Topics in Cognitive Science最新文献

{"title":"The Dynamicist Landscape.","authors":"David L Barack","doi":"10.1111/tops.12699","DOIUrl":"10.1111/tops.12699","url":null,"abstract":"<p><p>The dynamical hypothesis states that cognitive systems are dynamical systems. While dynamical systems play an important role in many cognitive phenomena, the dynamical hypothesis as stated applies to every system and so fails both to specify what makes cognitive systems distinct and to distinguish between proposals regarding the nature of cognitive systems. To avoid this problem, I distinguish several different types of dynamical systems, outlining four dimensions along which dynamical systems can vary: total-state versus partial-state, internal versus external, macroscopic versus microscopic, and systemic versus componential, and illustrate these with examples. I conclude with two illustrations of partial-state, internal, microscopic, componential dynamicism.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12699"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397047/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41152168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What Dynamic Approaches Have Taught Us About Cognition and What They Have Not: On Values in Motion and the Importance of Replicable Forms.","authors":"Joanna Rączaszek-Leonardi","doi":"10.1111/tops.12709","DOIUrl":"10.1111/tops.12709","url":null,"abstract":"<p><p>Over the past several decades, research in the cognitive sciences has foregrounded the importance of active bodies and their continuous dependence on the changing environment, strengthening the relevance of dynamical models. These models have been steadily developed within the ecological psychology approach to cognition, which arguably contributes to the \"ecological turn\" we are witnessing today. The embodied and situated nature of cognition, regarded by some as a passing trend, is presently becoming a largely accepted assumption. In this paper, I claim that in light of these developments, ecological psychology, in alliance with related approaches, such as enactivism and interactivism, has the potential to deeply transform our perspectives on cognition and action, restoring their pertinence to humans as persons. However, an important challenge to the realization of this potential has to be noted: neither the mainstream information-processing approach nor the dynamics-oriented perspective on cognition provides an account of how the capacity of humans to use language and think \"symbolically\" can be derived from the continuous flow of agent-environment interaction. I will attempt to show that posing the \"dynamical\" and \"computational\" hypotheses about the nature of cognition as mutually exclusive approaches to cognition results in undesirable reductionism, which makes it difficult to meet this challenge. There are good reasons, advanced over half a century ago by, for example, Michael Polanyi or Howard Pattee, to think that we need complementary descriptions to understand cognizing systems, in order to grasp the fact that they are governed both by physical laws and by emergent historical constraints. Details of such a complementarity-based approach still await elucidation, but some proposed solutions have the potential to ease the tension between the information-processing and dynamical approaches to cognition and to lead to a better understanding of their interrelation.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12709"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138446606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Team Cognition Research Is Transforming Cognitive Science.","authors":"Michael J Spivey","doi":"10.1111/tops.12763","DOIUrl":"10.1111/tops.12763","url":null,"abstract":"<p><p>About 30 years ago, the Dynamical Hypothesis instigated a variety of insights and transformations in cognitive science. One of them was the simple observation that, quite unlike trial-based tasks in a laboratory, natural ecologically valid behaviors almost never have context-free starting points. Instead, they produce lengthy time series data that can be recorded with dense-sampling measures, such as heartrate, eye movements, EEG, etc. That emphasis on studying the temporal dynamics of extended behaviors may have been the trigger that led to a rethinking of what a \"representation\" is, and then of what a \"cognitive agent\" is. This most recent and perhaps most revolutionary transformation is the idea that a cognitive agent need not be a singular physiological organism. Perhaps a group of organisms, such as several people working on a joint task, can temporarily function as one cognitive agent - at least while they're working adaptively and successfully.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12763"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397046/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous Hypotheses in Cognitive Agents: Commentary on Paxton, Necaise et al., and the Dynamical Hypothesis in Cognitive Science.","authors":"Jamie C Gorman","doi":"10.1111/tops.12772","DOIUrl":"10.1111/tops.12772","url":null,"abstract":"<p><p>The 1998 article by van Gelder proposed a Dynamical Hypothesis (DH) in cognitive science consisting of Nature (cognitive agents are dynamical systems) and Knowledge (cognitive agents should be understood dynamically) hypotheses in contrast to the Computational Hypothesis (CH) that cognitive agents are computers. My commentary focuses on the contributions of Paxton and Necaise et al. in interpersonal motor coordination and radicalization across social media. I do not think that either contribution supports the Nature hypothesis but does conform with the Knowledge hypothesis. I conclude by describing cognitive agents as living systems (or nonliving systems that mimic aspects of living systems) that can be alternately viewed to support the DH or CH or both at the same time.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12772"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Cognitive Agents to Cognitive Systems: Theoretical, Methodological, and Empirical Developments of van Gelder's (1998) \"Dynamical Hypothesis\".","authors":"Tri D Nguyen, Corey M Magaldino, Jayci T Landfair, Polemnia G Amazeen, Eric L Amazeen","doi":"10.1111/tops.12725","DOIUrl":"10.1111/tops.12725","url":null,"abstract":"<p><p>Over two decades have passed since the publication of van Gelder's (1998) \"dynamical hypothesis.