United States

Egodystonia refers to thoughts and behaviors that conflict with one’s values or beliefs, which is often observed in psychiatric conditions like obsessive-compulsive disorder (OCD). While prior work has demonstrated dissociations between beliefs and actions (Vaghi et al., 2017, 2019), we lack a computational framework to explain the mechanisms underlying this mismatch. In a novel experiment combining behavior and subjective report, we induced egodystonic feelings in a healthy population with a range of obsessive-compulsive traits. Individuals scoring higher on the Obsessive-Compulsive Inventory (OCI-R) reported greater egodystonic experiences. Egodystonicity was not influenced by reward availability or action rate, but was driven by perceived consequences of inaction, as captured by a computational model of the task. This study provides the first experimental evidence of induced egodystonia and offers a foundation for theoretical advances in understanding this phenomenon.

CogSci 2025

Towards a computational account of egodystonia

cognitive architectures

computational modeling

action

survey

emotion

poster

### 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. 
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* **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.
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* **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.

Converging evidence suggests that languages are shaped by
a drive for efficient communication. In particular, it has
been shown that languages efficiently compress meanings
into words via the Information Bottleneck (IB) principle in
domains ranging from visual percepts, such as colors and
objects, to non-visual high-level concepts, such as pronouns
and number. These domains, however, capture only static
elements described by adjectives, nouns, function words, or
grammatical markers, leaving open the question of whether the
same theory could also apply to verb meanings, which often
refer to dynamical aspects of the environment. We address
this question by considering locomotion verbs (e.g., walk, run,
and jump) across four languages (English, Dutch, Spanish,
and Japanese). We show that locomotion verb meanings
across languages are shaped by pressure for efficiency, which
resonates with similar findings in other domains and suggests
that the IB principle may apply more broadly across the
lexicon. Our results also open a new avenue for future work
to explore whether semantic categories of actions are rooted
in a strictly perceptual representation, or perhaps in motor and
functional representations as well.

Efficient compression in locomotion verbs across languages

Acquiring multiple meanings for a word is often proposed to be difficult for word learners. However, the difficulty may depend on the meanings: prior work has demonstrated that word-learning is easier for both adults and children when words' multiple meanings are related (polysemous, like "cap”) than unrelated (homophonous, like "bat”). However, it remains an open question how learners infer polysemous meanings if learners encounter these words in more referentially ambiguous contexts. In two studies, we examine children’s and adults’ learning of polysemes under uncertainty, using both artificial stimuli from prior work (Study 1) and attested non-English polysemes (Study 2). Results suggest that while adults can use similarities between referents to infer polysemous meanings across multiple exposures, children generally struggle to do so. This indicates that polyseme learning improves with age and suggests current computational models of cross-situational word-learning may capture children’s word learning strategies better than those of adults.

The development of polyseme learning under uncertainty

In interpersonal conflicts, empathy fosters socially adaptive behaviors that facilitate reconciliation, such as offering comprehensive and non-defensive apologies. Perceivers adjust their behaviors based on inferences about the intentions of social targets during social interactions. How do these inferences relate to perceivers’ empathy and shape their adaptive behaviors in conflicts? This study examined two aspects of intention inference: inference accuracy (how accurately perceivers infer targets’ intentions) and target-oriented inference (how much perceivers focus on targets’ states). We investigated whether these inferences link the relationship between empathy and adaptive behaviors. Our results showed that empathetic perceivers focused more on targets’ states when inferring their intentions, which was associated with offering more comprehensive apologies. Inference accuracy, however, did not influence the relationship between empathy and either the provision of comprehensive apologies or the reduction of defensive responses. Our study underscores the importance of considering others’ states in promoting adaptive behaviors during interpersonal conflicts.

How Empathy Promotes Socially Adaptive Behaviors in Interpersonal Conflicts?: An Exploratory Study on the Role of Intention Inference

Research on how humans perceive aesthetics in shapes, colours, and music has predominantly focused on Western populations, limiting our understanding of how cultural environments shape aesthetic preferences. We present a large-scale cross-cultural study examining aesthetic preferences across five distinct modalities extensively explored in the literature: shape, curvature, colour, musical harmony and melody. We gather 401,403 preference judgements from 4,835 participants across 10 countries, systematically sampling two-dimensional parameter spaces for each modality. The findings reveal both universal patterns and cultural variations. Preferences for shape and curvature cross-culturally demonstrate a consistent preference for symmetrical forms. While colour preferences are categorically consistent, ratio-like preferences vary across cultures. Musical harmony shows strong agreement in interval relationships despite differing regions of preference within the broad frequency spectrum, while melody shows the highest cross-cultural variation. These results suggest that aesthetic preferences emerge from an interplay between shared perceptual mechanisms and cultural learning.

