Netherlands

Researchers typically have a fair amount of freedom when it comes to data processing and analysis selection. In many instances, there isn’t one correct way to, for example, deal with outliers, which gives rise to a multitude of reasonable analysis pathways, each with its own outcome. Computational advances provide researchers with a unique opportunity to view the impact of such researcher degrees of freedom on the results from a study. Multiverse analyses involve the computational analysis of all these potential pathways, which can demonstrate the robustness of a particular phenomenon, or the lack thereof. However, even though multiverse analyses are less susceptible to biases compared to the typical single-pathway approach, it is still possible to selectively add or omit pathways. To address this, we propose a more principled approach to conducting multiverse analyses, and illustrate how it can be applied using the Semantic Priming Across Many Languages project.

**Authors:**

Tom Heyman: Leiden University; Ekaterina Pronizius MSc BSc: University of Vienna; Erin M. Buchanan: Harrisburg University

CogSci 2024

Crowdsourcing Multiverse Analyses to Examine the Robustness of Research Findings

## Welcome to EMNLP 2024! 
We are excited to welcome you to one of the most prominent conferences in the field of Natural Language Processing. This year, EMNLP 2024 is being held in a hybrid format,
offering both virtual and in-person participation in beautiful Miami. Due to a record-breaking number of submissions, we've expanded the total number of accepted papers to accommodate more cutting-edge research from around the globe.
### [Conference Handbook](https://drive.google.com/file/d/1WPROgxjLAC96AJL7Ugy0tEnYm7dkrbHt/view?usp=sharing)

You are required to register for this event. **Please register [here](https://2024.emnlp.org/registration/).** The EMNLP 2024 event page on Underline will be open to public one week prior to the event.

Please register!

EMNLP 2024

EMNLP 2024 will take place in Miami, Florida from Nov 12th to Nov 16th, 2024, at the Hyatt Regency Miami Hote and on Underline for remote participants.

poster

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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To access the site please register [**here**](https://cognitivesciencesociety.org/registration/). 

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

We investigated the impact of linguistic cues and autistic traits on lie detection. Adult participants (N = 125) judged suspects’ statements in a detective game. Untruthful statements were marked by semantic leakage. Literature indicates that liars use fewer first-person pronouns and mental state terms. We manipulated the untruthful statements for the presence/absence of these cues to test their effect on lie detection. The adults were 89% accurate in detecting lies. Mental state terms did not affect accuracy, while presence of first-person pronouns hindered it. Having autistic traits did not influence lie detection. However, adults with higher autistic traits struggled to detect lies when these contained both a first-person pronoun and a mental state term. Post-hoc analysis showed that lie detection accuracy was lower for longer sentences. Our findings underscore semantic leakage's significance in lie detection, with nuanced effects of linguistic cues on accuracy, particularly for adults with higher autistic traits.

**Authors:**

Özlem Yeter: University of Groningen; Barteld P. Kooi: University of Groningen; Harmen de Weerd: Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence; Rineke Verbrugge: University of Groningen; Petra Hendriks: University of Groningen

Semantic Leakage Enables Lie Detection, but First-Person Pronouns and Verbosity Can Get in the Way of Detection

From daily newsfeeds to scientific papers, we often read the same text more than once. How do our eye movements in repeated reading differ from first reading? In this work we examine this question at scale with L1 readers of English via standard eye movement measures and their sensitivity to linguistic word properties. We analyze consecutive and non-consecutive repeated reading, and further compare ordinary and information-seeking reading. We find sharp and robust facilitation effects that can be modulated by the reading regime, the presence of intervening textual material, and the relevance of the information to the task across the two readings. Finally, we examine individual differences in repeated reading effects and find that their magnitude interacts with reading speed, but not with reading proficiency. Our work extends prior findings on multiple axes, providing a detailed empirical picture of repeated reading which could inform future models of eye movements in reading.

