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Psychological Review - Vol 125, Iss 1

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Psychological Review Psychological Review publishes articles that make important theoretical contributions to any area of scientific psychology.
Copyright 2018 American Psychological Association
  • Overrepresentation of extreme events in decision making reflects rational use of cognitive resources.
    People’s decisions and judgments are disproportionately swayed by improbable but extreme eventualities, such as terrorism, that come to mind easily. This article explores whether such availability biases can be reconciled with rational information processing by taking into account the fact that decision makers value their time and have limited cognitive resources. Our analysis suggests that to make optimal use of their finite time decision makers should overrepresent the most important potential consequences relative to less important, put potentially more probable, outcomes. To evaluate this account, we derive and test a model we call utility-weighted sampling. Utility-weighted sampling estimates the expected utility of potential actions by simulating their outcomes. Critically, outcomes with more extreme utilities have a higher probability of being simulated. We demonstrate that this model can explain not only people’s availability bias in judging the frequency of extreme events but also a wide range of cognitive biases in decisions from experience, decisions from description, and memory recall. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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  • Internal and external sources of variability in perceptual decision-making.
    It is important to identify sources of variability in processing to understand decision-making in perception and cognition. There is a distinction between internal and external variability in processing, and double-pass experiments have been used to estimate their relative contributions. In these and our experiments, exact perceptual stimuli are repeated later in testing, and agreement on the 2 trials is examined to see if it is greater than chance. In recent research in modeling decision processes, some models implement only (internal) variability in the decision process whereas others explicitly represent multiple sources of variability. We describe 5 perceptual double-pass experiments that show greater than chance agreement, which is inconsistent with models that assume internal variability alone. Estimates of total trial-to-trial variability in the evidence accumulation (drift) rate (the decision-relevant stimulus information) were estimated from fits of the standard diffusion decision-making model to the data. The double-pass procedure provided estimates of how much of this total variability was systematic and dependent on the stimulus. These results provide the first behavioral evidence independent of model fits for trial-to-trial variability in drift rate in tasks used in examining perceptual decision-making. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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  • Neural scaling laws for an uncertain world.
    Autonomous neural systems must efficiently process information in a wide range of novel environments which may have very different statistical properties. We consider the problem of how to optimally distribute receptors along a 1-dimensional continuum consistent with the following design principles. First, neural representations of the world should obey a neural uncertainty principle—making as few assumptions as possible about the statistical structure of the world. Second, neural representations should convey, as much as possible, equivalent information about environments with different statistics. The results of these arguments resemble the structure of the visual system and provide a natural explanation of the behavioral Weber-Fechner law, a foundational result in psychology. Because the derivation is extremely general, this suggests that similar scaling relationships should be observed not only in sensory continua, but also in neural representations of “cognitive” 1-dimensional quantities such as time or numerosity. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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  • Task conflict and proactive control: A computational theory of the Stroop task.
    The Stroop task is a central experimental paradigm used to probe cognitive control by measuring the ability of participants to selectively attend to task-relevant information and inhibit automatic task-irrelevant responses. Research has revealed variability in both experimental manipulations and individual differences. Here, we focus on a particular source of Stroop variability, the reverse-facilitation (RF; faster responses to nonword neutral stimuli than to congruent stimuli), which has recently been suggested as a signature of task conflict. We first review the literature that shows RF variability in the Stroop task, both with regard to experimental manipulations and to individual differences. We suggest that task conflict variability can be understood as resulting from the degree of proactive control that subjects recruit in advance of the Stroop stimulus. When the proactive control is high, task conflict does not arise (or is resolved very quickly), resulting in regular Stroop facilitation. When proactive control is low, task conflict emerges, leading to a slow-down in congruent and incongruent (but not in neutral) trials and thus to Stroop RF. To support this suggestion, we present a computational model of the Stroop task, which includes the resolution of task conflict and its modulation by proactive control. Results show that our model (a) accounts for the variability in Stroop-RF reported in the experimental literature, and (b) solves a challenge to previous Stroop models—their ability to account for reaction time distributional properties. Finally, we discuss theoretical implications to Stroop measures and control deficits observed in some psychopathologies. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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  • Action and perception in literacy: A common-code for spelling and reading.
    There is strong evidence that reading and spelling in alphabetical scripts depend on a shared representation (common-coding). However, computational models usually treat the two skills separately, producing a wide variety of proposals as to how the identity and position of letters is represented. This article treats reading and spelling in terms of the common-coding hypothesis for perception-action coupling. Empirical evidence for common representations in spelling-reading is reviewed. A novel version of the Start-End Competitive Queuing (SE-CQ) spelling model is introduced, and tested against the distribution of positional errors in Letter Position Dysgraphia, data from intralist intrusion errors in spelling to dictation, and dysgraphia because of nonperipheral neglect. It is argued that no other current model is equally capable of explaining this range of data. To pursue the common-coding hypothesis, the representation used in SE-CQ is applied, without modification, to the coding of letter identity and position for reading and lexical access, and a lexical matching rule for the representation is proposed (Start End Position Code model, SE-PC). Simulations show the model’s compatibility with benchmark findings from form priming, its ability to account for positional effects in letter identification priming and the positional distribution of perseverative intrusion errors. The model supports the view that spelling and reading use a common orthographic description, providing a well-defined account of the major features of this representation. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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  • Subjects adjust criterion on errors in perceptual decision tasks.
    The optimal strategy in detection theory is to partition the decision axis at a criterion C, labeling all events that score above C “Signal”, and all those that fall below “Noise.” The optimal position of C, C*, depends on signal probability and payoffs. If observers place their criterion at some place other than C*, they suffer a loss in the Expected Value (EV) of payoffs over the course of many decisions. We provide an explicit equation for the degree of loss, where it is shown that the falloff in value will be steep in contexts of good discrimination and will be a flatter gradient in contexts of poor discrimination. It is these gradients of loss in EV that, in theory, drive C toward C*, strongly when discrimination is good, weakly when discrimination is poor. When signal probabilities or distributions variances are unequal, the basins of attraction are asymmetric, so that dynamic adjustments in C will be asymmetric, and thus, as we show, will leave it biased. We address our analysis to acquisition speed, response variability, discrimination reversal and other aspects of discriminated performance. In the final section, we develop an error correction model that predicts empirically observed deviations from C* that are inconsistent with the standard model, but follow from the proposed model given knowledge of d′. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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