Netherlands

Transformer large language models (LLMs) perform exceptionally well across a variety of linguistic tasks. These models represent relationships between words in a sentence via “attention heads”, which assign weights between different words. Some attention heads automatically learn to “specialize” in identifying particular syntactic dependencies. Are syntactic computations in such heads encapsulated from non-syntactic information? Or are they penetrable to external information, like the human mind where information sources such as semantics influence parsing from the earliest moments? Here, we tested whether syntax-specialized attention heads in two LLMs (BERT, GPT-2) are modulated by the semantic plausibility of their preferred dependency. In 6 out of 7 cases, we found that implausible sentences reduce attention between words constituting a head’s preferred dependency. Therefore, even in heads that are best candidates for syntactic encapsulation, syntax is penetrable to semantics. These data are broadly consistent with the integration of syntax and semantics in human minds.0

CogSci 2024

Evidence Against Syntactic Encapsulation in Large Language Models

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ACL 2024

The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) will take place in Bangkok, Thailand from August 11th to 16th, 2024. More information will be announced soon.

technical paper

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

The framework of event perception suggests that people segment continuous perceptual input into discrete events by forming mental representations of ongoing activity. Prior work extending the segmentation framework to emotion perception shows that a richer emotion vocabulary is associated with segmentation of emotion events in greater agreement with the cultural ingroup. However, little is known about how labeling behaviors themselves shape the segmentation of emotion events. Here, we look at the effect of labeling on emotion segmentation. Participants were randomly assigned to simply segment videos into discrete emotion events or to segment only when an emotion label is available and to label the segmented event. We found that compared to the group that segmented without providing labels, the group that segmented with explicit labeling behaviors were less sensitive at discriminating emotion events from non-emotion events and more conservative to identify an emotion event. The results are discussed with respect to competing theoretical accounts of the impact of labeling on emotion perception and suggest that the conceptual broadening account (where labels invoke idiographic emotion representations) may best account for the findings.0

Labeling Behaviors are Associated with the Identification of Emotion Events

Events of social exchange, such as givings and tradings, are uniquely prevalent in human societies and cognitively privileged even at early stages of development. Such events may be represented as having 3 or even 4 participants. To do so in visual working memory would be at the limit of the system, which throughout development can track only 3 to 4 items. Using a case study of trading, we ask (i) whether adults can track all four participants in a trading scene, and (ii) whether they do so by chunking the scene into two giving events, each with 3 participants, to avoid placing the visual working memory system at its limit. We find that adults represent this scene under a 4-participant concept, and do not view the trade as two sequential giving events. We discuss further implications for event perception and verb learning in development.0

Visual perception supports 4-place event representations: A case study of TRADING

One feature of mental time travel is the ability to recursively embed temporal perspectives across different times: humans can remember how we anticipated the future and anticipate how we will remember the past. This recursive structure might be formalised in terms of a “grammar” that is reflective of but more general than linguistic notions of absolute and relative tense. Here I provide a foundation for this grammatical framework, emphasising a bounded (rather than unbounded) role of recursion in supporting mental time travel to a limited temporal depth and to actual and possible scenarios. Anticipated counterfactual thinking, for instance, entails three levels of mental time travel to a possible scenario (“in the future I will reflect on how my past self could have taken a different future action”) and is implicated in complex human decision-making. This perspective calls for further research into the nature and origins of recursive mental time travel.0

Remembered Futures and Anticipated Pasts: The Recursive Grammar of Mental Time Travel

Seeing a person preparing to perform an action and later remembering having seen subsequent phases of the action, but not previous phases. This is what a theory on the role of the motor system in the creation and recovery of memories predicts can happen. We investigate memory for action after viewing an image representing an actor acting on a series of everyday objects. The participants in one experiment viewed a series of still photos of unfolding actions on objects (e.g., blowing the nose), and 15 minutes later they were asked to complete a recognition task. At recognition, participants viewed photos representing temporally distant moments, backward or forward in time compared to the original, along with the same photos seen at encoding. Results showed that participants tended to accept forward photos more than backward photos. In a pilot study, we explored the role of the temporal distance between encoding and recognition. Results showed that when 3 days elapsed between the encoding and recognition phases, participants did not tend to accept forward photos more than backward photos.0