**Authors:**

Yoav Meiri: Technion; Yevgeni Berzak: Technion

Déjà Vu: Eye Movements in Repeated Reading

Working Memory (WM) is a necessary component for models of human cognition and human-inspired robot cognitive architectures. Different theories explain how the limited capacity of WM should be maintained, including theories of forgetting through decay and interference. Yet, it is unclear how WM models informed by these theories might be used to inform robot cognition, and how they might shape robots' ability to engage in natural, situated, language-based interactions. To resolve this tension, we implemented an entity-level, feature-based WM system integrated into a robot cognitive architecture, which can be configured to reflect both decay- and interference-based dynamics. We demonstrate with a set of case studies how different parameterizations of these WM strategies have fundamentally different error modes in different interaction contexts. We formulate rules that inform the selection of decay and interference parameters to be used in contexts with different factors that are important for language-based interaction.

**Authors:**

Rafael Sousa Silva: Colorado School of Mines; Tom Williams: Colorado School of Mines

Uncovering the Rules of Entity-Level Robotic Working Memory

The CONTROL IS UP metaphor is an embodied cognitive mechanism that helps western speakers reason about power relations in terms of vertical spatial organization, This paper explores its multimodal elaboration in visual manifestations of pyramidal structured arrangements and kinetic practices such as genuflexion in medieval miniatures in order to (i) demonstrate the role of multimodal representations of metaphors in reasoning, (ii) unveil power relationships between different societal strata.
34 miniatures (12th ct. Liber feudorum maior) were analised with the “multimodal genuflexion test” to describe and measure (CAD-software) distances between kinetic elements (facial/manual gestures, postures).
Results indicate that (i) power relations are not just vertically represented (kneeling & bowing), physical distance between characters and position of hands are crucial, (ii) there is a significant positive correlation [U = 61,119; p = 0.003] between the power figure and the degree of “body bending” (bowing, kneeling) and hand distance.

**Authors:**

Iraide Ibarretxe Antuñano: University of Zaragoza; Andrea Ariño Bizarro: University of Zaragoza; David Moret Oliver: Real Estate Developer; María Teresa Moret-Oliver: University of Zaragoza; Guillermo Tomás Faci: Archivo

Kinetic elements in genuflexion correlate with the degree of power relations in societal strata: The CONTROL IS UP metaphor in medieval miniatures

Humans have an intuitive understanding of music. We can predict the ensuing notes of a melody given the first few notes, but what exactly drives these predictions? Previous research on musical cognition explores probabilistic models of melody perception where a melody’s structure can be inferred given its surface. Other research theorizes about “musical forces”, forces that are analogous to how we represent the physical world, and which inform the way we form expectations about music. We propose a single model of melodic expectation that combines both ideas using a structured generative model and sequential Monte Carlo inference. The generative model formalizes these musical forces, and combined with inference, enables predicting the last note of a melody given the beginning notes. This model explains human performance in an existing dataset of melodic predictions. The model explains more variance than its ablations, and suggests an “intuitive physics” basis for melodic expectation.

**Authors:**

Breanna K. Nguyen: Yale University; Ilker Yildirim: Yale University

An Intuitive Physics Approach to Modeling Melodic Expectation

How do humans infer the structural interpretations of a piece of music from its basic elements? Since recursive elaboration is an important structural principle in several musical traditions, generative probabilistic models are a useful tool for characterizing musical interpretation as a probabilistic inference problem. However, due to the high degree of ambiguity and combinatorial complexity of even short excerpts of music, exact inference (e.g. finding the "best" structural interpretation of a piece) is usually not feasible. The present work proposes a hybrid approach to this problem. An explicit and interpretable probabilistic top-down model is complemented with a heuristic parser that reverses the generative process in a greedy fashion and adapts to feedback from the top-down model via deep reinforcement learning. The combination of these two models bridges the gap between explicit but slow top-down knowledge and immediate musical intuitions on various levels of musicianship.

**Authors:**

Christoph Finkensiep: University of Amsterdam

Inferring Musical Structure - A Hybrid Approach Combining Probabilistic Models and Reinforcement Learning

When completing a task for a prolonged period, our ability to sustain attention fluctuates over time. Accordingly, in mice, disengaged behaviour has temporal autocorrelation (i.e., ‘disengagement states’), with lapses clustering in time, rather than occurring randomly. In this disengaged state, mice make more errors and provide responses biased towards one side. What neural and physiological processes trigger the transition into, and out of, disengagement states? Here, we investigated the role of pupil-linked arousal. We used a public dataset of 140 mice performing a perceptual decision-making task, including extracellular recordings alongside behavioural and pupil responses. We applied hidden Markov models to identify engagement states based on response times. Preliminary results show that disengaged trials are associated with larger and more variable baseline pupil, and suggest that pupil size changes precede state transitions. These findings will provide a starting point for exploring the cortical, subcortical and neuromodulatory processes preceding task (dis)engagement.

