Psychological reviewPub Date : 2024-11-01Epub Date: 2024-09-19DOI: 10.1037/rev0000502
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":"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":"1392-1410"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","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}
Psychological reviewPub Date : 2024-11-01Epub Date: 2023-09-21DOI: 10.1037/rev0000446
Sudeep Bhatia
{"title":"Inductive reasoning in minds and machines.","authors":"Sudeep Bhatia","doi":"10.1037/rev0000446","DOIUrl":"10.1037/rev0000446","url":null,"abstract":"<p><p>Induction-the ability to generalize from existing knowledge-is the cornerstone of intelligence. Cognitive models of human induction are largely limited to toy problems and cannot make quantitative predictions for the thousands of different induction arguments that have been studied by researchers, or to the countless induction arguments that could be encountered in everyday life. Leading large language models (LLMs) go beyond toy problems but fail to mimic observed patterns of human induction. In this article, we combine rich knowledge representations obtained from LLMs with theories of human inductive reasoning developed by cognitive psychologists. We show that this integrative approach can capture several benchmark empirical findings on human induction and generate human-like responses to natural language arguments with thousands of common categories and properties. These findings shed light on the cognitive mechanisms at play in human induction and show how existing theories in psychology and cognitive science can be integrated with new methods in artificial intelligence, to successfully model high-level human cognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1373-1391"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41165565","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 : 2024-11-01Epub Date: 2024-07-25DOI: 10.1037/rev0000486
Gregory E Cox
{"title":"Dynamic retrieval of events and associations from memory: An integrated account of item and associative recognition.","authors":"Gregory E Cox","doi":"10.1037/rev0000486","DOIUrl":"10.1037/rev0000486","url":null,"abstract":"<p><p>Memory theories distinguish between item and associative information, which are engaged by different tasks: item recognition uses item information to decide whether an event occurred in a particular context; associative recognition uses associative information to decide whether two events occurred together. Associative recognition is slower and less accurate than item recognition, suggesting that item and associative information may be represented in different forms and retrieved using different processes. Instead, I show how a dynamic model (Cox & Criss, 2020; Cox & Shiffrin, 2017) accounts for accuracy and response time distributions in both item and associative recognition with the same set of representations and processes. Item and associative information are both represented as vectors of features. Item and associative recognition both depend on comparing traces in memory with probes of memory in which item and associative features gradually accumulate. Associative features are slower to accumulate, but largely because they emerge from conjunctions of already-accumulated item features. I apply the model to data from 453 participants, each of whom performed an item and performed associative recognition following identical study conditions (Cox et al., 2018). Comparisons among restricted versions of the model show that its account of associative feature formation, coupled with limits on the rate at which features accumulate from multiple items, explains how and why the dynamics of associative recognition differ from those of item recognition even while both tasks rely on the same underlying representations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1297-1336"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141760645","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}
Donald J Robinaugh, Jonas M B Haslbeck, Lourens J Waldorp, Jolanda J Kossakowski, Eiko I Fried, Alexander J Millner, Richard J McNally, Oisín Ryan, Jill de Ron, Han L J van der Maas, Egbert H van Nes, Marten Scheffer, Kenneth S Kendler, Denny Borsboom
{"title":"Advancing the network theory of mental disorders: A computational model of panic disorder.","authors":"Donald J Robinaugh, Jonas M B Haslbeck, Lourens J Waldorp, Jolanda J Kossakowski, Eiko I Fried, Alexander J Millner, Richard J McNally, Oisín Ryan, Jill de Ron, Han L J van der Maas, Egbert H van Nes, Marten Scheffer, Kenneth S Kendler, Denny Borsboom","doi":"10.1037/rev0000515","DOIUrl":"https://doi.org/10.1037/rev0000515","url":null,"abstract":"<p><p>The network theory of psychopathology posits that mental disorders are systems of mutually reinforcing symptoms. This framework has proven highly generative but does not specify precisely how any specific mental disorder operates as such a system. Cognitive behavioral theories of mental disorders provide considerable insight into how these systems may operate. However, the development of cognitive behavioral theories has itself been stagnant in recent years. In this article, we advance both theoretical frameworks by developing a network theory of panic disorder rooted in cognitive behavioral theory and formalized as a computational model. We use this computational model to evaluate the theory's ability to explain five fundamental panic disorder-related phenomena. Our results demonstrate that the network theory of panic disorder can explain core panic disorder phenomena. In addition, by formalizing this theory as a computational model and using the model to evaluate the theory's implications, we reveal gaps in the empirical literature and shortcomings in theories of panic disorder. We use these limitations to develop a novel, theory-driven agenda for panic disorder research. This agenda departs from current research practices and places its focus on (a) addressing areas in need of more rigorous descriptive research, (b) investigating novel phenomena predicted by the computational model, and (c) ongoing collaborative development of formal theories of panic disorder, with explanation as a central criterion for theory evaluation. We conclude with a discussion of the implications of this work for research investigating mental disorders as complex systems. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":"131 6","pages":"1482-1508"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142882590","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 : 2024-11-01Epub Date: 2024-09-19DOI: 10.1037/rev0000490