Visual and Musical Aesthetic Preferences Across Cultures

When learning to categorize stimuli, do we assume similar things should have similar labels? Are people more likely to respond with closer labels (e.g. 2-1 vs 2-4) when stimuli are more similar to each other? Across five experiments, we report evidence of such a bias and demonstrate that it can surface across a wide range of stimulus modalities and features, and persists regardless of participants’ prior knowledge of the dimensions relevant for categorization. We also characterize some of the limits of this effect: it appears sensitive to the specific configuration of label-stimulus mappings, and may depend on overt similarity relations in label space. At minimum, our findings indicate the need to consider label-stimulus configurations when designing categorization experiments. They also hint more broadly at how label-to-stimulus mappings may affect how we structure novel categories.

Label Similarity and Stimulus Similarity Interact in Categorization

The ability to solve problems creatively is a pivotal characteristic of human brain, yet its underlying neural mechanism remains largely unknown. Previous hyperscanning studies mainly analyzed the entire time series of brain signals to reveal an overall pattern of inter-brain synchrony (IBS) during social interaction. However, we argue that this approach might not be able to capture the dynamic properties of inter-brain interaction. In this study, we proposed a novel approach based on sliding windows and k-mean clustering to identify the dynamic modulation of IBS patterns during an interactively creative problem-solving task. Results showed that inter-personal communication could be characterized as a series of dynamic and modular IBS states along the task. Besides, the transition of dynamic IBS states was highly correlated with the dyad’s creativity ability. In sum, the proposed approach holds great promise for advancing our current understanding of the dynamic neurocognitive processes underlying social interaction.

Dynamic Inter-brain Synchrony in Real-life Creative Problem Solving in Teams: an fNIRS-based Hyperscanning Study

Recent research portrays humans as the only species with a unique ability to detect geometric shapes with Euclidean features (e.g., parallel sides), a phenomenon known as the regularity effect. Studies show humans exhibit this effect across ages, cultures, and educational levels, while non-human primates do not. One interpretation credits this human advantage to symbolic representations, whereas non-human primates rely on low-level visual features. Our findings challenge this theory: with sufficient experience, non-human primates also show the regularity effect, and their accuracy is predicted by “symbolic” geometry models, as in human children. Notably, performance in both monkeys and children is accounted for by a mixture of symbolic and non-symbolic models of geometry. These findings question the claim that symbolic models are language-based or exclusively human, and strongly imply that humans and monkeys share abstract mechanisms to represent geometry. Ultimately, this overlap underscores the continuity between species.

The Continuity of Geometric Intuition between Monkeys and Humans

Language comprehension often deviates from the literal meaning of the input, particularly when errors resembles more plausible alternatives. Such non-literal interpretations have been associated with a reduced N400 and increased P600, but it remains debated whether these effects reflect perceptual misrepresentation of the input or error correction. One way to tease apart these accounts is to examine how comprehenders adapt to a noisy linguistic environment. A perceptual error account predicts that increased exposure to noise leads to habituation to errors and more misperception, resulting in reduced N400 and P600 responses. In contrast, an error correction account predicts that comprehenders perform more error correction in noisy environments, leading to increased P600s, and potentially modulated N400s depending on the timing of the correction. In this study, we manipulated the proportion of errors in non-critical exposure sentences and measured ERP responses to different types of anomalies. The results replicated prior findings of reduced N400s for recoverable errors. Results in the P600 window were not replicated and it remains an open question which framework (error correction vs. perceptual error) best accounts for the data. Further, the results revealed substantial individual differences in processing words which may contain errors with implications for how participants adapted to additional noise in the environment.

Adaptation to noisy language input in real time: Evidence from ERPs

How people reason about the mechanics of the physical world is an important question for several different cognitive sciences. Education, cognitive psychology, and developmental psychology have each conducted large numbers of studies over the last several decades, largely in isolation from one another (especially in the last quarter century). The results have suggested that cognitive mechanics may be subserved by a number of mechanisms that are differentially involved in different tasks. Here, we report converging results from factor analysis of a large compendium of mechanics questions.

How many factors underlie cognitive mechanics?

Recent studies have used complex regularization procedures for whole-cortex neural decoding, with results suggesting that neural representations may be much more widely distributed and variable than previously suspected. Such work typically requires extensive parallel compute infrastructure, bespoke regularizers, and complicated workflows. We considered whether comparable results can be obtained from the iterated LASSO, a simple algorithm using standard L1 regularization to conduct an iterative voxel-selection scheme. We applied the procedure to decode stimulus class (face, place, or object) from whole-brain 3T-fMRI data individually in each of 8 participants, achieving a remarkable 98% classification accuracy on held-out images. The algorithm found signals in about 8% of voxels across cortex, many appearing outside the traditional occipito-temporal regions thought to support visual object representation. Moreover, the model weights revealed wide variation across participants in how and where stimulus information is neurally encoded—results consistent with prior work that deployed much more complex workflows.

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Efficient compression in locomotion verbs across languages

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Efficient compression in locomotion verbs across languages

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