-10 days. In Study 3, the memory representations of decisions of a group of action-oriented participants were compared with those of a group of state-oriented participants (Kuhl, 1983). Characteristics related to standard decision theory, like consequences, values, and likelihood, had high ratings of applicability as well as affect/feeling. When testing the applicability of a circumplex model, the fuzzy-trace theory of memory, and differences between state- and action-oriented decision makers, we found (1) that there was no support for the circumplex model of emotions. Instead, an important decision problem was characterised by both positive and negative affect/emotion and thus, a bipolar mapping was found inadequate; (2) that a comparison of abstract and concrete aspects showed that the abstract characteristics scored higher, thereby supporting the fuzzy-trace theory; and (3) that the prediction that action-oriented participants would score higher than state-oriented participants on the characteristic of activity was not supported. However, state-oriented decision makers rated passivity higher than action-oriented decision makers for the important decision of leaving a partner. State-oriented decision makers used perceptual/cognitive scenario representations to a greater extent than action-oriented participants. Finally, it was stressed that in the development of decision theories it is essential to find theoretical representations as close as possible to how decision makers themselves represent the decisions. The method used in this contribution is focused on the role of memory in decision making and gives further insights into how important real-life decisions are represented by different decision makers.     

An Influence of Positive Affect on Decision Making in Complex Situations: Theoretical Issues With Practical Implications

This article reviews evidence indicating that, in most circumstances, positive affect enhances problem solving and decision making, leading to cognitive processing that is not only flexible, innovative, and creative, but also thorough and efficient. These results have implications regarding consumers’ potential reactions to affect generated by ads, products, consumption situations, and service encounters. These cognitive effects of positive affect are considered in the context of effects on social interaction that show that positive affect leads to helping, generosity, and interpersonal understanding. Together, these findings suggest implications especially for customer satisfaction, and particularly for a role for employee positive affect, or employee satisfaction, in generating customer satisfaction. Moreover, studies specifically in the domain of medical decision making and problem solving indicate that these implications would apply to the specific areas of doctor–patient interaction, medical decision making, and medical consumer satisfaction. Finally, it is suggested that the benefits of positive affect be considered when formulating healthcare policy and be included in economic models and policy decisions more generally as well.     

A note on response-decision in perceptual identification

Summary Perceptual identification is conceived here as a two-stage process which includes perceptual processing and a response-decision. Three models for the decision part are discussed. Nakatani's (1972) model is based on choice theory and incorporates sophisticated guessing. Rumelhart's (1971) model assumes that the probability of a response equals either the prior or posterior probability of the stimulus corresponding to this response. A third model is derived which incorporates assumptions from both Nakatani's and Rumelhart's model. According to the results of two visual identification experiments Rumelhart's model has been rendered implausible whereas the third model provides a more plausible interpretation of the results.