United States

This study investigates how expertise influences the mental representation of dance choreography, focusing on differences between expert and novice ballet dancers. Event Segmentation Theory (EST) was used to examine chunking in a 50-step ballet sequence. Participants, classified as experts or novices based on dance experience, were tasked with segmenting choreography across repeated viewings. Results showed that experts segmented the sequence into fewer, larger chunks, and showed greater consistency and greater similarity with each other. Novices, in contrast, identified more segments and showed less agreement. These findings underscore the role of domain-specific knowledge that incorporates the structure of the domain in forming mental representations, and sets the stage for exploring how this may enable superior expert learning and memory for very long sequences of dance.
Keywords: expertise; event segmentation; chunking; dance memory

CogSci 2025

Breaking it Down: Expertise and Dance Segmentation

event cognition

dance

psychology

memory

We are pleased to announce the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), which will be held in Vancouver, British Columbia at the Vancouver Convention Centre – West Building from 20-27 February, 2024.

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-24 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.

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AAAI 2024

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. 

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### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

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#### About

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

#### Our History 

* **Society Creation**<br>
The Society was incorporated as a 501(c)(3) non-profit professional organization in Massachusetts in 1979. The organizing committee included Roger Schank, Allan Collins, Donald Norman, and a number of other scholars from psychology, linguistics, computer science, and philosophy. 
<br><br>
* **Conference Creation**<br>
The first conference on cognitive science was held at La Jolla, California in August, 1979, and has occurred annually since then. The proceedings of each conference are published, and those from most years are available through Lawrence Erlbaum Associates, Inc. The annual proceedings of the Cognitive Science Conference represent a major source of information on new work and new ideas in the scientific study of thinking. In 1990, the Society, with help from an anonymous donor, established the David Marr Prize for the best student paper at each annual meeting.
<br><br>
* **Journal Creation**<br>
The Journal, Cognitive Science, began publication in 1976, and is now published by Wiley-Blackwell. The Executive Editor is currently Richard P. Cooper of Birkbeck, University of London, and there are 18 Associate Editors and a 30-member editorial board. It serves as the premier outlet for research reports that intersect two or more disciplines. Copyrights for articles published in the journal are held by the Society. The Governing Board of the Cognitive Science Society voted in late 2006 to found a new journal, Topics in Cognitive Science (topiCS). The Editor in Chief is Wayne Gray, Cognitive Science Department, Rensselaer Polytechnic Institute. The journal seeks to fill a niche not occupied by Cognitive Science Journal or other cognitive science journals. Membership in the Society includes a subscription to Cognitive Science and TopiCS. Copyrights for articles published in the journal are held by the Society.
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#### Code of Conduct

By attending the CogSci 2025 Conference, you are required to adhere to the society’s **[Code of Conduct](https://drive.google.com/file/d/1ChPuihLy6jE_BWqfO7J2KKgX35JW2zsM/view?usp=sharing)**.
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The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

The Self-Prioritization Effect (SPE) suggests that
associating stimuli with the ‘self’ affords processing
advantages in perception (Sui & Humphreys, 2012),
attention (Keyes & Brady, 2010), long-term memory
(Turk et al., 2008; Klein, 2012), working memory (Yin
et al., 2019; Roy et al., 2023), and decision-making
(Polman, 2012; Hu et al., 2019). An important aspect
of working memory is the ability for continuous
tracking, maintenance & updation. The Multiple-
Object Tracking (MOT) paradigm involves constant
attention and maintenance in working memory and
online decision-making. The current study was
designed to test the tracking performances for self-
associated stimuli (neutral shapes and colored shapes)
compared to stranger-associated stimuli (neutral
shapes and colored shapes) in a multiple object
tracking (MOT) paradigm. Additionally, we used
three different set-sizes (6,8,10), where half of the
shapes were targets, and half were distractors, to check
for boundary conditions with respect to WM load. We
found that with increasing set-size, tracking
performance decreases significantly. Also, whether
targets or distracters belong to the same
(homogeneous) or different categories
(heterogeneous) moderates the tracking performance
of the participants, as target shapes becomes more
complicated when the target and distracters are of the
same type, i.e., the homogenous conditions. We found
that the tracking performances of the self-associated
shapes were significantly better than the stranger-
associated target shapes when the target and
distractors were of different categories (heterogeneous
condition) but only upto set-size 8 due to working
memory limits. Additionally, we found that self-
associated shapes or colored shapes were significantly
poorer in tracking when target and distractors were of
same categories (homogeneous condition) within the
working memory limits. These results suggest that
individuals can pay more attention to self-associated
stimuli, which are maintained in working memory and
have better focus of attention, despite limited capacity
WM resources.
Keywords: self-association, tracking, multiple
object tracking, working memory, visual working
memory, identity, location.

