The response dynamics of preferential choice

The ubiquity of psychological process models requires an increased degree of sophistication in the methods and metrics that we use to evaluate them. We contribute to this venture by capitalizing on recent work in cognitive science analyzing response dynamics, which shows that the bearing information processing dynamics have on intended action is also revealed in the motor system. This decidedly “embodied” view suggests that researchers are missing out on potential dependent variables with which to evaluate their models—those associated with the motor response that produces a choice. The current work develops a method for collecting and analyzing such data in the domain of decision making. We first validate this method using widely normed stimuli from the International Affective Picture System (Experiment 1), and demonstrate that curvature in response trajectories provides a metric of the competition between choice options. We next extend the method to risky decision making (Experiment 2) and develop predictions for three popular classes of process model. The data provided by response dynamics demonstrate that choices contrary to the maxim of risk seeking in losses and risk aversion in gains may be the product of at least one “online” preference reversal, and can thus begin to discriminate amongst the candidate models. Finally, we incorporate attentional data collected via eye-tracking (Experiment 3) to develop a formal computational model of joint information sampling and preference accumulation. In sum, we validate response dynamics for use in preferential choice tasks and demonstrate the unique conclusions afforded by response dynamics over and above traditional methods.     

Attention in risky choice

Previous research on the processes involved in risky decisions has rarely linked process data to choice directly. We used a simple measure based on the relative amount of attentional deployment to different components (gains/losses and their probabilities) of a risky gamble during the choice process, and we related this measure to the actual choice. In an experiment we recorded the decisions, decision times, and eye movements of 80 participants who made decisions on 11 choice problems. We used the number of eye fixations and fixation transitions to trace the deployment of attention during the choice process and obtained the following main results. First, different components of a gamble attracted different amounts of attention depending on participants' actual choice. This was reflected in both the number of fixations and the fixation transitions. Second, the last-fixated gamble but not the last-fixated reason predicted participants' choices. Third, a comparison of data obtained with eye tracking and data obtained with verbal protocols from a previous study showed a large degree of convergence regarding the process of risky choice. Together these findings tend to support dimensional decision strategies such as the priority heuristic.     

The simplest complete model of choice response time: linear ballistic accumulation

We propose a linear ballistic accumulator (LBA) model of decision making and reaction time. The LBA is simpler than other models of choice response time, with independent accumulators that race towards a common response threshold. Activity in the accumulators increases in a linear and deterministic manner. The simplicity of the model allows complete analytic solutions for choices between any number of alternatives. These solutions (and freely-available computer code) make the model easy to apply to both binary and multiple choice situations. Using data from five previously published experiments, we demonstrate that the LBA model successfully accommodates empirical phenomena from binary and multiple choice tasks that have proven difficult for other theoretical accounts. Our results are encouraging in a field beset by the tradeoff between complexity and completeness.     

On self-referencing differences in judgment and choice

Compared to judgment, choice is argued to elicit more self-referent processing and thereby produce greater subsequent recall of evaluated information. This response mode effect is shown to be dependent upon sufficient visualization to overcome the use of heuristic processing during choice. When visualizing prior to the task, choice leads to increased thinking about personal consumption occasions relative to judgment, leading to enhanced recall of vivid (vs. non-vivid) attributes. This proposed interaction of task and visualization was found in two experiments that assessed incidental recall following a choice or judgment task. In experiment 1, participants recalled more vivid product attribute information after choosing between options than after rating each option separately, but only when instructed to visualize during evaluation. To eliminate a comparison-based explanation of this effect, a second experiment was conducted that presented only one option in each category. Participants who evaluated their intention to purchase the option (a judgment equivalent of choice) demonstrated greater recall of vivid product attribute information than did participants who rated their liking for the option, and this recall difference was again moderated by instructions to visualize.     