**Authors:**

Philippa A Johnson: Leiden University; Sander Nieuwenhuis: Leiden University; Anne Urai: Leiden University

Pupil dynamics preceding switches in task engagement

Pupil dilation has been associated with increased mental effort, which can be modulated by external sensory stimulation as well as internal cognition. Underlying a cognitive task are multiple cognitive processes which can be stimulus-driven, goal-driven or spontaneous. However, what remains unknown is how these processes correlate with pupil size modulations and whether it is possible to dissociate their individual effects. To answer this, we employed behavioral and pupil data from two cognitive tasks performed in internal and external attention conditions, where stimulus-driven attention demands were manipulated for the same set of tasks. Using model-based analysis, we were able to dissociate within conditions, how individual processes affect pupil and also compare their effects between conditions. We made two important and novel findings – first, for each condition we were able to dissociate stimulus-driven and goal-driven effects. Second, when compared between conditions, we found distinct stimulus-driven attention-based effects but similar goal-directed task-based effects.

**Authors:**

Adarsh Palaskar: Indian Institute of Technology Jodhpur; Shilpa Dang: Indian Institute of Technology Jodhpur

How pupil tracks cognitive processes underlying internally- and externally-directed attention tasks

A behavioural and two EEG hyper-scanning experiments are presented which investigate how predictive processing modulates the way interlocutors align behaviourally and at the level of the brain (Hasson, 2012; Pickering & Garrod, 2007). In the experiments interlocutors engaged in dyadic interactions performing a semi-controlled semantic association game and where the p predictability of the semantic associations was manipulated. The behavioural results showed that both interlocutors were around 400 ms faster in the predictable versus non-predictable conditions The results of the two EEG studies aim at demonstrating (1) whether we observe brain-to-brain synchronisation between the interlocutors at the level of word semantics, and (2) whether prediction enhances this synchronisation. To our knowledge, this is the first study to directly demonstrate prediction effects in an interaction.

**Authors:**

Emilia Kerr: Aix-Marseille University; Kristof Strijkers: CNRS & Aix-Marseille University; Benjamin Morillon: Aix-Mareille University

Does prediction drive neural alignment in conversation?

The brain uses contextual information and prior knowledge to predict future content during
language comprehension. Previously, it has been demonstrated that contextual word
embeddings, derived from Large Language Models, can be linearly mapped onto brain data. Recently, Goldstein et al. (2022) have used this method to study neural signatures of
predictive processing. They found that predictive signatures of an upcoming word can be
observed in its pre-onset signal, measured with ECoG during listening to naturalistic
narratives . In the fMRI domain, Caucheteux et al. (2023) have shown that including
embeddings of multiple upcoming words improves the model’s fit to brain data. This has
been interpreted as an indica4on that the brain encodes long-range predictions. In this study we examine whether the same predictive information can be found in MEG data, a signal with lower signal-to-noise ratio than EcOG and higher temporal resolution than fMRI. We show that: 1) The signatures of pre-onset predictions about the upcoming word are also detectable in MEG data similarly to ECoG and 2) Contrary to what has been observed in the fMRI data, including future embeddings does not improve brain encoding in MEG signals. These findings provide a novel avenue for studying predictive processing during language comprehension with naturalistic stimuli using MEG signals.

**Authors:**

Sahel Azizpour: Donders institute for brain, cognition and behaviour; Britta U. Westner: Donders institute for brain, cognition and behaviour; Umut Guclu: Donders institute for brain, cognition and behaviour; Linda Geerligs: Donders institute for brain, cognition and behaviour

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Semantic Leakage Enables Lie Detection, but First-Person Pronouns and Verbosity Can Get in the Way of Detection

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