A model of the go/no-go task

In this article, the first explicit, theory-based comparison of 2-choice and go/no-go variants of 3 experimental tasks is presented. Prior research has questioned whether the underlying core-information processing is different for the 2 variants of a task or whether they differ mostly in response demands. The authors examined 4 different diffusion models for the go/no-go variant of each task along with a standard diffusion model for the 2-choice variant (R. Ratcliff, 1978). The 2-choice and the go/no-go models were fit to data from 4 lexical decision experiments, 1 numerosity discrimination experiment, and 1 recognition memory experiment, each with 2-choice and go/no-go variants. The models that assumed an implicit decision criterion for no-go responses produced better fits than models that did not. The best model was one in which only response criteria and the nondecisional components of processing changed between the 2 variants, supporting the view that the core information on which decisions are based is not different between them.     

Learning to allocate limited time to decisions with different expected outcomes

The goal of this article is to investigate how human participants allocate their limited time to decisions with different properties. We report the results of two behavioral experiments. In each trial of the experiments, the participant must accumulate noisy information to make a decision. The participants received positive and negative rewards for their correct and incorrect decisions, respectively. The stimulus was designed such that decisions based on more accumulated information were more accurate but took longer. Therefore, the total outcome that a participant could achieve during the limited experiments’ time depended on her “decision threshold”, the amount of information she needed to make a decision. In the first experiment, two types of trials were intermixed randomly: hard and easy. Crucially, the hard trials were associated with smaller positive and negative rewards than the easy trials. A cue presented at the beginning of each trial would indicate the type of the upcoming trial. The optimal strategy was to adopt a small decision threshold for hard trials. The results showed that several of the participants did not learn this simple strategy. We then investigated how the participants adjusted their decision threshold based on the feedback they received in each trial. To this end, we developed and compared 10 computational models for adjusting the decision threshold. The models differ in their assumptions on the shape of the decision thresholds and the way the feedback is used to adjust the decision thresholds. The results of Bayesian model comparison showed that a model with time-varying thresholds whose parameters are updated by a reinforcement learning algorithm is the most likely model. In the second experiment, the cues were not presented. We showed that the optimal strategy is to use a single time-decreasing decision threshold for all trials. The results of the computational modeling showed that the participants did not use this optimal strategy. Instead, they attempted to detect the difficulty of the trial first and then set their decision threshold accordingly.     

On the dangers of averaging across observers when comparing decision bound models and generalized context models of categorization

Averaging across observers is common in psychological research. Often, averaging reduces the measurement error and, thus, does not affect the inference drawn about the behavior of individuals. However, in other situations, averaging alters the structure of the data qualitatively, leading to an incorrect inference about the behavior of individuals. In this research, the influence of averaging across observers on the fits of decision bound models (Ashby, 1992a) and generalized context models (GCM; Nosofsky, 1986) was investigated through Monte Carlo simulation of a variety of categorization conditions, perceptual representations, and individual difference assumptions and in an experiment. The results suggest that (1) averaging has little effect when the GCM is the correct model, (2) averaging often improves the fit of the GCM and worsens the fit of the decision bound model when the decision bound model is the correct model, (3) the GCM is quite flexible and, under many conditions, can mimic the predictions of the decision bound model, whereas the decision bound model is generally unable to mimic the predictions of the GCM, (4) the validity of the decision bound model's perceptual representation assumption can have a large effect on the inference drawn about the form of the decision bound, and (5) the experiment supported the claim that averaging improves the fit of the GCM. These results underscore the importance of performing single-observer analysis if one is interested in understanding the categorization performance of individuals.     

决策过程中的调节匹配效应及其机制

以大学生为被试,运用实验法探讨了决策过程中调节定向与信息搜索模式之间的匹配效应及其机制。结果显示：(1) 促进定向组被试决策时更偏好基于属性的信息搜索模式,而预防定向组被试决策时更偏好基于选项的信息搜索模式;(2)当两种调节定向组被试分别使用各自所偏好的信息搜索模式制定决策时,达成了调节匹配,相比调节不匹配,这种匹配使被试对其所做选择给出了更积极的评价,即出现了调节匹配效应;(3)加工流畅性可以部分地解释这种调节匹配效应。     