Self-Association Makes It Easier to Track Multiple Objects But Within Capacity Limitations: A Multiple-Object Tracking Investigation 

Prevalence-induced concept change (PICC) occurs when reduced category prevalence  increases the likelihood that ambiguous stimuli are classified as belonging to the now-minority category. PICC has been observed across perceptual and social domains and persists despite instructions or incentives to suppress it. However, other findings suggest its expression is instead shaped by social context. If AI models are to be treated as theories of cognition, they should exhibit PICC as well. We show that a standard AI model for sequential learning, trained on dynamic category distributions, does not display PICC, instead favoring the now-majority category. This opposite-PICC effect suggests that simple sequential learning may be insufficient to produce PICC. Additional mechanisms, such as structured priors, contextual sensitivity, or internal feedback, seem necessary for its emergence. Our findings contribute to the understanding of PICC and its implications for categorization theories, AI-driven decision-making, and the role of media exposure in shaping social perceptions.

Prevalence-Induced Concept Change: Universal or Context-Dependet? Implications for Social Psychology and AI Cognition

Grounded in predictive processing theory, this study explored the idea that young learners generate top-down expectations about upcoming words, both in meaning (semantic) and sound (phonological), to aid early language development. Researchers hypothesize that language acquisition is facilitated by children’s growing ability to anticipate not only the content of an utterance but also the specific forms those utterances might take. By examining how toddlers transition from broad conceptual understanding to accurate phonological prediction, this work sheds light on the cognitive mechanisms that enable rapid language growth possible in early childhood. The main goal was to determine when and how toddlers begin to form semantic and phonological expectations for upcoming words. To address this, three preferential looking experiments were conducted with Spanish-speaking toddlers at 18, 24, and 30 months. Highly constrained sentences were played aloud while toddlers viewed pairs of images: either a target or a competitor (semantic or phonological) and an unrelated distractor. As the toddlers listened, their gaze patterns revealed whether they anticipated the correct word or a related image before the target was fully pronounced. The rationale was that if toddlers can detect cues in the sentence and map them onto future words, they will show anticipatory looks toward images that match meaning or sound. Analyses revealed a progressive pattern: at 18 months, toddlers clearly predicted specific words in strongly constraining contexts, but showed no consistent anticipation of semantic alternatives. By 24 months, toddlers not only looked toward the correct referent but also demonstrated meaningful shifts toward pictures sharing semantic features with the target. This suggests they were extracting and forecasting aspects of meaning ahead of time. However, reliably predicting word forms based on phonological cues emerged more robustly at around 30 months, when children also shifted their gaze to phonologically similar items before the target was spoken. These findings highlight a developmental trajectory in which toddlers leverage broader conceptual knowledge first, refining phonological detail later as their linguistic system matures.

From Meanings to Sounds: Development of Language Prediction in Toddlers

Agent-based models (ABMs) have become a valuable tool in social epistemology for addressing a fundamental question: How should scientists communicate? Yet, ABMs often yield conflicting results—some suggest that high levels of communication decrease group accuracy, while others find it beneficial. Why do models differ so dramatically? We argue that these discrepancies arise from a simple fact: different models use different conceptions of ”communication,” and model qualitatively different phenomena. To demonstrate the effects of such differences, we integrate three paradigmatic conceptions of communication from the literature—direct evidence sharing, belief averaging, and testimony exchange—into a unifying simulation. This allows us to test them under identical conditions. Our findings suggest that communication is generally beneficial. However, the effects of communication vary significantly by which conception one adopts, even under identical conditions. This lack of robustness highlights a critical issue: outcomes depend heavily on how communication is modeled.

