Netherlands

This study extends the Retrieving Effectively from Memory (REM) model, a prominent computational model of episodic memory, to the domain of categorization. Our modeling approach begins with the assumption that same-category items share common features representing defining characteristics of their category. We use the model to explore how different learning modes (observation versus classification) influence category learning, considering several strategies that may emerge during the classification mode. Model simulation results indicate that different strategies which people might adopt during classification can either confer an advantage or pose a disadvantage in category learning. These findings suggest potential avenues for future research, particularly in exploring diverse strategies employed during learning.

**Authors:**

Sinem Aytac: Syracuse University; Yu-Wei Chang: Syracuse University; Michael Kalish: Syracuse University; Daniel Corral: Syracuse University

CogSci 2024

Towards a Unified Model Describing Multiple Tasks: Extending the Retrieving Effectively from Memory Model to Categorization

The 46th Annual Meeting of the Cognitive Science Society was an in-person meeting held in Rotterdam, The Netherlands at the Postillion Hotel & Conference Centre.

**ON-DEMAND PROGRAM ACCESS AFTER THE CONFERENCE** 
Recordings of the invited program are now available. You can access them by clicking on the 'Schedule' icon on the left. Select view by week and navigate to the day and time slot of the recording you wish to view. Click on the time slot to access the recording.

Recordings available (click on each recording to view):

**Thursday, July 25** 
0900: [Keynote Speaker Morgan Barense on Enhancing real-world event memory](https://underline.io/events/465/sessions/17997/lecture/99084-dynamics-between-minds-and-the-environment) 
1000: [Gleitman Award Winner Isabelle Dautriche on Language Foundations: Insights from acquisition, communication, cognition, and more](https://underline.io/events/465/sessions/18000/lecture/99085-gleitman-talk) 
1415: [Invited Symposium: Dynamics between minds and the environment](https://underline.io/events/465/sessions?eventSessionId=18016&searchGroup=lecture) 
1700: [Rumelhart Prize Presentation Speaker Alison Gopnik on Exploit, explore, empower: Three ages and three intelligences](https://underline.io/events/465/sessions/18028/lecture/99161-rp1-rumelhart-prize-presentation) 

**Friday, July 26** 
0900: [C.L. de Carvalho-Heineken Prize Keynote Speaker Kia Nobre on Focusing in memory](https://underline.io/events/465/sessions/18035/lecture/99162-hp1-c-l-de-carvalho-heineken-prize-keynote-address) 
1030: [Rumelhart Symposium: Childhood as exploration](https://underline.io/events/465/sessions/18038/lecture/100346-childhood-as-exploration) 
1415: [Elman Prize Symposium](https://underline.io/events/465/sessions?eventSessionId=18053&searchGroup=lecture) 
1600: [Invited Symposium: Dynamics between minds](https://underline.io/events/465/sessions?eventSessionId=18065&searchGroup=lecture) 
1745: [Keynote Speaker Andrea E. Martin on Neural dynamics encode the structure and statistics of language](https://underline.io/events/465/sessions/18077/lecture/99271-neural-dynamics-encode-the-structure-and-statistics-of-language) 

**Saturday, July 27** 
0900: [Keynote Speaker Gregor Schöner on How higher cognition emerges from the dynamics of strongly interacting neural populations](https://underline.io/events/465/sessions/18083/lecture/99273-dynamics-within-the-mind) 
1000: [Glushko Talks](https://underline.io/events/465/sessions?eventSessionId=18086&searchGroup=lecture) 
1500: [Invited Symposium: Dynamics within minds](https://underline.io/events/465/sessions?eventSessionId=18100&searchGroup=lecture) 


#### **CogSci 2024 Program Book**
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**The Program Book can be downloaded [here](https://drive.google.com/file/d/1yRVp1cBqRnAbdYi4GXWV_pZeyWNsRquv/view?usp=sharing).**

#### **Letter from the President**

Welcome to the 2024 Meeting of the Cognitive Science Society in Rotterdam! CogSci 2024 brings together a large community of cognitive scientists who have traveled here from around the world, as well as a smaller group of remote presenters. I would like to extend an especially warm welcome to our first-time CogSci meeting attendees, and hope that 
their experience inspires them to join our future meetings for many years to come.

