Netherlands

The present study investigated the effects of presentational timing, operationalized as different levels of temporal overlap, on cross-modal priming of written words. We used a paradigm where the playback of spoken word primes was shifted relative to the presentation of written targets (asynchronous, partially overlapping, and synchronous presentation). Our participants (n = 48) carried out a speeded lexical decision task on the written targets. Presenting the spoken primes, albeit the words’ onset, before the written targets reduced lexical decision times to both words and pseudowords. Asynchronous presentation of the spoken primes resulted in the largest difference between word and pseudoword response times. We discuss our results in relation to the mental structure of human word knowledge and in the context of word form acquisition.

**Authors:**

Johanna Funk: Philipps University of Marburg; Louis Terenci Hessler Carbonell: Philipps Universität Marburg ; Denise Al-Rubaye-Jung: DSA; Michelle Morgenstern: Philipps-Universität Marburg; Elisa Schmied: Philipps-Universität Marburg ; Jasemina Tzallas: Philipps-Universität Marburg ; Florian Hintz: Philipps University

CogSci 2024

Cross-modal priming of written words across different timing conditions

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**
<div style="position:relative;padding-top:0;width:900px;height:500px;"><iframe style="position:absolute;border:none;width:100%;height:100%;left:0;top:0;" src="https://online.fliphtml5.com/ebtyf/cble/" seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe></div>


**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.

You need to log in with the email address you registered with. Access credentials have been sent to your email. 

Please be sure to check your spam and other email folders if you do not see an email confirmation right away.

Please log in to explore this event.

It looks like you are not registered for this event. 

To access the site please register [**here**](https://cognitivesciencesociety.org/registration/). 

Please register!

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

What words are central in our semantic representations? In this experiment, we compared the core vocabulary derived from different association-based and language-based distributional models of semantic representation. Our question was: what kinds of words are easiest to guess given the surrounding sentential context? This task strongly resembles the prediction tasks on which distributional language models are trained, so core words from distributional models might be expected to be easier to guess. Results from 667 participants revealed that people's guesses were affected by word predictability, but that aspects of their performance could not be explained by distributional language models and were better captured by association-based semantic representations.

**Authors:**

Andrew Wang: The University of Melbourne; Simon De Deyne: University of Melbourne; Meredith McKague: University of Melbourne; Andrew Perfors: University of Melbourne

Word prediction is more than just predictability: An investigation of core vocabulary

It has been proposed that Chinese classifiers facilitate efficient communication by reducing the noun uncertainty in context. Although recent evidence has undermined this proposal, it was obtained using the common method of equating noun occurrence probabilities with corpus frequencies. This method implicity assumes words occur uniformly across contexts, yet this is inconsistent with empirical findings showing word distributions to be bursty. We hypothesized that if language users are sensitive to burstiness, and if classifiers provide information about upcoming nouns, this information will be less important in reducing uncertainty about noun after their first mention. We show that classifier usage provides more information at earlier mentions of nouns and and less information at later mentions, and that the actual classifier distribution appears inconsistent with previous proposals. These results support the idea that classifiers facilitate efficient communication and indicate that language users representations of lexical probabilities in context are dynamic.

**Authors:**

Sihan Chen: MIT; Edward Gibson: Massachusetts Institute of Technology; Michael Ramscar: University of Tübingen

Availability, informatively and bustiness: Why average corpus measures are an inaccurate guide to surprisal in language

Recent advances in generative language models, such as ChatGPT, have demonstrated an uncanny ability to produce texts that appear to be comparable to those produced by humans. Several key empirical results related to human processing of language, such as analogical reasoning, have been replicated using these models. Nevertheless, there are some important differences between the language generated by these models and language produced by humans. In this paper, I examine how LLMs performs on two pronoun disambiguation tasks reported on by Rhode, Levy, and Kehler (2011) and Sagi and Rips (2014). While LLMs performed reasonably in these tasks, their responses demonstrate stronger language-based biases while the influence of world knowledge, such as causal relationships, was lessened. Because LLMs replicate language produced by humans, these results can help shed light on which aspects of language use are directly encoded in language and which require additional reasoning faculties beyond language processing.

