Netherlands

The mechanisms underpinning probability matching remain a disputed topic. Common explanations of the effect contrast a suboptimal resource-allocation view with a misapplied optimal pattern searching approach. We suggest an alternative framing of probability matching as the result of a Bayesian sampling process involving people simulating a mental sequence of possible outcomes. We designed a behavioural experiment where people are presented with information about a six-sided die with four sides of one colour and two of another, framing three distinct within-subject subtasks. The first two involved predicting the next outcome, with and without feedback. The third explicitly asked participants to mentally sample outcomes by randomly generating sequences of rolls from the die. Consistent with a Bayesian sampling process, the statistics of the sequence, such as the higher chance of selecting the maximising response on the first trial, were similar across the subtasks. We then quantitatively fit the model to these tasks.

**Authors:**

Christian Tsvetkov: University of Warwick; Haijiang Yan: University of Warwick; Adam Sanborn: University of Warwick

CogSci 2024

Modelling probability matching as an approximate Bayesian sampling process

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

Human memory has various deficits such as forgetting. Such deficits are generally regarded as human irrationality. However, superficial deficits in human cognition can be understood differently as rational aspects in terms of the interaction between human cognition and the environmental feature. Based on this idea, the present study analyzed the nature of memory-based judgment errors. We hypothesized that systematic errors are produced when ecologically rational inferences based on statistical regularity in the environment are performed in uncertain situations. To verify this hypothesis, we proposed a benchmark for a rational inference model of memory-based judgments under uncertainty, and tested it by analyzing real-world data, computer simulations, and a behavioral experiment. We found that the error patterns participants showed in the memory-based judgment were consistent with those predicted by the rational inference benchmark. These findings provide new insights into the errors produced by memory-based judgments from the rational side of cognition.

**Authors:**

Hidehito Honda: Otemon Gakuin University; Masaru Shirasuna: Otemon Gakuin University; Jun Kawaguchi: Nagoya University; Toshihiko Matsuka: Chiba University; Kazuhiro Ueda: The University of Tokyo

On the ecologically rational inference and memory-based judgment errors

What sorts of graphical formats best convey effect size and degree of certainty of a finding? Confidence intervals are commonly used to show uncertainty, yet lay people and experts fail to correctly interpret their meaning. There has been a recent push to present individual data points rather than only presenting aggregated summary statistics (e.g., means, confidence intervals, lines of best fit). But it is unclear how well people can aggregate raw data presented in a graphical format. Across two studies, we presented participants with hypothetical study outcomes of two independent groups in three graph styles: dot plots, mean with 95% confidence interval (CI) plots, combined plots, and bee plots. We asked participants to make judgments about the effect size using the Common Language Effect Size or Bayes Factors. Participants were more likely to underestimate effect sizes and Bayes Factors for dot plots and bee plots compared to mean + 95% CI plots and combined plots. These findings suggest that people have trouble making statistical inferences when presented with raw data points in graphs.

**Authors:**

Sara Jaramillo: University of Pittsburgh; Benjamin Rottman: University of Pittsburgh

Can People Accurately Draw Statistical Inferences from Dot Plots?

Citizens in a democracy must navigate an increasingly dense information landscape. Regulation can aid this navigation by mandating disclosures of the source and nature of political campaign material. In many countries, legislators are increasing transparency requirements for online advertising in particular. The current paper looks at how and if citizens use these proposed disclosures as signals for specific dimensions of trustworthiness and intent of advertisers. This paper specifically investigates whether such requirements uniquely disadvantage unknown political campaigners, increasing the barriers they face when communicating with citizens. The findings of this survey experiment support that political campaigners are not disadvantaged by such requirements, even when disclaimers disclose micro-targeting information. Furthermore, there is some support that ‘paid for by’ disclaimers, if they are processed, can benefit advertisers by reducing perceptions of manipulation and increasing perceived trustworthiness.