A diffusion model account of normal and impaired readers

Acquired aphasics and dyslexics with even very profound word reading impairments have been shown to perform relatively well on the lexical decision task, but direct contrasts with unimpaired participant's data is often complicated by extremely long reaction times for patient data. The dissociation between lexical decision and word naming performance shown by these patients is of theoretical importance, and here we present an analysis of processing underlying the lexical decision task. We are able to determine what aspects of performance are affected by acquired aphasics in the lexical decision task. We fit lexical decision data from aphasic patients and from normal readers with a sequential sampling model (the diffusion model) that simultaneously considers reaction time and accuracy. This model provides a powerful means of assessing processes involved in impaired and unimpaired lexical decision. Our results suggest that lexical decision may tap impairments at both a linguistic and a nonlinguistic level. These impairments combine to make patients produce the exaggerated lexical decision reaction times typical of neurolinguistic patients: we demonstrate that patients have compromised decision and nondecision processes but that the quality of the information upon which they base their decisions is not much different from that of unimpaired participants.     

时间距离对于验证性信息加工的影响

研究基于解释水平理论考察时间距离对于验证性信息加工的影响, 即在个体和组织决策情境中, 人们倾向于偏好选择和高估与自身观点和决策相一致的信息, 而不是非一致性信息。通过4个情境决策实验, 研究结果一致表明近期决策会提高信息搜寻和评估中的验证偏差, 而远期决策会降低它们的验证偏差, 知觉到的决策确定性在其中起到部分中介作用(实验1b)。解释水平(实验2)和期许性/可行性表征(实验3)分别在时间距离对验证性信息加工的影响中起到调节作用, 结果依次表明在低解释水平(高可行性-低期许性特征)条件下, 时间距离与验证性信息加工的负相关关系会得到显著增强, 而在高解释水平(高期许性-低可行性特征)条件下, 时间距离与验证性信息加工的负相关关系会得到显著降低。     

A diffusion model account of masking in two-choice letter identification

The diffusion model developed by R. Ratcliff (1978, 1981, 1985, 1988) for 2-choice decisions was applied to data from 2 letter identification experiments. In the experiments, stimulus letters were displayed and then masked, and the stimulus onset asynchrony between letter and mask was manipulated to vary accuracy from near chance to near ceiling. A standard reaction time procedure was used in one experiment and a deadline procedure in the other. Two hypotheses about the effect of masking on the information provided to the decision process were contrasted: (a) The output of perception to the decision process varies with time, so that the information used by the decision process rises and falls, reflecting the stimulus onset and mask onset. (b) The output of perception to the decision is constant over time, reflecting information integrated over the time between the stimulus and mask onsets. The data were well fit by the diffusion model only with the assumption of constant information over time.     

Two interpretations of the discrimination parameter

In this paper we propose two interpretations for the discrimination parameter in the two-parameter logistic model (2PLM). The interpretations are based on the relation between the 2PLM and two stochastic models. In the first interpretation, the 2PLM is linked to a diffusion model so that the probability of absorption equals the 2PLM. The discrimination parameter is the distance between the two absorbing boundaries and therefore the amount of information that has to be collected before a response to an item can be given. For the second interpretation, the 2PLM is connected to a specific type of race model. In the race model, the discrimination parameter is inversely related to the dependency of the information used in the decision process. Extended versions of both models with person-to-person variability in the difficulty parameter are considered. When fitted to a data set, it is shown that a generalization of the race model that allows for dependency between choices and response times (RTs) is the best-fitting model.     

Modeling response signal and response time data

The diffusion model (Ratcliff, 1978) and the leaky competing accumulator model (LCA, Usher & McClelland, 2001) were tested against two-choice data collected from the same subjects with the standard response time procedure and the response signal procedure. In the response signal procedure, a stimulus is presented and then, at one of a number of experimenter-determined times, a signal to respond is presented. The models were fit to the data from the two procedures simultaneously under the assumption that responses in the response signal procedure were based on a mixture of decision processes that had already terminated at response boundaries before the signal and decision processes that had not yet terminated. In the latter case, decisions were based on partial information in one variant of each model or on guessing in a second variant. Both variants of the diffusion model fit the data well and both fit better than either variant of the LCA model, although the differences in numerical goodness-of-fit measures were not large enough to allow decisive selection between the models.     

Modeling simple driving tasks with a one-boundary diffusion model

A one-boundary diffusion model was applied to the data from two experiments in which subjects were performing a simple simulated driving task. In the first experiment, the same subjects were tested on two driving tasks using a PC-based driving simulator and the psychomotor vigilance test. The diffusion model fit the response time distributions for each task and individual subject well. Model parameters were found to correlate across tasks, which suggests that common component processes were being tapped in the three tasks. The model was also fit to a distracted driving experiment of Cooper and Strayer (Human Factors, 50, 893–902, 2008). Results showed that distraction altered performance by affecting the rate of evidence accumulation (drift rate) and/or increasing the boundary settings. This provides an interpretation of cognitive distraction whereby conversing on a cell phone diverts attention from the normal accumulation of information in the driving environment.     