Ed O'Brien
{"title":"A flexible threshold theory of change perception in self, others, and the world.","authors":"Ed O'Brien","doi":"10.1037/rev0000490","DOIUrl":"10.1037/rev0000490","url":null,"abstract":"<p><p>I propose a flexible threshold theory of change perception in self and social judgment. Traditionally, change perception is viewed as a basic cognitive process entailing the act of discriminating informational differences. This article takes a more dynamic view of change perception, highlighting people's motivations in interpreting those differences. Specifically, I propose people's change perceptions depend not only on the salience and quality of the evidence for change but they also depend on the adaptation implications of the change, as people are sensitive to whether their prompted response would be worth it. Variables that exacerbate perceived adaptation implications should thus lead people to contract their change perception thresholds (people should become less open to concluding things have changed and so less likely to act), while variables that alleviate perceived adaptation implications should thus lead people to expand their change perception thresholds (people should become more open to concluding things have changed and so more likely to act), all else equal in the evidence. Moreover, these effects should emerge for perceiving declines and improvements alike so long as change bears on adaptation implications. I review support for these proposals and use the theory to generate novel predictions, contributions, and applications. The theory can explain anew why people respond (or fail to respond) to changing climates and economies, worsening personal health, growing social progress, and many other self and social phenomena. Change perception is more than an act of discriminating differences-it also entails people's threshold judgments of whether and how these differences matter. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1435-1458"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142294104","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 : 2024-11-01Epub Date: 2024-06-06DOI: 10.1037/rev0000492
Rizqy Amelia Zein, Marlene Sophie Altenmüller, Mario Gollwitzer
{"title":"Longtime nemeses or cordial allies? How individuals mentally relate science and religion.","authors":"Rizqy Amelia Zein, Marlene Sophie Altenmüller, Mario Gollwitzer","doi":"10.1037/rev0000492","DOIUrl":"10.1037/rev0000492","url":null,"abstract":"<p><p>Science and religion are influential social forces, and their interplay has been subject to many public and scholarly debates. The present article addresses how people mentally conceptualize the relationship between science and religion and how these conceptualizations can be systematized. To that end, we provide a comprehensive, integrative review of the pertinent literature. Moreover, we discuss how cognitive (in particular, epistemic beliefs) and motivational factors (in particular, epistemic needs, identity, and moral beliefs), as well as personality and contextual factors (e.g., rearing practices and cross-cultural exposure), are related to these mental conceptualizations. And finally, we provide a flowchart detailing the psychological processes leading to these mental conceptualizations. A comprehensive understanding of how individuals perceive the science-religion relationship is interesting in and of itself and practically relevant for managing societal challenges, such as science denial. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1459-1481"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261228","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 : 2024-11-01Epub Date: 2024-07-25DOI: 10.1037/rev0000488
James Antony, Xiaonan L Liu, Yicong Zheng, Charan Ranganath, Randall C O'Reilly
{"title":"Memory out of context: Spacing effects and decontextualization in a computational model of the medial temporal lobe.","authors":"James Antony, Xiaonan L Liu, Yicong Zheng, Charan Ranganath, Randall C O'Reilly","doi":"10.1037/rev0000488","DOIUrl":"10.1037/rev0000488","url":null,"abstract":"<p><p>Some neural representations gradually change across multiple timescales. Here we argue that modeling this \"drift\" could help explain the spacing effect (the long-term benefit of distributed learning), whereby differences between stored and current temporal context activity patterns produce greater error-driven learning. We trained a neurobiologically realistic model of the entorhinal cortex and hippocampus to learn paired associates alongside temporal context vectors that drifted between learning episodes and/or before final retention intervals. In line with spacing effects, greater drift led to better model recall after longer retention intervals. Dissecting model mechanisms revealed that greater drift increased error-driven learning, strengthened weights in slower drifting temporal context neurons (temporal abstraction), and improved direct cue-target associations (decontextualization). Intriguingly, these results suggest that decontextualization-generally ascribed only to the neocortex-can occur within the hippocampus itself. Altogether, our findings provide a mechanistic formalization for established learning concepts such as spacing effects and errors during learning. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1337-1372"},"PeriodicalIF":5.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141760646","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":"A theory of flexible multimodal synchrony.","authors":"Ilanit Gordon,Alon Tomashin,Oded Mayo","doi":"10.1037/rev0000495","DOIUrl":"https://doi.org/10.1037/rev0000495","url":null,"abstract":"Dominant theoretical accounts of interpersonal synchrony, the temporal coordination of biobehavioral processes between several individuals, have employed a linear approach, generally considering synchrony as a positive state, and utilizing aggregate scores. However, synchrony is known to take on a dynamical form with continuous shifts in its timeline. Acting as one continuously, is not always the optimal state, due to an intrinsic tension between individualistic and synergistic forms of action that exist in many social situations. We propose an alternative theory of flexible multimodal synchrony which highlights context as a key component that defines \"pulls\" toward synchrony and \"pulls\" toward segregation inherent to the social situation. Traitlike individual differences and relationship variables then sensitize individuals to these contextual \"pulls.