**Authors:**

Hazel Clare Gordon: University of Sheffield; Tom Stafford: University of Sheffield; Katharine Dommett: University of Sheffield

A Cue to Trust? Investigating the Impact of Political Advertising Transparency Disclaimers on Citizen Trust Evaluations

Emotions regulate social interactions from early in ontogeny, but are difficult to assess in pre-verbal or just-verbal children. Previous studies have used body posture as a measure of emotion expressions, employing depth-sensor imaging cameras (e.g., Kinect) in laboratory environments. Advances in artificial intelligence now allow researchers to track posture keypoints from existing video recordings taken with any camera. The studies reported here explore the use of OpenPose to capture children’s emotional expressions. In Study 1, we analysed posture data from previous studies and found that children’s expressed valence was positively related to changes in their upper-body expansion whereas expressed arousal was related to overall levels of movement. In Study 2, we asked children (n = 64, aged 5 to 10 years) to recall emotional episodes of ‘happiness’, ‘sadness’, ‘pride’ and ‘shame’. There were no effects of specific emotion categories on changes in children’s posture, but exploratory analyses revealed that recalling positive emotions yielded greater changes in upper-body expansion compared to negative emotions. Together, the findings suggest that the valence and arousal of expressed emotions can be captured using OpenPose. Findings are discussed with respect to the question of how children conceptualize emotions.

**Authors:**

Marlene Försterling: University of Oxford; Stella Gerdemann: Max Planck Institute for Human Development; Brian Parkinson: University of Oxford; Robert Hepach: University of Oxford

Exploring the expression of emotions in children’s body posture using OpenPose

Space helps us understand abstract math concepts (Winter et al., 2015). Mental rotation is often studied for its predictive role in math development (Casey et al., 2015; Geer et al., 2019). The association between spatial location knowledge and math development remains overlooked despite the significance of left-right body space encoding in numbers (SNARC effect, Dehaene et al., 1993). This ongoing study investigates the link between preschoolers' mental rotation skills, spatial location knowledge, and various mathematical abilities (symbolic, non-symbolic, counting). Preliminary analyses (N= 20; Mage= 4;6) using R showed a significant relationship between spatial location knowledge and symbolic math (r= .43; p= .05) and counting skills (r= .51; p= .02), while no such association is found between mental rotation skills and mathematical abilities (all ps> .05). These findings demonstrate a strong link between spatial location knowledge, but not mental rotation, and development of preschoolers’ mathematical skills.

**Authors:**

Hüseyin Yalçıner: Middle East Technical University; Dilay Z. Karadoller: Koç University

Relationship Between Spatial and Number Development: Spatial Location Knowledge but not Mental Rotation relates to Numerical Skills of Preschoolers

There are two foundational assumptions that underlie research in interactivity. First, that external scaffolds should support problem-solving and other cognitive activities and second, that human agents naturally engage in this form of offloading. We aimed to test whether participants would naturally engage with external resources without prompting in four types of simple verbal problems and whether this was affected by levels of expertise or the experience of impasse. We found that very few people naturally engaged external scaffolds apart from with mathematical problems where it had a benefit. There was no difference in expertise in problem solving between those who did and those who did not use external props and nor was there a significant difference in the proportion of people using external scaffolds as a function of experiencing impasse. These results suggest that researchers in interactivity need to focus on how and when interactivity is both engaged and provides a benefit.

**Authors:**

Wendy Ross: London Metropolitan; Selene Arfini: University of Pavia

Spontaneous use of external scaffolds in verbal problem solving is rare but beneficial

In general, it is still unclear, to what extent, that autistic children would develop the ability to recognize facial expression by age and which basic emotion expressions are consistently difficult to learn. Moreover, what crucial processing and mechanisms would play a key role for the autistic behavior patterns in early social interaction. To answer these questions, a deep learning model is constructed to simulate the eye movement records during judging emotion expression of typical developed and autistic children. The simulation results are: 1. for older autistic models, if the gaze fixations for eyes and mouth of positive emotion is longer, it would lead to greater recognition performance; 2. in contrast, for younger autistic models, it takes longer training sessions to correctly recognize most of negative emotions as too much inferences of internal information occurred while establishing reliable prototypes of facial figures in differentiating the angry, sad, and disgusting expressions.