Attention and attribute overlap in preferential choice

Attributes that are common, or overlapping, across alternatives in two-alternative forced preferential choice tasks are often non-diagnostic. In many settings, attending to and evaluating these attributes does not help the decision maker determine which of the available alternatives is the most desirable. For this reason, many existing behavioural theories propose that decision makers ignore common attributes while deliberating. Across six experiments, we find that decision makers do direct their attention selectively and ignore attributes that are not present in or associated with either of the available alternatives. However, they are as likely to attend to common attributes as they are to attend to attributes that are unique to a single alternative. These results suggest the need for novel theories of attention in preferential choice.     

Drawing conclusions from choice response time models: A tutorial using the linear ballistic accumulator

Cognitive models of choice and response times can lead to deeper insights into the processes underlying decisions than standard analyses of accuracy and response time data. The application of these models, however, has historically been reserved for the authors of the models, and their associates. Recently, choice response time models have become more accessible through the release of user-friendly software for estimating their parameters. The aim of this tutorial is to provide guidance about the process of using these parameter estimates and associated model fits to make conclusions about experimental data. We use an application of one response time model, the linear ballistic accumulator, as an example to demonstrate the steps required to select an appropriate parametric characterization of a data set. We also discuss how to evaluate the quality of the agreement between model and data, including guidelines for presenting model predictions for group-level data.     

Response-level probability effects on reaction time: Now you see them,now you don't

Many reaction time (RT) experiments have tested for response-level probability effects. Their results have been mixed, which is surprising because psychophysiological studies provide clear evidence of motor-level changes associated with an anticipated response. A survey of the designs used in the RT studies reveals many potential problems that could conceal the effects of response probability. We report five new RT experiments testing for response-level probability effects with the most promising of the previous designs—that of Blackman (1972 Blackman, A. R. 1972. Influence of stimulus and response probability on decision and movement latency in a discrete choice reaction task. Journal of Experimental Psychology, 92: 128–133. doi:10.1037/h0032169[Crossref], [PubMed] , [Google Scholar])—and with new designs. Some of these experiments yield evidence of response-level probability effects, but others do not. It appears that response-level probability effects are present primarily in simple tasks with a strong emphasis on response preparation, possibly because participants only expend effort on response preparation in these tasks.     

Multi-attribute choice and affect: The influence of naturally occurring and manipulated moods on choice processes

Based on a two-dimensional model of affect that views Pleasantness and Arousal as affect's two primary dimensions, this study investigates the effects of emotions on choice processes and outcomes. In Study 1, subjects first described their naturally occurring emotional state and then performed two multi-attribute product choice tasks. Subjects in more pleasant mood deliberated longer, used more decision-related information, re-examined more previously examined information, and made more interdimensional moves. Subjects in more aroused mood spent less time deliberating, revealed less information, ignored more product-describing attributes, and re-examined less of previously examined information. Study 2 replicated many of these effects with experimentally manipulated emotions and using a managerial decision-making task. The results are interpreted in terms of (1) a congruency between one's hedonic state and selected decision strategy and (2) a restriction in attentional capacity induced by increased Arousal.     

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.     

Neural affective decision theory: Choices, brains, and emotions

We present a theory and neurocomputational model of how specific brain operations produce complex decision and preference phenomena, including those explored in prospect theory and decision affect theory. We propose that valuation and decision making are emotional processes, involving interacting brain areas that include two expectation-discrepancy subsystems: a dopamine-encoded system for positive events and a serotonin-encoded system for negative ones. The model provides a rigorous account of loss aversion and the shape of the value function from prospect theory. It also suggests multiple distinct neurological mechanisms by which information framing may affect choices, including ones involving anticipated pleasure. It further offers a neural basis for the interactions among affect, prior expectations and counterfactual comparisons explored in decision affect theory. Along with predicting the effects of particular brain disturbances and damage, the model suggests specific neurological explanations for individual differences observed in choice and valuation behaviors.     