\" In this manner, context, individual differences, and relationship variables provide the backdrop to the emergence of flexible and dynamical synchrony patterns, which we consider adaptive, in several modalities-behavioral, physiological, and neural. We point to three consequences of synchrony patterns: social-, task, and self-oriented. We discuss multimodal associations that arise in different contexts considering the theory and delineate hypotheses that emanate from the theory. We then provide two empirical proofs-of-concept: First, we show how individual differences modulate the effect of context on synchrony's outcomes in a novel dyadic motor game. Second, we reanalyze previously reported data, to show how a \"flexibility\" approach to synchrony data analysis improves predictive ability when testing for synchrony's effects on social cohesion. We provide ways to standardize the characterization of context and guidelines for future synchrony research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":"26 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142490937","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}
Gabriela Lunansky, George A Bonanno, Tessa F Blanken, Claudia D van Borkulo, Angélique O J Cramer, Denny Borsboom
{"title":"Bouncing back from life's perturbations: Formalizing psychological resilience from a complex systems perspective.","authors":"Gabriela Lunansky, George A Bonanno, Tessa F Blanken, Claudia D van Borkulo, Angélique O J Cramer, Denny Borsboom","doi":"10.1037/rev0000497","DOIUrl":"https://doi.org/10.1037/rev0000497","url":null,"abstract":"<p><p>Experiencing stressful or traumatic events can lead to a range of responses, from mild disruptions to severe and persistent mental health issues. Understanding the various trajectories of response to adversity is crucial for developing effective interventions and support systems. Researchers have identified four commonly observed response trajectories to adversity, from which the resilient is the most common one. Resilience refers to the maintenance of healthy psychological functioning despite facing adversity. However, it remains an open question how to understand and anticipate resilience, due to its dynamic and multifactorial nature. This article presents a novel formalized framework to conceptualize resilience from a complex systems perspective. We use the network theory of psychopathology, which states that mental disorders are self-sustaining endpoints of direct symptom-symptom interactions organized in a network system. The internal structure of the network determines the most likely trajectory of symptom development. We introduce the resilience quadrant, which organizes the state of symptom networks on two domains: (1) healthy versus dysfunctional and (2) stable versus unstable. The quadrant captures the four commonly observed response trajectories to adversity along those dimensions: resilient trajectories in the face of adversity, as well as persistent symptoms despite treatment interventions. Subsequently, an empirical illustration, by means of a proof-of-principle, shows how simulated observations from four different network architectures lead to the four commonly observed responses to adversity. As such, we present a novel outlook on resilience by combining existing statistical symptom network models with simulation techniques. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142473481","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}
Gabriela Lunansky,George A Bonanno,Tessa F Blanken,Claudia D van Borkulo,Angélique O J Cramer,Denny Borsboom
{"title":"Bouncing back from life's perturbations: Formalizing psychological resilience from a complex systems perspective.","authors":"Gabriela Lunansky,George A Bonanno,Tessa F Blanken,Claudia D van Borkulo,Angélique O J Cramer,Denny Borsboom","doi":"10.1037/rev0000497","DOIUrl":"https://doi.org/10.1037/rev0000497","url":null,"abstract":"Experiencing stressful or traumatic events can lead to a range of responses, from mild disruptions to severe and persistent mental health issues. Understanding the various trajectories of response to adversity is crucial for developing effective interventions and support systems. Researchers have identified four commonly observed response trajectories to adversity, from which the resilient is the most common one. Resilience refers to the maintenance of healthy psychological functioning despite facing adversity. However, it remains an open question how to understand and anticipate resilience, due to its dynamic and multifactorial nature. This article presents a novel formalized framework to conceptualize resilience from a complex systems perspective. We use the network theory of psychopathology, which states that mental disorders are self-sustaining endpoints of direct symptom-symptom interactions organized in a network system. The internal structure of the network determines the most likely trajectory of symptom development. We introduce the resilience quadrant, which organizes the state of symptom networks on two domains: (1) healthy versus dysfunctional and (2) stable versus unstable. The quadrant captures the four commonly observed response trajectories to adversity along those dimensions: resilient trajectories in the face of adversity, as well as persistent symptoms despite treatment interventions. Subsequently, an empirical illustration, by means of a proof-of-principle, shows how simulated observations from four different network architectures lead to the four commonly observed responses to adversity. As such, we present a novel outlook on resilience by combining existing statistical symptom network models with simulation techniques. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":"66 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142486347","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}