Canada

High-level cognition relies on the ability to determine what the relevant possibilities are in the face of incomplete information. For example, causal judgments require reasoning about the relevant counterfactual possibilities in the context in which the actual events occurred. Similarly, to judge that someone is morally responsible for a given action requires assessing what other actions were available to the agent in the context they acted within. Defining the set of relevant possibilities in a context---what we call the contextual &#39;modal space&#39;---is computationally intractable both because such contexts are not well defined and because there are indefinitely many possibilities that one could consider. Interestingly though, high-level judgments that require reasoning over such possibilities are often made quickly and effortlessly, suggesting that they may recruit a heuristic or implicit representation of the contextually relevant modal space. In this paper we (1) introduce a sampling approach for empirically describing contextual modal spaces, (2) find that modal spaces are shaped by statistical and prescriptive normality, (3) demonstrate that the contextual modal spaces play a domain general role in high-level cognition in the sense that the same modal space is recruited across different domains of reasoning, and finally (4) we provide evidence that such judgments are made on the basis of heuristic representations of the contextual modal space rather than on-line sampling of relevant alternatives.

CogSci 2022

Domain-general modal spaces play a foundational role throughout high-level cognition

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** 
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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) 


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#### **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

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CogSci 2024

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

High-level cognition relies on the ability to determine what the relevant possibilities are in the face of incomplete information. For example, causal judgments require reasoning about the relevant counterfactual possibilities in the context in which the actual events occurred. Similarly, to judge that someone is morally responsible for a given action requires assessing what other actions were available to the agent in the context they acted within. Defining the set of relevant possibilities in a context---what we call the contextual 'modal space'---is computationally intractable both because such contexts are not well defined and because there are indefinitely many possibilities that one could consider. Interestingly though, high-level judgments that require reasoning over such possibilities are often made quickly and effortlessly, suggesting that they may recruit a heuristic or implicit representation of the contextually relevant modal space. In this paper we (1) introduce a sampling approach for empirically describing contextual modal spaces, (2) find that modal spaces are shaped by statistical and prescriptive normality, (3) demonstrate that the contextual modal spaces play a domain general role in high-level cognition in the sense that the same modal space is recruited across different domains of reasoning, and finally (4) we provide evidence that such judgments are made on the basis of heuristic representations of the contextual modal space rather than on-line sampling of relevant alternatives.

technical paper

Join us for CogSci2022! Our 44th Annual Conference will be centered around the theme of diversity, with an accompanying range of keynotes and invited speakers who themselves highlight the diversity of our field. Our three symposia are Cognition across Diverse Populations, Cognition within Diverse Societies, and Global Challenges for Cognitive Science. The conference is being offered in a fully hybrid environment for onsite and online attendees.
 
 [**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2022/07/Cogsci-2022-PAAG-Detailed-July-12final-1.pdf)
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The 44th Annual Meeting of the Cognitive Science Society highlighted research on the theme Cognitive Diversity in addition to the full breadth and diversity of research topics offered by the society’s membership. 





Consider a causal claim like “Tom caused the train delay.” Previous research has shown that the extent to which Tom is seen to act intentionally (i.e., through his own agency) affects the extent to which people agree with this claim. But is this effect of perceived agency a unique phenomenon to causal judgments? Two experiments suggest this may not be the case. Study 1 finds that perceived agency affects people’s under- standing of both causal and non-causal events. Study 2 then finds that while perceptions of agency were similarly involved in people’s understanding of causal and non-causal events, they affected only cases where these events were brought about by animate agents (e.g., people). These results thus suggest that perceptions of agency may have a much more general influence in how people understand events involving agents, and therefore in how they understand the sentences that describe them. We discuss implications for causal cognition, broader research in agency, and the intersections between both and linguistics.

No privileged link between intentionality and causation: Generalizable effects of agency in language

The well-known CRT is a test designed to measure a person’s ‘cognitive reflection’ and used as a predictor of decision making ability. Within the literature, however there is a growing consensus that it shares the majority of its variance with numerical and other cognitive abilities and thus the question increasingly asked is whether it has predictive power beyond existing measures. That is, is there something unique captured by the CRT? This study examines the CRT in parallel with a wide range of individual differences measures reflecting aspects of intelligence (8 CHC broad ability factors), personality (the Big 5 and 30 facets), other decision styles (5 measures) and attention (12 measures covering six aspects of attention). Results indicate that the CRT is, primarily, a cognitive measure, strongly linked to fluid, crystallized and quantitative ability but may also be capturing some distinct aspects of attention relating to the ability to ignore distractors.

What is the CRT? Intelligence, Personality, Decision Style or Attention?

People generally prefer functional explanations over mechanistic ones. Why? One possibility is that people value functional information more. But another possibility is that people don't have an overall preference for functional explanations; Instead, people might just expect this information to precede mechanistic information. Here, we ask whether people have preferences for the order of functional and mechanistic information in explanations. In a first set of studies, we show that adults do in fact prefer that functional information precedes mechanistic. In a second set of studies, we show that people have a more general preference for explanations to address the whole before parts. Finally, we show that the preference for function to precede mechanism may be related to the broader whole-before-parts preference.