\" In that paper, van Gelder proposed that cognitive agents were not digital computers-per the representational computational approach-but dynamical systems. The evolution of the dynamical hypothesis was driven by parallel advances in three areas. Theoretically, a deeper understanding of genetics, biology, neuroscience, and cognitive science inspired questions about how systems within each domain dynamically interact and extend their effects across spatiotemporal scales. Methodologically, more sophisticated and domain-general tools allowed researchers to discover, model, and quantify system dynamics, structure, and patterns across multiple scales to generate a more comprehensive system-level understanding of behaviors. Empirically, we can analyze a system's behavior while preserving its natural dynamics, revealing evidence that the reductionist approach leads to an incomplete understanding of the components and the overall system. Researchers have traditionally reduced a complex system into its component processes and assumed that the parts can be recombined to explain the whole. These three advances fundamentally altered our understanding of a \"cognitive agent:\" How their behaviors are driven by long-range coordination across multiple processes, how the interdependent and nested structure of interacting variables produces behaviors that are greater than the sum of its parts, and how environmental constraints shape adaptive yet stable behavioral patterns.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12725"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139941028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ball Don't Lie: Commentary on Chemero (2024) and Wallot et al. (2024).","authors":"Damian G Kelty-Stephen, Madhur Mangalam","doi":"10.1111/tops.12764","DOIUrl":"10.1111/tops.12764","url":null,"abstract":"<p><p>The interaction-dominant approach to perception and action, originally formulated in the mid-1990s, has matured and gained remarkable momentum as an entailment of the dynamical hypotheses proposed at that time. This framework seeks to explain the fluid and intricate interplay of causality spanning the entire organism by integrating high-dimensional details with low-dimensional constraints across various scales of behavior. Both Chemero (2024) and Wallot et al. (2024) have skillfully explored the theoretical implications and methodological challenges this perspective introduces. We echo Chemero's (2024) and Wallot et al.'s (2024) focus on multifractality, while also underscoring new efforts to model the synergetic relationships and cascading dynamics inherent in this interaction-dominant approach.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12764"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397053/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142606890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introduction to topiCS Volume 18, Issue 3.","authors":"Andrea Bender","doi":"10.1111/tops.70071","DOIUrl":"10.1111/tops.70071","url":null,"abstract":"","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e70071"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397036/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148457261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inference and Imagination.","authors":"Ruth M J Byrne","doi":"10.1111/tops.70066","DOIUrl":"10.1111/tops.70066","url":null,"abstract":"<p><p>Our ability to imagine alternatives to reality is central to everyday cognition. Our competence in reasoning depends not only on our capacity to envisage the relevant facts, but also on our proficiency in simulating alternatives to them. I discuss how our skill in making deductive inferences depends on imagining possibilities. To illustrate, I consider evidence on the suppression of inferences, the cognitive processes based on mental models that explain how we make inferences, and corroboration from studies of counterfactual reasoning. I also discuss how our ability to create alternatives to reality depends on identifying mutable aspects of mental simulations. To illustrate, I consider evidence on imagining alternatives to aspects of situations within our control, the cognitive processes based on simulation availability that explain how we create alternatives to reality, and corroboration from studies of moral decision-making. I conclude with an exploration of the imagination as the engine of the mind.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e70066"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148284375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding Collective Human Behavior in Social Media Networks Via the Dynamical Hypothesis: Applications to Radicalization and Conspiratorial Beliefs.","authors":"Aaron Necaise, Jingjing Han, Hana Vrzáková, Mary Jean Amon","doi":"10.1111/tops.12702","DOIUrl":"10.1111/tops.12702","url":null,"abstract":"<p><p>The dynamical hypothesis has served to explore the ways in which cognitive agents can be understood dynamically and considered dynamical systems. Originally used to explain simple physical systems as a metaphor for cognition (i.e., the Watt governor) and eventually more complex animal systems (e.g., bird flocks), we argue that the dynamical hypothesis is among the most viable approaches to understanding pressing modern-day issues that arise from collective human behavior in online social networks. First, we discuss how the dynamical hypothesis is positioned to describe, predict, and explain the time-evolving nature of complex systems. Next, we adopt an interdisciplinary perspective to describe how online social networks are appropriately understood as dynamical systems. We introduce a dynamical modeling approach to reveal information about emergent properties in social media, where radicalized conspiratorial beliefs arise via coordination between user-level and community-level comments. Lastly, we contrast how the dynamical hypothesis differs from alternatives in explaining collective human behavior in social networks.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12702"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41239889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abduction and Deduction in Dynamical Cognitive Science.","authors":"Anthony Chemero","doi":"10.1111/tops.12692","DOIUrl":"10.1111/tops.12692","url":null,"abstract":"<p><p>This paper reviews the recent history of a subset of research in dynamical cognitive science, in particular that subset that allies itself with the sciences of complexity and casts cognitive systems as interaction dominant, noncomputational, and nonmodular. I look at this history in the light of C.S. Peirce's understanding of scientific reasoning as progressing from abduction to deduction to induction. In particular, I examine the development of a controversy concerning the use of the interaction dominance of human cognitive systems as an explanation of the ubiquitous 1/f noise, multifractality, and complexity matching in human behavior.</p>","PeriodicalId":47822,"journal":{"name":"Topics in Cognitive Science","volume":" ","pages":"e12692"},"PeriodicalIF":3.3,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13397059/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41173476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}