Response time modeling reveals multiple contextual cuing mechanisms

Contextual cuing refers to a response time (RT) benefit that occurs when observers search through displays that have been repeated over the course of an experiment. Although it is generally agreed that contextual cuing arises via an associative learning mechanism, there is uncertainty about the type(s) of process(es) that allow learning to influence RT. We contrast two leading accounts of the contextual cuing effect that differ in terms of the general process that is credited with producing the effect. The first, the expedited search account, attributes the cuing effect to an increase in the speed with which the target is acquired. The second, the decision threshold account, attributes the cuing effect to a reduction in the response threshold used by observers when making a subsequent decision about the target (e.g., judging its orientation). We use the diffusion model to contrast the quantitative predictions of these two accounts at the level of individual observers. Our use of the diffusion model allows us to also explore a novel decision-level locus of the cuing effect based on perceptual learning. This novel account attributes the RT benefit to a perceptual learning process that increases the quality of information used to drive the decision process. Our results reveal both individual differences in the process(es) involved in contextual cuing but also identify several striking regularities across observers. We find strong support for both the decision threshold account as well as the novel perceptual learning account. We find relatively weak support for the expedited search account.     

害羞者对模糊情境信息的解释偏向

以模糊情境句子和形容词为刺激材料,分别采用文本材料范式和改编的词汇情境联接范式,对害羞者的延时解释和即时解释偏向特点进行探讨。结果发现：害羞者对模糊情境信息不仅缺乏积极的即时解释偏向特点,而且也缺乏积极的延时解释偏向特点;害羞者未表现出消极的即时和延时解释偏向特点。研究表明害羞者可能是社交焦虑的前期阶段,对害羞者的干预可以通过引导其积极的解释偏向的方式来实现。     

Repetition and practice effects in a lexical decision task

Ss classified visually presented verbal units into the categories “in your vocabulary” or “not in your vocabulary.” The primary concern of the experiment was to determine if making a prior decision on a given item affects the latency of a subsequent lexical decision for the same item. Words of both high and low frequency showed a systematic reduction in the latency of a lexical decision as a consequence of prior decisions (priming) but did not show any reduction due to nonspecific practice effects. Nonwords showed no priming effect but did show shorter latencies due to nonspecific practice. The results also indicated that many (at least 36) words can be in the primed state simultaneously and that the effect persists for at least 10 min. The general interpretation was that priming produces an alteration in the representation of a word in memory and can facilitate the terminal portion of the memory search process which is assumed to be random.     

Strategy generalization across orientation tasks: testing a computational cognitive model

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find-on-map) or within an egocentric view of a space (find-in-scene). A general strategy instantiated in a computational cognitive model of the find-on-map task, based on the results from Gunzelmann and Anderson (2006) , was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps.     

Group communication and decision-making strategies

In daily life, people frequently make inferences about current and future states of the world. Most of these inferences are not made individually, but by exchanging information about which strategies could be used with other people. In an experiment, we analyzed whether exchanging information socially increased the probability of selecting the most adaptive strategy. In our experiment, take-the-best (TTB; Gigerenzer & Goldstein, 1996), a simple heuristic that employs one-reason decision making, achieved the highest payoff. Results showed that the fit of TTB increased substantially across trial blocks when participants were allowed to exchange information with other group members. In contrast, when participants made inferences individually, they did not select the most adaptive strategy even after seven trial blocks. Overall, our results support the hypothesis that group communication increases the likelihood that participants select the most adaptive strategy for making inferences.     

Mapping the perceptual structure of rectangles through goodness-of-fit ratings

Three experiments were carried out to investigate the internal structure of a rectangular frame to test Arnheim's (1974 Art and Visual Perception, 1988 The Power of the Center) proposals about its 'structural skeleton'. Observers made subjective ratings of how well a small probe circle fit within a rectangle at different interior positions. In experiment 1, ratings of 77 locations were highest in the center, decreased with distance from the center, greatly elevated along vertical and horizontal symmetry axes, and somewhat elevated along the local symmetry axes. A linear regression model with six symmetry-related factors accounted for 95% of the variance. In experiment 2 we measured perceived fit along local symmetry axes versus global diagonals near the corners to determine which factor was relevant. 2AFC probabilities were elevated only along the local symmetry axes and were higher when the probe was closer to the vertex. In experiment 3 we examined the effect of dividing a rectangular frame into two rectangular 'subframes' using an additional line. The results show that the primary determinant of good fit is the position of the target circle within the local subframes. In general, the results are consistent with Arnheim's proposals about the internal structure of a rectangular frame, but an alternative interpretation is offered in terms of the Gestalt concept of figural goodness.     