**Authors:**

Eyal Sagi: University of St. Francis

Large Language Models and Human Discourse Processing

Polysemy is pervasive in modern language and represents one key factor that allows for the unlimited expressive potential of human language. One important process of historical meaning extension is that of metaphor (Anderson 2017). Recently, the paradigm of Experimental Semiotics has been proposed as a novel methodology to investigate semantic change (Bowerman & Smith 2022). In experimental semiotics, participants have to converge on a novel signalling system in the absence of a shared language. Here we adopt this approach to experimentally investigate the role of metaphor in meaning extensions. Specifically, we will present results of a study in which participants have to communicate about a novel meaning space in a referential communication game. Importantly, participants will only be able to use symbols for which they have previously established symbol-meaning mappings in a prior game. The results show to which degree participants make use of metaphor in in this task.

**Authors:**

Michael Pleyer: Nicolaus Copernicus University in Toruń; Darya Namednikava: Centre for Language Evolution Studies, Nicolaus Copernicus University ; Klaudia Karkowska: Nicolaus Copernicus University; Svetlana Kuleshova: Nicolaus Copernicus University in Torun; Marek Placiński: Nicolaus Copernicus University in Toruń; Slawomir Wacewicz: Nicolaus Copernicus University

An Experimental-Semiotic Approach to the Emergence of Metaphor and Polysemy in Interaction

Experiments in psycholinguistics allow us to test hypotheses and build theories. However, psycholinguistic experiments often suffer from low ecological validity, because participants are often required to perform an unusual task in the face of unusual materials. In the current experiment, we test the predictions of Noisy Channel Processing in a naturalistic task: identifying the lyrics of a song. We conducted an experiment where participants heard short excerpts from songs and then indicated which one out of four possible transcriptions they had heard. We found that the predictions of Noisy Channel Processing bear out: options with higher prior and likelihood were chosen more often by participants as the heard song lyrics. Thus, Noisy Channel Processing is successful in explaining the everyday phenomenon of misheard song lyrics. More broadly, this suggests that Noisy Channel Processing captures everyday language processing, and that it is not dependent on unnatural experimental tasks and materials.

**Authors:**

Moshe Poliak: MIT; Hannah Kimura: MIT; Edward Gibson: Massachusetts of Institute Technology

Mis-Heard Lyrics: an Ecologically-Valid Test of Noisy Channel Processing

This paper presents prevalence norms collected from a representative sample of Singapore English speakers for a set of 240 concepts unique to Singapore English. Prevalence refers to the proportion of people who know or recognize a particular concept. Because large-scale, diachronic language corpora are scarce for non-standard varieties of English, the present study aims to establish the collection of prevalence norms from a cross-sectional sample as a potential alternative for tracking changes in word usage patterns over time. Preliminary analyses indicate that lexical knowledge of Singapore English concepts differs across gender, age, and ethnic groups. In particular, while most concepts are generally well known, some concepts are better known by younger participants and others are better known by older participants. These results underline the dynamic nature of Singapore English vocabulary and demonstrate how simple psycholinguistic tasks could be used to study lexical change in under-resourced languages and varieties.

**Authors:**

Cynthia S.Q. Siew: National University of Singapore

Tracking Lexical Knowledge of Concepts Unique to Singapore English Among Speakers of Singapore English

We investigated the processing and interpretation of aspectual coercion in the case of non-culminating accomplishments in English and German, two languages which differ in interesting ways in their aspectual properties. Two offline experiments employing an inference rating task provide evidence that non-culminating accomplishments in both languages actually involve a shift in interpretation. Four self-paced reading experiments furthermore show that this type of coercion isn't costly - neither in German, a language lacking grammatical aspect, nor in English with an aspectual opposition between progressive and perfective simple past forms. This lack of online effect in processing coercion was obtained in a first pair experiments using adverbial modification (sentence-internally) within the verb phrase and in a second pair of experiments in which aspectual coercion was triggered in a subsequent discourse unit. Finding no processing difficulty is in line with previous results for this type of aspectual coercion in German, but is inconsistent with findings reported for English (Bott & Hamm, 2014). A final stops-making-sense experiment replicates the lack of effect for English and furthermore shows that the processing of non-culminating accomplishments does not incur a processing effect even in a task calling for immediate full interpretation. The present study thus adds to existing evidence that aspectual coercion does not necessarily incur processing costs (Pickering, McElree, Frisson, Chen &Traxler, 2006).

