Psychological reviewPub Date : 2024-10-01Epub Date: 2024-07-25DOI: 10.1037/rev0000466
Lauren C Fong, Anthea G Blunden, Paul M Garrett, Philip L Smith, Daniel R Little
{"title":"Unifying approaches to understanding capacity in change detection.","authors":"Lauren C Fong, Anthea G Blunden, Paul M Garrett, Philip L Smith, Daniel R Little","doi":"10.1037/rev0000466","DOIUrl":"10.1037/rev0000466","url":null,"abstract":"<p><p>To navigate changes within a highly dynamic and complex environment, it is crucial to compare current visual representations of a scene to previously formed representations stored in memory. This process of mental comparison requires integrating information from multiple sources to inform decisions about changes within the environment. In the present article, we combine a novel systems factorial technology change detection task (Blunden et al., 2022) with a set size manipulation. Participants were required to detect 0, 1, or 2 changes of low and high detectability between a memory and probe array of 1-4 spatially separated luminance discs. Analyses using systems factorial technology indicated that the processing architecture was consistent across set sizes but that capacity was always limited and decreased as the number of distractors increased. We developed a novel model of change detection based on the statistical principles of basic sampling theory (Palmer, 1990; Sewell et al., 2014). The sample size model, instantiated parametrically, predicts the architecture and capacity results a priori and quantitatively accounted for several key results observed in the data: (a) increasing set size acted to decrease sensitivity (<i>d</i>') in proportion to the square root of the number of items in the display; (b) the effect of redundancy benefited performance by a factor of the square root of the number of changes; and (c) the effect of change detectability was separable and independent of the sample size costs and redundancy benefits. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1266-1289"},"PeriodicalIF":5.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141760648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Psychological reviewPub Date : 2024-10-01Epub Date: 2024-09-19DOI: 10.1037/rev0000493
Jake Spicer, Jian-Qiao Zhu, Nick Chater, Adam N Sanborn
{"title":"How do people predict a random walk? Lessons for models of human cognition.","authors":"Jake Spicer, Jian-Qiao Zhu, Nick Chater, Adam N Sanborn","doi":"10.1037/rev0000493","DOIUrl":"10.1037/rev0000493","url":null,"abstract":"<p><p>Repeated forecasts of changing values are common in many everyday tasks, from predicting the weather to financial markets. A particularly simple and informative instance of such fluctuating values are <i>random walks</i>: Sequences in which each point is a random movement from only its preceding value, unaffected by any previous points. Moreover, random walks often yield basic rational forecasting solutions in which predictions of new values should repeat the most recent value, and hence replicate the properties of the original series. In previous experiments, however, we have found that human forecasters do not adhere to this standard, showing systematic deviations from the properties of a random walk such as excessive volatility and extreme movements between subsequent predictions. We suggest that such deviations reflect general statistical signatures of cognition displayed across multiple tasks, offering a window into underlying mechanisms. Using these deviations as new criteria, we here explore several cognitive models of forecasting drawn from various approaches developed in the existing literature, including Bayesian, error-based learning, autoregressive, and sampling mechanisms. These models are contrasted with human data from two experiments to determine which best accounts for the particular statistical features displayed by participants. We find support for sampling models in both aggregate and individual fits, suggesting that these variations are attributable to the use of inherently stochastic prediction systems. We thus argue that variability in predictions is strongly influenced by computational noise within the decision making process, with less influence from \"late\" noise at the output stage. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1069-1113"},"PeriodicalIF":5.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring the impact of multiple social cues to advance theory in person perception research.","authors":"Samuel A W Klein, Jeffrey W Sherman","doi":"10.1037/rev0000503","DOIUrl":"https://doi.org/10.1037/rev0000503","url":null,"abstract":"<p><p>Forming impressions of others is a fundamental aspect of social life. These impressions necessitate the integration of many and varied sources of information about other people, including social group memberships, apparent personality traits, inferences from observed behaviors, and so forth. However, methodological limitations have hampered progress in understanding this integration process. In particular, extant approaches have been unable to measure the independent contributions of multiple features to a given impression. In this article, after describing these limitations and their constraints on theory testing and development, we present a multinomial processing tree model as a computational solution to the problem. Specifically, the model distinguishes the contributions of multiple cues to social judgment. We describe an empirical demonstration of how applying the model can resolve long-standing debates among person perception researchers. Finally, we survey a variety of questions to which this approach can be profitably applied. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An entropy modulation theory of creative exploration.","authors":"Thomas T Hills, Yoed N Kenett","doi":"10.1037/rev0000511","DOIUrl":"https://doi.org/10.1037/rev0000511","url":null,"abstract":"<p><p>Compared to individuals who are rated as less creative, higher creative individuals tend to produce ideas more quickly and with more novelty-what we call faster-and-further phenomenology. This has traditionally been explained either as supporting an associative theory-based on differences in the structure of cognitive representations-or as supporting an executive theory-based on the principle that higher creative individuals utilize cognitive control to navigate their cognitive representations differently. Though extensive research demonstrates evidence of differences in semantic structure, structural explanations are limited in their ability to formally explain faster-and-further phenomenology. At the same time, executive abilities also correlate with creativity, but formal process models explaining how they contribute to faster-and-further phenomenology are lacking. Here, we introduce entropy modulation theory which integrates structure and process-based creativity accounts. Relying on a broad set of evidence, entropy modulation theory assumes that the difference between lower and higher creative individuals lies in the executive modulation of entropy during cognitive search (e.g., memory retrieval). With retrieval targets racing to reach an activation threshold, activation magnitude and variance both independently enhance the entropy of target retrieval and increase retrieval speed, reproducing the faster-and-further phenomenology. Thus, apparent differences in semantic structure can be produced via an entropy modulating retrieval process, which tunes cognitive entropy to mediate cognitive flexibility and the exploration-exploitation trade-off. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Emotion understanding as third-person appraisals: Integrating appraisal theories with developmental theories of emotion.","authors":"Tiffany Doan, Desmond C Ong, Yang Wu","doi":"10.1037/rev0000507","DOIUrl":"https://doi.org/10.1037/rev0000507","url":null,"abstract":"<p><p>Emotion understanding goes beyond recognizing emotional displays-it also involves reasoning about how people's emotions are affected by their subjective evaluations of what they experienced. Inspired by work in adults on cognitive appraisal theories of emotion, we propose a framework that can guide systematic investigations of how an adult-like, sophisticated understanding of emotion develops from infancy to adulthood. We integrate basic concepts of appraisal theories with developmental theories of emotion understanding and suggest that over development, young children construct an intuitive, theory-like understanding of other people's emotions that is structurally similar to appraisal theories. That is, children are increasingly able to evaluate other people's situations from those people's perspectives along various appraisal dimensions and use such third-person appraisals to understand those people's emotional responses to events. This \"third-person-appraisal\" framework can not only incorporate existing empirical findings but can also identify gaps in the literature, providing a guiding framework for systematically investigating the development of emotion understanding. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Efficient visual representations for learning and decision making.","authors":"Tyler Malloy, Chris R Sims","doi":"10.1037/rev0000498","DOIUrl":"https://doi.org/10.1037/rev0000498","url":null,"abstract":"<p><p>The efficient representation of visual information is essential for learning and decision making due to the complexity and uncertainty of the world, as well as inherent constraints on the capacity of cognitive systems. We hypothesize that biological agents learn to efficiently represent visual information in a manner that balances performance across multiple potentially competing objectives. In this article, we examine two such objectives: storing information in a manner that supports accurate recollection (maximizing veridicality) and in a manner that facilitates utility-based decision making (maximizing behavioral utility). That these two objectives may be in conflict is not immediately obvious. Our hypothesis suggests that neither behavior nor representation formation can be fully understood by studying either in isolation, with information processing constraints exerting an overarching influence. Alongside this hypothesis we develop a computational model of representation formation and behavior motivated by recent methods in machine learning and neuroscience. The resulting model explains both the beneficial aspects of human visual learning, such as fast acquisition and high generalization, as well as the biases that result from information constraints. To test this model, we developed two experimental paradigms, in decision making and learning, to evaluate how well the model's predictions match human behavior. A key feature of the proposed model is that it predicts the occurrence of commonly found biases in human decision making, resulting from the desire to form efficient representations of visual information that are useful for behavioral goals in learning and decision making and optimized under an information processing constraint. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learning emotion regulation: An integrative framework.","authors":"Rachael N Wright, R Alison Adcock, Kevin S LaBar","doi":"10.1037/rev0000506","DOIUrl":"https://doi.org/10.1037/rev0000506","url":null,"abstract":"<p><p>Improving emotion regulation abilities, a process that requires learning, can enhance psychological well-being and mental health. Empirical evidence suggests that emotion regulation can be learned-during development and the lifespan, and most explicitly in psychotherapeutic interventions and experimental training paradigms. There is little work however that directly addresses such learning mechanisms. The present article proposes that learning in specific components of emotion regulation-emotion goals, emotional awareness, and strategy selection-may drive skill learning and long-term changes in regulatory behavior. Associative learning (classical and instrumental conditioning) and social learning (including observational, instructed, or interpersonal emotion regulation processes) are proposed to function as underlying mechanisms, while reinforcement-learning models may be useful for quantifying how these learning systems operate. A framework for how people learn emotion regulation will guide basic science investigations and impact clinical interventions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rob Ranyard, Henry Montgomery, Ashley Luckman, Emmanouil Konstantinidis