Cognitive models of choice: comparing decision field theory to the proportional difference model

People often face preferential decisions under risk. To further our understanding of the cognitive processes underlying these preferential choices, two prominent cognitive models, decision field theory (DFT; Busemeyer & Townsend, 1993 ) and the proportional difference model (PD; González-Vallejo, 2002 ), were rigorously tested against each other. In two consecutive experiments, the participants repeatedly had to choose between monetary gambles. The first experiment provided the reference to estimate the models' free parameters. From these estimations, new gamble pairs were generated for the second experiment such that the two models made maximally divergent predictions. In the first experiment, both models explained the data equally well. However, in the second generalization experiment, the participants' choices were much closer to the predictions of DFT. The results indicate that the stochastic process assumed by DFT, in which evidence in favor of or against each option accumulates over time, described people's choice behavior better than the trade-offs between proportional differences assumed by PD.     

A comparison of bounded diffusion models for choice in time controlled tasks

The Wiener diffusion model (WDM) for 2-alternative tasks assumes that sensory information is integrated over time. Recent neurophysiological studies have found neural correlates of this integration process in certain neuronal populations. This paper analyses the properties of the WDM with two different boundary conditions in decision making tasks in which the time of response is indicated by a cue. A dual reflecting boundary mechanism is proposed and its performance is compared with a well-established absorbing boundary in the cases of the WDM, the WDM with extensions, and the WDM with prior probability. The two types of boundary influence the dynamics of the model and introduce differential weighting of evidence. Comparisons with Ornstein-Uhlenbeck models are also done, and it is shown that the WDM with both types of boundary achieves similar performance and produces similar fits to existing behavioural data. Further studies are proposed to distinguish which boundary mechanism is more consistent with experimental data.     

From Poisson shot noise to the integrated Ornstein-Uhlenbeck process: Neurally principled models of information accumulation in decision-making and response time

In the diffusion model of decision-making, evidence is accumulated by a Wiener diffusion process. A neurally motivated account of diffusive evidence accumulation is given, in which diffusive accumulation arises from an interaction between neural integration processes operating on short and long time scales. The short time scale process is modeled as a Poisson shot noise process with exponential decay. Stimulus information is coded by excitatory-inhibitory shot noise pairs. The long time scale process is modeled as algebraic integration, possibly implemented as a first-order autoregressive process realized by recurrent connections within a population of neurons. At high intensities, an excitatory-inhibitory shot noise pair converges weakly to an Ornstein-Uhlenbeck (OU) velocity process. The integrated OU process, or OU displacement process, obtained by integrating the velocity process over time, is indistinguishable at long times from the Wiener process. Diffusive information accumulation may therefore be characterized as an integrated OU process whose properties mimic those of the Wiener process.     

Processing time predictions of current models of perception in the classic additive factors paradigm

This article explores the consequences for factorial additivity in a Sternberg [(1969). The discovery of processing stages: Extensions of donders method In: W.G. Koster (Ed.), Attention and performance II, Acta Psychologica, 30, 276-315] additive-factors paradigm of the assumptions adopted by models of perception that relate the representation of a stimulus to decision time. Three example models, signal detection theory with the latency-distance hypothesis, stochastic general recognition theory, and a random walk model of exemplar classification, are interrogated to determine what type of interaction they predict factors will yield in a hypothetical factorial (choice) reaction time experiment in which the ‘empirical’ factors’ effects are manifest as parameter changes. All frameworks make the critical assumption that decision time depends on the perceptual representation of the stimulus as well as the architecture. As a consequence, nonadditivity of factors thought to affect different “stages” in the classical approach emerges within the current modeling approach. The nature of this influence is revealed through analytic investigations and simulation. Earlier empirical findings of failures of selective influence that have defied adequate explanation are reinterpreted in light of the present findings.     