I want to thank this year’s conference co-chairs, Larissa K Samuelson, Stefan Frank, Mariya Toneva, Allyson Mackey, and Eliot Hazeltine, for putting together an amazing series of invited talks and symposia around the theme of Dynamics of Cognition. The co-chairs also deserve credit for handling a record-breaking number of submissions and producing a truly exciting conference program 

Beyond the invited talks and symposia dedicated to this year’s conference theme, I would like to highlight the presentations and events honoring the 
Rumelhart, Elman, Gleitman and C .L . de Carvalho Heineken prize winners, including the Rumelhart reception on Thursday. As you may know, we are recording all of the invited talks and symposia, and all prize-winners’ talks, and will be making this content available after the conference. 

The Cognitive Science Society relies on the volunteer efforts of our Governing Board members who work on matters related to our membership; conference policies; diversity and inclusion, international, and outreach initiatives; prizes and much more. We welcome interest from Society members who would like to become more involved in what we do. The 
Society is deeply grateful to Rick Dale and Andrea Bender, who serve as editors of the two Society journals, Cognitive Science and Topics in Cognitive Science respectively. We especially acknowledge our editors’ generosity in donating their stipends each year to D&I and outreach efforts. 

This year’s Annual Meeting depends critically on the support of Marischal De Armond and his team at Podium Conference Specialists: Sharon Zwack, Cendrine De Vis, Sarah-Kate Burke, and Rachel Waller worked tirelessly to secure the venue and handled a multitude of logistical and organizational issues, from arranging coffee breaks and receptions to making sure that a huge number of posters fits comfortably into the available space. Finally, and importantly, I would like to acknowledge the Cognitive Science Society Executive Officer, Erica Wojcik, for managing the complex and ever expanding sphere of our Society’s activities.

I hope you enjoy this year’s meeting and the many different opportunities to engage with the vibrant community of cognitive scientists gathered here. I also hope you get a chance to explore the great city of Rotterdam with its many attractions, museums, restaurants and scenic views. If you’d like to talk more about our Society, or simply want to say hello, please stop by!

![](https://assets.underline.io/markdown_image/1/image/3c66d0e21fff30e204df1138ffd15173.jpeg)

**Anna Papafragou** 
President, Cognitive Science 
Society 2023-2024

**CODE OF CONDUCT** 
By attending the CogSci 2024 Conference, you are required to adhere to the society’s [Code of Conduct](https://drive.google.com/file/d/16-6KkptF0Gn3ZYGJDlpqpwTdImw45Ng0/view?usp=drive_link).

**ABOUT THE COGNITIVE SCIENCE SOCIETY** 
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.

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The 46th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

poster

We use situation models to combine events into experiences. But what are the ingredients of a situation model and to what degree do abstract event features contribute to updating of situation models? We manipulated abstract event feature dimensions and narrative specific factors in an experiment in which participants actively constructed a narrative from a random order of event descriptions. We investigated the influence of abstract factors (“degree of feature-change”, “event position”) on response speeding during a subsequent oddball task. Participants were faster for oddballs with a different degree of feature change, which interacted with whether the oddball was from within the same story or from another story. When looking at other-story-oddballs only, we found an interaction between position within the event structure and degree of feature change. Our results suggest that people use abstractions of event features which are important for the instantiation of a situation model.

**Authors:**

Rene Terporten: Radboud University; Roel M. Willems: Radboud University; Monique Flecken: University of Amsterdam; Silvy H.P. Collin: Tilburg University

Ingredients of a Narrative: How an Abstract Feature Space and Event Position Contribute to a Situation Model

The alignment between large language models and humans' knowledge and preferences is central to such tools' safe and fair deployment. A number of approaches to quantifying alignment exist, but current work is fragmented, preventing an overview across categories of stimuli and demographic groups. We propose that free associations from massive citizen-science projects can advance representational alignment by helping evaluate both content and demographic inclusivity. We assess the representational alignment of GPT-4 Turbo and data from the English Small World of Words Study (ca. 80.000 respondents, 3.7 million responses). Our results indicate that while the language model can capture some procedural signatures of human responses, it shows heterogeneous alignment across stimuli categories, poor representational alignment for controversial topics (e.g., religion, nationality), and differential representation of demographic groups (e.g., males, females). All in all, our work suggests that free association can be used to evaluate the representational alignment of large language models.