How race affects evidence accumulation during the decision to shoot

The biasing role of stereotypes is a central theme in social cognition research. For example, to understand the role of race in police officers’ decisions to shoot, participants have been shown images of Black and White males and instructed to shoot only if the target is holding a gun. Findings show that Black targets are shot more frequently and more quickly than Whites. The decision to shoot has typically been modeled and understood as a signal detection process in which a sample of information is compared against a criterion, with the criterion set for Black targets being lower. We take a different approach, modeling the decision to shoot as a dynamic process in which evidence is accumulated over time until a threshold is reached. The model accounts for both the choice and response time data for both correct and incorrect decisions using a single set of parameters. Across four studies, this dynamic perspective revealed that the target’s race did not create an initial bias to shoot Black targets. Instead, race impacted the rate of evidence accumulation with evidence accumulating faster to shoot for Black targets. Some participants also tended to be more cautious with Black targets, setting higher decision thresholds. Besides providing a more cohesive and richer account of the decision to shoot or not, the dynamic model suggests interventions that may address the use of race information in decisions to shoot and a means to measure their effectiveness.     

Frontal cortex electrophysiology in reward- and punishment-related feedback processing during advice-guided decision making: An interleaved EEG-DC stimulation study

During decision making, individuals are prone to rely on external cues such as expert advice when the outcome is not known. However, the electrophysiological correlates associated with outcome uncertainty and the use of expert advice are not completely understood. The feedback-related negativity (FRN), P3a, and P3b are event-related brain potentials (ERPs) linked to dissociable stages of feedback and attentional processing during decision making. Even though these ERPs are influenced by both reward- and punishment-related feedback, it remains unclear how extrinsic information during uncertainty modulates these brain potentials. In this study, the effects of advice cues on decision making were investigated in two separate experiments. In the first experiment, electroencephalography (EEG) was recorded in healthy volunteers during a decision-making task in which the participants received reward or punishment feedback preceded by novice, amateur, or expert advice. The results showed that the P3a component was significantly influenced by the subjective predictive value of an advice cue, whereas the FRN and P3b were unaffected by the advice cues. In the second, sham-controlled experiment, cathodal transcranial direct current stimulation (ctDCS) was administered in conjunction with EEG in order to explore the direct contributions of the frontal cortex to these brain potentials. Results showed no significant change in either advice-following behavior or decision times. However, ctDCS did decrease FRN amplitudes as compared to sham, with no effect on the P3a or P3b. Together, these findings suggest that advice information may act primarily on attention allocation during feedback processing, whereas the electrophysiological correlates of the detection and updating of internal prediction models are not affected.     

A pattern recognition account of decision making

In the domain of pattern recognition, experiments have shown that perceivers integrate multiple sources of information in an optimal manner. In contrast, other research has been interpreted to mean that decision making is nonoptimal. As an example, Tversky and Kahneman (1983) have shown that subjects commit a conjunction fallacy because they judge it more likely that a fictitious person named Linda is a bank teller and a feminist than just a bank teller. This judgment supposedly violates probability theory, because the probability of two events can never be greater than the probability of either event alone. The present research tests the hypothesis that subjects interpret this judgment task as a pattern recognition task. If this hypothesis is correct, subjects’ judgments should be described accurately by the fuzzy logical model of perception (FLMP)—a successful model of pattern recognition. In the first experiment, the Linda task was extended to an expanded factorial design with five vocations and five avocations. The probability ratings were described well by the FLMP and described poorly by a simple probability model. The second experiment included (1) two fictitious people, Linda and Joan, as response alternatives and (2) both ratings and categorization judgments. Although the ratings were accurately described by both the FLMP and an averaging of the sources of information, the categorization judgments were described better by the FLMP. These results reveal important similarities in recognizing patterns and in decision making. Given that the FLMP is an optimal method for combining multiple sources of information, the probability judgments appear to be optimal in the same manner as pattern-recognition judgments.