{"title":"Violations of transitive preference: A comparison of compensatory and noncompensatory accounts.","authors":"Rob Ranyard, Henry Montgomery, Ashley Luckman, Emmanouil Konstantinidis","doi":"10.1037/rev0000502","DOIUrl":"https://doi.org/10.1037/rev0000502","url":null,"abstract":"<p><p>Violations of transitive preference can be accounted for by both the noncompensatory lexicographic semiorder heuristic and the compensatory additive difference model. However, the two have not been directly compared. Here, we fully develop a simplified additive difference (SAD) model, which includes a graphical analysis of precisely which parameter values are consistent with adherence to, or violation of, transitive preference, as specified by weak stochastic transitivity (WST) and triangle inequalities (TI). The model is compatible with compensatory, within-dimension evaluation. We also develop a stochastic difference threshold model that also predicts intransitive preferences and encompasses a stochastic lexicographic semiorder model. We apply frequentist methods to compare the goodness of fit of both of these models to Tversky's (1969) data and four replications and Bayes factor methods to determine the strength of evidence for each model. We find that the two methods of analysis converge and that, for two thirds of the participants for whom predictions can be made, one of these models predicting violations of WST has a good and the best fit and has strong Bayesian support relative to an encompassing model. Furthermore, for about 20% of all participants, the SAD model (consistent with violations of WST or TI) is significantly better-fitting and has stronger Bayesian support than the stochastic difference threshold model. Finally, Bayes factor analysis finds strong evidence against transitive models for most participants for whom the SAD model consistent with violation of WST or TI is strongly supported. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Orlando E Jorquera, Osvaldo M Farfán, Sergio N Galarce, Natalia A Cancino, Pablo D Matamala, Edgar H Vogel
{"title":"A formal analysis of the standard operating processes (SOP) and multiple time scales (MTS) theories of habituation.","authors":"Orlando E Jorquera, Osvaldo M Farfán, Sergio N Galarce, Natalia A Cancino, Pablo D Matamala, Edgar H Vogel","doi":"10.1037/rev0000504","DOIUrl":"https://doi.org/10.1037/rev0000504","url":null,"abstract":"<p><p>In this article, we compare two theories of habituation: the standard operating processes (SOP) and the multiple time scales (MTS) models. Both theories propose that habituation is due to a reduction in the difference between actual and remembered stimulation. Although the two approaches explain short-term habituation using a similar nonassociative mechanism based on a time-decaying memory of recent stimulus presentations, their understanding of retention of habituation or long-term habituation differs. SOP suggests that retention of habituation happens through associative retrieval from a long-term memory store, while MTS relies on the differential decay rate of a series of memory units. This essential difference implies that spontaneous recovery, which refers to the return of the response to levels above those reached during habituation, is predominantly a consequence of a mixture of decay and loss of association for SOP and exclusively of decay for MTS. We analyze these mechanisms conceptually and mathematically and demonstrate their functioning with computer simulations of conceptual and published experiments. We evaluate both theories regarding parsimony and explanatory power and propose potential experiments to evaluate their predictions. We provide MATLAB-Simulink and Python codes for the simulations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiaqi Huang, Jerome R Busemeyer, Zo Ebelt, Emmanuel M Pothos
{"title":"Bridging the gap between subjective probability and probability judgments: The quantum sequential sampler.","authors":"Jiaqi Huang, Jerome R Busemeyer, Zo Ebelt, Emmanuel M Pothos","doi":"10.1037/rev0000489","DOIUrl":"https://doi.org/10.1037/rev0000489","url":null,"abstract":"<p><p>One of the most important challenges in decision theory has been how to reconcile the normative expectations from Bayesian theory with the apparent fallacies that are common in probabilistic reasoning. Recently, Bayesian models have been driven by the insight that apparent fallacies are due to sampling errors or biases in estimating (Bayesian) probabilities. An alternative way to explain apparent fallacies is by invoking different probability rules, specifically the probability rules from quantum theory. Arguably, quantum cognitive models offer a more unified explanation for a large body of findings, problematic from a baseline classical perspective. This work addresses two major corresponding theoretical challenges: first, a framework is needed which incorporates both Bayesian and quantum influences, recognizing the fact that there is evidence for both in human behavior. Second, there is empirical evidence which goes beyond any current Bayesian and quantum model. We develop a model for probabilistic reasoning, seamlessly integrating both Bayesian and quantum models of reasoning and augmented by a sequential sampling process, which maps subjective probabilistic estimates to observable responses. Our model, called the Quantum Sequential Sampler, is compared to the currently leading Bayesian model, the Bayesian Sampler (J. Zhu et al., 2020) using a new experiment, producing one of the largest data sets in probabilistic reasoning to this day. The Quantum Sequential Sampler embodies several new components, which we argue offer a more theoretically accurate approach to probabilistic reasoning. Moreover, our empirical tests revealed a new, surprising systematic overestimation of probabilities. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}