A Right Way to Explain? Function, Mechanism, and the Order of Explanations

What kinds of arguments do people make, and what effect do they have on others? Normative constraints on argument-making are as old as philosophy itself, but little is known about the diversity of arguments made in practice. We use NLP tools to extract patterns of argument-making from the Reddit site "Change My View'' (r/CMV). This reveals six distinct argument patterns: not just the familiar deductive and inductive forms, but also arguments about definitions, relevance, possibility and cause, and personal experience. Data from r/CMV also reveal differences in efficacy: personal experience and, to a lesser extent, arguments about causation and examples, are most likely to shift a person's view, while arguments about relevance and presumption are the least. Finally, our methods reveal a gradient of argument-making preferences among users: a two-axis model, of "personal—impersonal'' and "concrete—abstract'', can account for nearly 80% of the strategy variance between individuals.

The Diversity of Argument-Making in the Wild: from Assumptions and Definitions to Causation and Anecdote in Reddit's ``Change My View''

We introduce purely visual paradigms that convey the logical structure of illusory inferences from disjunction: (a AND b) OR c, a |- b. Although the logical information was conveyed entirely via non-linguistic means, we found that the visual paradigms induce reasoning fallacies, though less attractive than their linguistic counterparts. The visual paradigms highlight the role of alternative-based reasoning, or question-answer dynamics, as they control for narrowly interpretive processes that confound the study of their linguistic counterparts. To our knowledge, this is the first work to develop visual paradigms that represent reasoning fallacies committed by adults and involve multiple logical operators non-trivially embedded. Previous studies focused on pre-verbal children or non-human animals, and for this reason limited the scope of research to visually representing logically simple, valid inferences.

Question-answer dynamics in deductive fallacies without language

Investigation of the relationship between cognitive function and academic performance has recently pivoted from differences in intelligence to executive function. To date, these studies have focused disproportionately on samples recruited from Western countries, despite evidence in support of cultural differences in these putative relationships. To address this gap, the present study investigated whether differences in inhibitory and/or attentional control could predict academic performance in a sample of Chinese adolescents (n=42). Participants reported on demographic details and completed both the Simon task and Attention Network Test. Data were analyzed using multiple linear regression controlling for gender, age, SES, English language proficiency, processing speed, and fluid intelligence. Results showed that one index of inhibitory control derived from flanker task performance explained a significant amount of unique variance in academic performance. Our findings provide evidence that executive function, specifically inhibitory control, plays a significant role in academic performance.

Inhibitory Control Predicts Academic Performance Beyond Fluid Intelligence and Processing Speed in English-Immersed Chinese High Schoolers

Parents and teachers often encourage students (e.g., "You can do it!") when they encounter challenges, but these messages are not always effective. Whose encouragement motivates students the most, and why? Here we tested the hypothesis that others’ domain knowledge (e.g., knowledge about course materials) and ability knowledge (e.g., knowledge about students’ abilities in the course) each inform how students evaluate their encouragement. In a large-scale survey, we find that middle school students (n=288) and high school students (n=425) are most likely to seek out and be motivated by encouragement from someone with both domain and ability knowledge, rather than only one or the other. This effect emerged both when students reasoned about hypothetical classmates (Study 1a) and real people in their lives (Study 1b). Moreover, we find that confidence in others' performance estimates linearly increases when they have greater ability and domain knowledge (Study 1c). Collectively, this work suggests that students do not find all encouragement equally motivating. Rather, students find encouragement most motivating when the speaker has knowledge of their abilities and the domain.

Adolescents are most motivated by encouragement from someone who knows their abilities and the domain

Research in cognitive science indicates that the effects of corrective feedback are powerful, but quite variable. Stemming from the Feedback Intervention Theory, we tested two features of feedback that may influence the learner’s attention to the self and ultimately their performance. In this zoom-based experiment, 6 to 8 year old children (N = 102) completed an online learning activity focused on solving mathematical equivalence problems. During the learning activity, children were assigned to different conditions which varied both feedback source (person vs. computer) and feedback type (correct-answer vs. correct-answer+verification). Feedback source was found to affect accuracy, where computer-based feedback resulted in higher accuracy compared to person-based feedback. Additionally, feedback type was found to affect strategy variability. Low knowledge children were more likely to use a variety of different strategies when they received correct-answer only feedback, while high knowledge children were less affected by the presence or absence of verification cues.

The source and type of feedback influence children's mathematics performance

We describe UMA (Unified Model of Arithmetic), a theory of children’s arithmetic implemented as a computational model. UMA extends a theory of fraction arithmetic (Braithwaite et al., 2017) to include arithmetic with whole numbers and decimals. We evaluated UMA in the domain of decimal arithmetic by training the model on problems from a math textbook series, then testing it on decimal arithmetic problems that were solved by 6th and 8th graders in a previous study. UMA’s test performance closely matched that of children, supporting three assumptions of the theory: (1) most errors reflect small deviations from standard procedures, (2) between-problem variations in error rates reflect the distribution of input that learners receive, and (3) individual differences in strategy use reflect underlying variation in learning parameters.

Testing a Unified Model of Arithmetic

Common critiques of natural language processing (NLP)
methods cite their lack of multimodal sensory information,
claiming an inability to learn situated, action-oriented relations
through language alone. Barsalou’s (1983) theory of
ad hoc categories, which are formed from to achieve goals in
real-world scenarios, correspond theoretically to those types
of relations with which language models ought to have great
difficulty. Recent NLP models have developed dynamic approaches
to word representations, where the same word can
have different encodings depending on the context in which it
appears. Testing these models using categorization tasks with
human response data demonstrates that situated properties may
be partially captured through semantic analysis. We discuss
possible ways in which different notions of situatedness may
be distinguished for future development and testing of NLP
models.

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No privileged link between intentionality and causation: Generalizable effects of agency in language

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