Why Models of Scientific Communication Disagree

Humans can reason across multiple domains (e.g., syllogistic, conditional, relational reasoning). Previous research has often investigated these domains in isolation, hence often identifying domain-specific strategies. A fundamental question in cognitive science is, however, if we apply rather a more general reasoning process or more domain-specific mechanisms. To approach this question and allow for analyses and modeling across domains, we first present a general data set that is well-grounded in the state-of-art of reasoning research and covers not only syllogistic, conditional and spatial reasoning, but also includes a test battery (e.g., memory). Second, we investigate relationships between the domains and present a preliminary step towards cross-domain modeling by predicting an individuals' syllogistic conclusion based on behavior observed in the other domains. Our results show that domains are heavily interrelated with subtle differences between domains, highlighting the need for explanations that integrate subtle domain-specific strategies in a general theory of human reasoning.

Using Cross-Domain Data to Predict Syllogistic Reasoning Behavior

Beneficial effects of meditation on mental well-being are not unequivocally confirmed in research (Goyal et al., 2014). In our study (n=19), we hypothesize that meditation (practiced over a longer period of time) impacts emotions and their intensity. We used The Geneva Emotion Wheel in meditation sessions (n=12) performed regularly over a 12-week period of time, from April to July, 2024. We controlled depression and personality type. Emotions were measured before and after each meditation session. Depression was measured before the start of the meditation course and at the end of it by The Patient Health Questionnaire (Kroenke et al., 2001). Personality traits were tested once - before the start of the meditation course by Big Five Inventory-10 (Rammstedt & John, 2007). The results showed that meditation had a positive effect on several emotions and their intensity, but the effect on depression was not found.

Effects of meditation on emotions and depression: a longitudinal study using Geneva Emotion Wheel 

Sentences with plural definites like ‘the circles’ are usually
interpreted akin to universally quantified sentences (maximal
reading). In some circumstances, however, they also allow
for non-maximal readings, i.e imprecise readings that allow
for exceptions. We report two mouse-tracking experiments
that investigate the online derivation of these non-maximal in-
terpretations of plural definites. Our results show that non-
maximal readings are harder to process than maximal interpre-
tations. This difficulty seems to be associated to hesitation in
the decision-process rather than to a truly two-step derivation.
Interestingly, we also find that experimental setup plays an im-
portant role in the availability and difficulty linked to these
readings.

Processing non-maximal readings of sentences with plural definites

People contribute to new creations through different tasks, skill and effort. How do these contributions influence judgements of ownership? Past research has shown that initial effort towards a goal and net labour contribution are both relevant to intuitions about rightful ownership. However, their relative weights remain unclear, and hence often have different implications about who the owner should be. Here, we examine ownership judgements of new creations, contrasting different contributions. Across four online experiments (total N=704), we describe an initiator and a completer who work together on the creation of a new object, with their contributions varying in terms of effort, skill and how much they meet the original goal. We find an especially strong preference for the initiator to take ownership. This may be because initiation seems more necessary: without it, the subsequent steps of creation would not be needed.

Who owns new creations? Initiation weighs more than completion

Task-unrelated thinking (TUT) can impact both performance and well-being, yet its role in affect regulation remains underexplored, especially in an educational context. This study examined TUT level, characteristics, and functions in 173 on-site and 143 online students, assessing their affect and class experiences in an ecological setting. While overall TUT levels did not differ between groups, distinctions emerged in characteristics (e.g., inner speech) and functions (e.g., stimulation or avoidance). Valence was the only characteristic predicting prospective sadness or anxiety. Using TUT for problem-solving or avoidance was linked to increased sadness, whereas using it for stimulation was linked to reduced anxiety. These findings highlight that TUT’s effects depend more on its nature and purpose than its frequency. The observed link between avoidance-related TUT and negative affect has significant implications for clinical psychology and educational settings, particularly in understanding emotion regulation in online and on-site learning.

The Role of Task-Unrelated Thinking Characteristics and Function in  Affect Regulation During Online and On-site Classes

In their 2022 study, Thomas and colleagues found that when observing third-party interactions, infants, toddlers, and children might use saliva-sharing as a cue for inferring relationship thickness. The present study is the first external attempt to replicate their key findings with infants aged 8.5 to 10 months (n = 50). We used the original stimuli and the original design, but instead of running the study online and coding gaze direction manually from video recordings, we tested infants in a laboratory and measured gaze behavior with an eye tracker. Our study successfully replicated one of the main findings of the original study (longer looking at the saliva-sharing actress) while failing to replicate the other one (looking first at the saliva-sharer). These findings confirm that infants rely on certain behavioral cues for mapping social relationships among third-party individuals.

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Self-Association Makes It Easier to Track Multiple Objects But Within Capacity Limitations: A Multiple-Object Tracking Investigation

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