**Authors:**

Hui-Xin Cai: National Cheng Kung University; TSE MING Chen: National Changhua University of Education; HUA FENG: Graduate Institute of Rehabilitation Counseling; Shu-Ling Peng: National Cheng Kung University; Po-Sheng Huang: National Taiwan University of Science and Technology; Ying-Chien Wang: National Cheng Kung University; Jon-Fan Hu: National Cheng Kung University

A Deeping Learning Modeling for the Development of Emotion judgement in Autistic Children

Memorability is an intrinsic property of stimuli, reflecting their average likelihood of being remembered across individuals. While recent research has examined the relationship between semantic relatedness and English word memorability, it is unclear whether these findings apply to other languages, and moreover, whether emotional content contributes to word memorability. We conducted three behavioural cued-recall experiments using Chinese words and implemented computational modeling to examine semantic relatedness and emotional consistency as predictors of memorability. We found that both factors explained word memorability: words that were more semantically dissimilar were associated with higher memorability; broad emotional consistency (non-neutral cue-target pairs) and positive emotional consistency (positive- positive pairs) both had memory advantages. Our results provide new insights into Chinese word memorability, and the potential contributions of semantics and emotion.

**Authors:**

Haoyu Zhang: University of Toronto; Wilma Bainbridge: University of Chicago; Pei Sun: Tsinghua University ; Andy C.H. Lee: University of Toronto

Exploring the Contributions of Semantics and Emotion to Word Memorability: a Behavioural and Computational Modeling Study

An assertion about a fact can be verified by observation. That is impossible for assertions about what is permissible or obligatory, i.e., deontic assertions based on moral principles, conventions, rules, or laws. An integrated theory of emotions and mental models predicts that emotional reactions and strength of belief should be correlated for deontic assertions, but not be correlated for factual assertions. Previous studies have corroborated this prediction for moral claims, matters of convention, prudential rules, and personal recommendations. We report two experiments that yield the same interaction for legal pronouncements from the Italian Civil Code compared with parallel factual assertions. People like what they believe, and they believe what they like. We discuss several remaining unknowns including the potential role of emotions in reasoning about legal and other deontic propositions.

**Authors:**

Monica Bucciarelli: Università di Torino; Phil Johnson-Laird: Princeton University

Emotion, Belief, and the Words of the Law

Emotion space models are frameworks that represent emotions in a multidimensional space, providing a structured way to understand and analyze the complex landscape of human emotions. However, the dimensional representation of emotions is still debatable. In this work, we are probing the higher dimensional space constituted by emotion labeling done by participants from India on multimedia stimuli. Our approach formalizes the study of emotion in the investigation of representational state spaces capturing semantic variation in emotion-related response (including experience and expression, as well as associated physiology, cognition, and motivation). We have created a high-dimensional space of emotional ratings by participants to represent emotional stimuli. Using a prominent dimensional reduction technique, t-distribution-based stochastic neighbour embedding (t-SNE), we have projected the higher dimensional space into two dimensions. We observed that the structure of emotional categories and clusters formed of these emotional categories is similar to Russell's circumplex model. The transition from the blended complex emotional states to the discrete emotional states is projected out from the centre, and discrete emotional states occur in the periphery. Using advanced visualization and multidimensional technique, we show a continuity of emotional experiences to complement the existing knowledge based on V-A space with the information on how the transitions among emotion categories occur.

**Authors:**

Sudhakar Mishra: Indian Institute of Technology Kanpur; Narayanan Srinivasan: Indian Institute of Technology; Uma Shanker Tiwary: Indian Institute of Information Technology Allahabad

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