False Memories of Actions: When Motor Simulation is Deceptive

A Federated Graph Learning Framework for Brain Connectome

Reservoir computing (RC) offers distinct advantages in extracting spatiotemporal information with low training costs by separating recurrent neural networks into a fixed network with recurrent connections. The quality of the fixed network, known as the reservoir, plays a pivotal role in the performance of the RC system. Our work aims to provide a unified synaptic development framework for RC, constructing a more biologically plausible reservoir to model and understand the neural networks development within the human brain. In this paper, we propose an Autonomous Synaptic Development Reservoir Computing model (ASD-RC) based on an adaptive network of phase oscillators. The reservoir autonomously adjusts the distribution of connection weights in response to external stimuli, forming a task-specific structure. Through experiments and theoretical analyses, we demonstrate that ASD-RC can emulate various synaptic development rules of biological neural networks in \textit{vivo}, including the Hebbian rule and STDP. Furthermore, experiments reveal that combining different development rules can enhance performance on prediction tasks compared to using a single development rule, showcasing the emergence and effects of synergistic development that improve information processing capacity.0

Unveiling the Synergistic Effects: A Unified Autonomous Synaptic Development Mechanism for Reservoir Computing

Decoding naturalistic stimuli from neural recordings is a significant challenge in systems neuroscience, primarily due to the high-dimensional and nonlinear nature of stimulus-response interactions, and is further exacerbated by the limited availability and noisiness of neural data. While contemporary approaches that incorporate generative models, such as Generative Adversarial Networks (GANs), attempt to address these issues by mapping neural responses to latent representations, they do not fully overcome these obstacles. In this work, we present a novel paradigm of differential neural decoding (dicoding) that focuses on the relative changes in response patterns, which not only expands the neural training data quadratically but also inherently denoises it. To determine the corresponding stimulus changes, this method leverages the Euclidean and feature-disentangled properties of the underlying latents through vector arithmetic. As such, we not only effectively exploit the latent space but also achieve semantically meaningful latent offsets in the context of the stimuli, resulting in improved sample efficiency. We trained a decoder to predict changes in latent vectors based on the corresponding changes in neural responses. The absolute latent vector itself was derived by vector addition of the predicted latent change (indicative of stimulus shift) to a reference latent, which was fed to the generator for the reconstruction of the perceived stimulus. Our results show that this geometrically principled approach facilitates more effective reconstruction of naturalistic stimuli from noisy and limited neural data.0

Get more from less: Differential neural decoding for effective reconstruction of perceived naturalistic stimuli from limited and noisy training data

An important issue in the semantic memory literature concerns the relative importance of experience-based sensorimotor versus language corpus-based distributional information in conceptual representations. Here we examine how each sort of information is associated with the EEG response to words in a property verification task in which participants indicated whether or not a property term (such as ”red”) is typically obtained for a concept term (such as ”APPLE”). To define and measure each type of information, we operationalized distributional and sensorimotor information using cosine distance measurements derived from GloVe Embeddings and Lancaster Sensorimotor Norms respectively. We then modeled single-trial EEG responses to property words in a property verification task using regression models. Our findings indicate that semantic processing in this task simultaneously incorporates distributional and sensorimotor information, and their contribution is shaped by task-relevant linguistic context. We aim for our study to contribute to a critical examination of such information operationalizations and also encourage a systematic evaluation of their performance across tasks, particularly for
EEG measurements.0

Effects of Distributional and Sensorimotor Distance Measures on the EEG during Property Verification

The cognitive processes underlying mental folding have been investigated for decades, while the neural correlates associated with this spatial transformation are barely understood. This study combines cognitive modeling with EEG recordings from 41 subjects to investigate the general mechanisms of mental spatial transformation. By linking model-based simulation and electrocortical activity, we identified brain areas involved during mental folding. Our novel approach showed active central parietal and left parietal, as well as occipital areas during spatial storage, while the right parietal cortex was associated with spatial transformation. The left occipital and parietal regions were active especially during visual baseline trials, while the right parietal region exhibited stronger activity for more difficult folding trials, replicating previous results. The varying activation patterns imply different cognitive loads for storage and for transformation depending on task difficulty.0

Identifying Cognitive Processes and Neural Substrates of Spatial Transformation in a Mental Folding Task with Cognitive Modeling

Spatial cognition is fundamental to human behavior, but people differ in how they remember spatial relations, variably using body-based (egocentric) and environment-based (allocentric) spatial reference frames. Despite decades of study, the causes of this variation and flexibility in spatial memory remain unclear. Here we show that people spontaneously use different reference frames on different spatial axes at the same time. When remembering the placement of a target object in a 2-dimensional array, Indigenous Tsimane' adults preferentially used allocentric space to determine lateral placement and egocentric space to determine sagittal placement in the same action. This effect of axis was also significant among US university students, whose overall preference for egocentric space was stronger on the sagittal than lateral axis. These findings support a novel account of spatial cognitive diversity and suggest that people across cultures habitually integrate egocentric and allocentric spatial reference frames into the same action.0

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Labeling Behaviors are Associated with the Identification of Emotion Events

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