How social and non-social information influence classification decisions: A computational modelling approach

Social information such as observing others can improve performance in decision making. In particular, social information has been shown to be useful when finding the best solution on one’s own is difficult, costly, or dangerous. However, past research suggests that when making decisions people do not always consider other people’s behaviour when it is at odds with their own experiences. Furthermore, the cognitive processes guiding the integration of social information with individual experiences are still under debate. Here, we conducted two experiments to test whether information about other persons’ behaviour influenced people’s decisions in a classification task. Furthermore, we examined how social information is integrated with individual learning experiences by testing different computational models. Our results show that social information had a small but reliable influence on people’s classifications. The best computational model suggests that in categorization people first make up their own mind based on the non-social information, which is then updated by the social information.     

Strategic flexibility in response preparation: Effects of cue validity on reaction time and pupil dilation

This study examined the ability of participants to strategically adapt their level of response preparation to the predictive value of preparatory cues. Participants performed the finger-precuing task under three levels of cue validity: 100, 75 and 50% valid. Response preparation was indexed by means of reaction time (RT) and pupil dilation, the latter providing a psychophysiological index of invested effort. Results showed a systematic increase in RT benefits (generated by valid cues) and RT costs (generated by invalid cues) with increments in the predictive value of cues. Converging with these behavioural effects, pupil dilation also increased systematically with greater cue validity during the cue-stimulus interval, suggesting more effortful response preparation with increases in cue validity. Together, these findings confirm the hypothesis that response preparation is flexible and that it can be strategically allocated in proportion to the relative frequency of valid/invalid preparatory cues.     

Comparison selection: An approach to the study of consumer judgment and choice

We introduce an alternative perspective on the study of consumer judgment and decision making, which is based on the notion that judgment and choice problems consist of comparisons that decision makers might select. Our new perspective proposes that if we can predict the likelihood that particular comparisons will become focal in a judgment or choice task, we will be able to gain a better understanding of and anticipate the resulting effect. Building on related literatures, we propose that comparison selection is driven by the task's latitude of acceptance (LOA) and comparison fluency (i.e., the overall ease of making that comparison). The task's LOA curve represents the range and concentration of potentially acceptable comparisons, whereas comparison fluency refers to the salience and ease of making the comparison. We illustrate our approach using previously studied problems (e.g., choice, variety seeking, the “jacket and calculator” problem, and contingent valuation) as well as new empirical tests.     

The process of selective exposure: Why confirmatory information search weakens over time

The present research investigated whether the tendency to prefer decision-consistent to decision-inconsistent information after making a preliminary choice would vary during the sequential process of searching for additional pieces of decision-relevant information. Specifically, it was tested whether decision makers would be more confirmatory in their information evaluation and search at the commencement rather than end of an information search process. In fact, five studies revealed that participants exhibited stronger confirmatory tendencies in both information evaluation (Studies 2 and 5) and search (Studies 1, 3, and 4) immediately after making a preliminary decision compared to during the later stages of an information search process. With regard to the underlying mechanism, results further revealed that individuals appear to be more motivated to detect the best decision alternative at the beginning (as opposed to the end) of an information search process, which leads to increases in confirmatory information processing during these stages.     

Intra-individual reaction time variability in schizophrenia, depression and borderline personality disorder

Intra-individual reaction time variability (IIV) in neuropsychological task performance reflects short term fluctuations in performance. Increased IIV has been reported in patients with schizophrenia and could be related to a deficient neural timing mechanism, but the role of IIV in adult patients with other psychiatric disorders has not been established. Therefore, we compared IIV measures obtained in a Go/Nogo task from patients with schizophrenia, major depression and borderline personality disorder. IIV was increased for patients with schizophrenia. When correcting for differences in mean reaction time, depressive and borderline patients also showed increased IIV. Importantly, all groups showed a strong association between IIV and accuracy of task performance. This suggests that increased IIV might be a sensitive marker for the efficiency of top-down attentional control in all diagnostic groups. Aside from these similarities, the complete results including measures of IIV, mean reaction time and accuracy show differential patterns for patients with schizophrenia compared to those with borderline personality disorder or depression. These results are discussed with respect to common versus disorder-specific neural mechanisms underlying increased IIV.