**Authors:**

Dirk U Wulff: Max Planck Institute for Human Development; Zak Hussain: University of Basel; Samuel Aeschbach: Max Planck Institute for Human Development; Rui Mata: University of Basel

Evaluating language model alignment with free associations

The paper focuses on understanding designers abstraction in ill-structured problem-solving. It introduces a protocol study with expert designers to empirically analyze the abstraction process. A logic-based schema of abstraction is found to model the process the designers employed. The study reveals how designers utilize this schema, detailing, developing, and evaluating solutions for ill-structured problems. It highlights the recursive nature of abstraction and raises questions about the termination of the process in ill-structured domains. We conclude by proposing a computational model to further evaluate abstraction in complex problem-solving scenarios.

**Authors:**

Ryan Bruggeman: Northeastern University; Estefania Ciliotta Chehade: Northeastern University; Tucker J Marion: Northeastern University; Paolo Ciuccarelli: Northeastern University

Toward a Computational Model of Design Abstraction for Ill-Structured Problems

Schemas are mental representations of common structures of our experience, and they are centrally important to human thinking and memory. Recently, it has been proposed that schemas also play an important role in structuring our imagination of the future. However, tools for automatically measuring the schematic content of written and spoken event narratives are underdeveloped. Here, we report a preliminary investigation into a set of metrics that may differentiate between more and less schematic narratives. Across two experiments, we find that written and spoken narratives that are schema-congruent are more associative, in that they contain words that are more strongly psychologically associated with one another. We discuss how this finding might contribute to the development of tools to automatically measure schematicity in future narratives.

**Authors:**

Isaac Kinley: University of Toronto; Donna Rose Addis: Rotman Research Institute; Samuel Fynes-Clinton: Rotman Research Institute; Reece Roberts: University of Auckland; Yang Xu: University of Toronto

On quantifying schematicity of future narratives

Implicit mentalising involves the automatic awareness others’ perspectives. The Joint Simon task demonstrates this as a Joint Simon Effect (JSE): A spatial compatibility effect is elicited more strongly in a Joint Simon versus an Individual go/no-go task. The JSE may stem from spontaneous action co-representation of a social partner’s frame-of-reference, which creates a spatial overlap between stimulus-response location in the Joint (but not Individual) task. However, JSE’s domain-specificity is debated. We investigated the potential content of co-representation during task-sharing—typical geometric stimuli were replaced with two coloured sets of animal silhouettes. Each set was assigned to either the participant themselves or their partner. Critically, a surprise image recognition task followed, aiming to identify any partner-driven effects in incidental memory exclusive to the Joint task-sharing condition, versus the Individual condition. Bayesian statistics indicated a robust absence of the key JSE, limiting interpretations of incidental memory findings, with implications regarding JSE’s replicability.

**Authors:**

Malcolm Ka Yu Wong: Lancaster University; Marina Bazhydai: Lancaster University; Calum Hartley: Lancaster University; Jessica Wang: Lancaster University

Does implicit mentalising involve the representation of others’ mental state content? Examining domain-specificity with an adapted Joint Simon task: A registered report

We investigated the impact of nameability, presentation configuration, and placement structure on object location memory. In Experiment 1, participants memorized photos of nameable and unnameable objects presented at one of four screen locations, either one or four objects at a time. After a filled retention interval, they were presented again centrally, and participants indicated the position where they were previously located. Results revealed a substantial memory advantage for nameable objects. Presentation configuration had no effect. In Experiment 2, we replicated these findings and additionally investigated the role of placement structure by presenting objects either in the corners or on the left/right/top/bottom position of the screen. Memory was better for horizontal/vertical placement, but only for nameable objects. Thus, nameable objects profit from semantic encoding, which can be further improved by simple orientation cues. Notably, with an average accuracy of 50%, location memory was not as "massive" as suggested in previous studies.