**Authors:**

Oliver Bott: Bielefeld University; Torgrim Solstad: Bielefeld University; Jens Michaelis: Bielefeld University

Processing non-culminating accomplishments across languages

This research explores the potential of machine learning (ML) in identifying vocal markers for schizophrenia. While previous research showed that voice-based ML models can accurately predict schizophrenia diagnosis and symptoms, it is unclear to what extent such ML markers generalize to different clinical subpopulations and languages: the assessment of generalization performance is however crucial for testing their clinical applicability.
We systematically examined voice-based ML model performance on a large cross-linguistic dataset (3 languages: Danish, German, Chinese). Employing a rigorous pipeline to minimize overfitting, including cross-validated training sets and multilingual models, we assessed generalization on participants with schizophrenia and controls speaking the same or different languages. Model performance was comparable to state-of-the art findings (F1-score ~ 0.75) within the same language; however, models did not generalize well - showing a substantial decrease - when tested on new languages, and the performance of multilingual models was also generally low (F1-score ~ 0.50).

**Authors:**

Alberto Parola: Copenhagen University; Astrid Rybner: Aarhus University; Emil Trenckner Jessen: Aarhus University; Stine Nyhus Larsen: Aarhus University; Marie Damsgaard Mortensen: Aarhus University; Arndis Simonsen: Aarhus University; Yuan Zhou: Chinese Academy of Sciences; Katja Koelkebeck: Hospital and Institute of the University of Duisburg-Essen; Vibeke Bliksted: Aarhus University; Riccardo Fusaroli: Aarhus University

Voice markers of schizophrenia: assessing the generalizability of machine learning models and their clinical applicability

Most Chinese words are compounds formed through the combination of meaningful characters. Yet, due to compositional complexity, it is poorly understood how this compositional process would affect the access to the whole-word meaning. In the present study, we turned to the recent development in compositional distributional semantics (Marelli et al., 2017), and employed a deep neural network to learn the less-than-systematic relationship between the constituent characters and the compound words. Based on the composed representations as derived from the computational model, we quantified the extent to which the compound meaning can be predicted by nonlinearly combining the constituent meanings, i.e., the degree to which the characters could provide reliable information to access the compound meaning. We observed the effect of compositionality, as operationalized by the computed metrics, on compound recognition, over and above the effects of constituent character properties and compound properties. More importantly, we found that this effect was increasingly stronger when holistic access to the compound meaning became more challenging. These findings therefore, from a computational perspective, provided new evidence for the compositional process involved in Chinese word recognition, which also shed light on the universal process of compound comprehension.

**Authors:**

Tianqi Wang: The University of Hong Kong; Xu Xu: Shanghai Jiao Tong University

Composition as nonlinear combination in semantic space: Exploring the effect of compositionality on Chinese compound recognition

People sometimes explicitly announce that they are being sarcastic. The announcement appears to be particularly common in text-based conversations where prosodic cues are more difficult to identify. In certain cases, the tone of a comment is sufficient to determine non-literal meaning. But what happens in the absence of these features, or when context forces us to explicitly caveat our sarcasm? In this study, we examine Reddit comments from \texttt{r/AskReddit} to see the features that are present in comments tagged with \say{/s}, a convention on the platform for users to denote sarcasm. We found that a host of cues which mimic prosody, and other aspects of figures of speech, were inconsistent predictors of announced sarcasm. In contrast, when talking about sociomoral topics such as politics or race, users were more likely to tag their comments with \say{/s}. This suggests that we are more likely to announce sarcasm in text-based conversations where misinterpretation would be detrimental.

**Authors:**

Joshua Hew: University of Edinburgh; Aida Tarighat: University of Edinburgh; Martin Corley: University of Edinburgh; Zachary Horne: University of Edinburgh

Premium content

Downloads

Next from CogSci 2024

Word prediction is more than just predictability: An investigation of core vocabulary

Similar lecture

Balancing on the Edge: Review and Computational Framework on the Dynamics of Fear of Falling and Fear of Heights in Postural Control