**Authors:**

Flurina L. Brodwolf: University of Bern; Beat Meier: University of Bern

Impact of nameability, presentation configuration, and placement structure on object location memory

Bayesian reasoning tasks require processing data in probabilistic situations to revise risk estimations. Such tasks are difficult when data is presented in terms of single-event probabilities; the multiplicative combination of priors and likelihoods often is disregarded, resulting in erroneous strategies such as prior neglect or averaging heuristics. Proportions (relative frequencies) are computationally equivalent to probabilities. However, proportions are connected to natural mental representations (so-called ratio sense). Mental representations of nested proportions (70% of 20%) allow for a mental operation that corresponds to a multiplicative combination of percentages. In two studies, we focused on the conceptual understanding underlying Bayesian reasoning by utilizing graphical representations without numbers (to avoid calculations with percentages). We showed that verbally framing Bayesian tasks in terms of proportions, as opposed to single-event probabilities, increased correct Bayesian judgment, and reduced averaging heuristics. Thus, we claim, proportions can be regarded as a natural view on normalized Bayesian situations.

**Authors:**

Katharina Loibl: University of Education Freiburg; Timo Leuders: University of Education Freiburg

Thinking in proportions rather than probabilities facilitates Bayesian reasoning

The speech-to-song illusion is a robust psychological phenomenon whereby a spoken sentence sounds increasingly more musical as it is repeated. Despite decades of research, a complete formal account of this transformation is still lacking, and some of its nuanced characteristics, namely, that certain phrases appear to transform while others do not, is not well understood. Here we provide a formal account of this phenomenon, by recasting it as a statistical inference whereby a rational agent attempts to decide whether a sequence of utterances is more likely to have been produced in a song or speech. Using this approach and analyzing song and speech corpora, we further introduce a novel prose-to-lyrics illusion that is purely text-based. In this illusion, simply duplicating written sentences makes them appear more like song lyrics. We provide robust evidence for this new illusion in both human participants and large language models.

**Authors:**

Raja Marjieh: Princeton University; Pol van Rijn: Max Planck Institute for Empirical Aesthetics; Ilia Sucholutsky: Princeton University; Harin Lee: Max Planck Institute for Human Cognitive and Brain Sciences; Tom Griffiths: Princeton University ; Nori Jacoby: Max Planck Institute for Empirical Aesthetics

A Rational Analysis of the Speech-to-Song Illusion

Intelligence tests are used in various scenarios in order to assess individuals' cognitive abilities. Typically being rather resource demanding and considerably long, some taking up to 2 hours to complete, we propose a predictive analysis paradigm with the aim of shortening and optimising tests by identifying the most predictive tasks. Taking the Berlin Intelligence Structre Test for Adolescents (BIS-HB) as an exemplar, we apply machine learning models and successfully predict IQ scores on the individual level. Moreover, we identify non-significant and potentially redundant tasks and exclude them from the analysis, obtaining the same satisfactory prediction results. A new direction of research in the field will allow not only the optimisation of IQ tests, but also enhance the knowledge and understanding.

**Authors:**

Joshua Blickle: HBK-Zwickau; Sara Todorovikj: University of Technology Chemnitz; Marco Ragni: TU Chemnitz

Evaluating the Predictive Power of Tasks and Items in IQ Tests

Perceptual organization contains two interrelated sets of phenomena: visual grouping and figure-ground segmentation. Different types of grouping and segmenting (and interaction and competition between them) have been described. Less clear is what happens once an accent is added in grouping or segmenting. According to several eye tracking experiments (n=35), apart from pop-out effect of particular elements, the overall structure of the visual field is changed. If compared to the non-accentuated stimuli, adding single accent to both grouping and segmentation stimuli induces not only local changes in saccadic processes but also a more global difference in gaze alignment. Most importantly, accent assigns a directional effect to the visual structure, typically decreases the average fixation time (by 11-28% depending on stimuli) and changes location of fixations and decreases their variation (if compared to non-accentuated stimuli). However, no significant differences between the number of fixations in non-accentuated and accentuated stimuli can be observed.

**Authors:**

Jurgis Skilters: University of Latvia; Liga Zarina: University of Latvia; Baingio Pinna: University of Sassari; Megija Lelde Gintere: University of Latvia; Santa Bartušēvica: University of Latvia; Solvita Umbrasko: University of Latvia; Ardis Platkājis: Riga Stradins University; Laura Zeļģe: University of Latvia; Jānis Mednieks: Riga Stradins University; Aleksejs Ševčenko: Riga Stradins University; Nauris Zdanovskis: Riga Stradins University; Agnese Anna Pastare: Riga Stradins University; Artūrs Šilovs: Riga Stradins University

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Ingredients of a Narrative: How an Abstract Feature Space and Event Position Contribute to a Situation Model

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