Netherlands

Double dissociations were long considered a gold standard for establishing functional modularity. However, Plaut (1995) demonstrated that double dissociations could result without underlying modularity, by damaging an attractor network with separate orthographic, semantic, and phonological layers. Plaut’s model was complex, with 7 sets of units and 13 layers of connections. We investigated whether double dissociations would emerge (in a modular or nonmodular fashion) in a simpler network with two sets of units and two layers of connections. We trained 10 different networks with randomly-initialized weights on these items using backpropagation. After training, we created 10 copies of each network and randomly damaged 10-80% of connections between phonological and semantic nodes in one simulation, and 10-80% of
recurrent semantic connections in another simulation. Double dissociations were apparent at every level of damage to phonological-semantic damage. Semantic-semantic damage led only to concrete deficits. The presence of double dissociations given different degrees of damage in each model reconfirm Plaut’s (1995) findings in a much more “flat” architecture (O’Connor, Cree, &amp; McRae, 2009), with less potential
for modularity. The tendency for concrete impairments given damage to the semantic attractor level is at once surprising and revealing; it demonstrates the division of labor (and partial modularity) that emerges in this network. We will discuss theoretical implications, as well as next steps in this research program.

**Authors:**

Ihintza Malharin: BCBL: Basque Center on Cognition, Brain and Language; Simona Mancini: Basque Center on Cognition, Brain and Language; James Magnuson: University of Connecticut

CogSci 2024

Double Dissociations Emerge in a Flat Attractor Network

**Welcome to ACL-IJCNLP 2021!**

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ACL-IJCNLP 2021

The great event is jointly organized by the Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP).

Double dissociations were long considered a gold standard for establishing functional modularity. However, Plaut (1995) demonstrated that double dissociations could result without underlying modularity, by damaging an attractor network with separate orthographic, semantic, and phonological layers. Plaut’s model was complex, with 7 sets of units and 13 layers of connections. We investigated whether double dissociations would emerge (in a modular or nonmodular fashion) in a simpler network with two sets of units and two layers of connections. We trained 10 different networks with randomly-initialized weights on these items using backpropagation. After training, we created 10 copies of each network and randomly damaged 10-80% of connections between phonological and semantic nodes in one simulation, and 10-80% of
recurrent semantic connections in another simulation. Double dissociations were apparent at every level of damage to phonological-semantic damage. Semantic-semantic damage led only to concrete deficits. The presence of double dissociations given different degrees of damage in each model reconfirm Plaut’s (1995) findings in a much more “flat” architecture (O’Connor, Cree, & McRae, 2009), with less potential
for modularity. The tendency for concrete impairments given damage to the semantic attractor level is at once surprising and revealing; it demonstrates the division of labor (and partial modularity) that emerges in this network. We will discuss theoretical implications, as well as next steps in this research program.

**Authors:**

Ihintza Malharin: BCBL: Basque Center on Cognition, Brain and Language; Simona Mancini: Basque Center on Cognition, Brain and Language; James Magnuson: University of Connecticut

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**
<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.

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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.

Eye tracking is a promising set of methods and tools for assessing cognitive processes in neurodegeneration. Our research aims to examine stimulus-driven eye tracking as a potential disease marker in neurodegenerative conditions by using visual stimuli of perceptual grouping, segmentation, and accentuation (Pinna & Sirigu, 2011), which reveal how elements tend to be grouped in the direction of a discontinuous accent impacting shape perception, directionality effects, and overall structural alignment in visual field. Based on preliminary analysis, there are significant differences in the average number of fixations between clinical and control groups (p = 0.0236). Specifically, there are differences in accentuation stimuli (p= 0.0123). On average, clinical groups have a larger fixation number (x̄= 10.49) if compared to the control group (x̄= 7.78). Additionally, there are variations in the focus of visual attention within specific sets of stimuli between the control and clinical groups.

**Authors:**

Santa Bartušēvica: University of Latvia; Jurgis Skilters: University of Latvia; Liga Zarina: University Of Latvia; Solvita Umbrasko: University of Latvia; Laura Zeļģe: University of Latvia; Ardis Platkājis: Riga Stradins University; Agnese Anna Pastare: Riga Stradins University; Jānis Mednieks: Riga Stradins University; Aleksejs Ševčenko: Riga Stradins University; Edgars Naudiņš: Riga Stradins University; Nauris Zdanovskis: Riga Stradins University

Neurodegenerative constraints in stimulus-driven eye movements

This research explores computational models of decision-making under risk. Our models replace the conventional utility function with an episodic memory retrieval process, dynamically estimating utility by recalling past events. Rather than beginning deliberation with explicit knowledge of choice outcome utilities, the value of an outcome emerges from the stochastic recall of related past experiences. In order to reflect both the cognitive and neural dynamics of episodic recall during decision making, our approach incorporates a computational neuroscience model of the hippocampus. Comparisons between this account and previously published decision-making models demonstrate consistency with patterns of behavior captured by those models, while also making predictions concerning the specific effects of contextually cued memory retrieval. We also propose explorations involving the modeling of interactions between the hippocampus and the prefrontal cortex with the goal of shedding light on the neural basis of deliberation.

**Authors:**

Rebecca Sullivan: University of California, Merced; Hoshmand Malaie: University of California, Merced; David C. Noelle: University of California, Merced

The Emergence of Utility from Episodic Memory in a Model of Decision-Making Under Risk

The structure of social networks modulates our beliefs and choices. However, when making decisions within a thick web of interpersonal relationships, it is often impossible for individuals to consider the topological structure of entire network. So which social connections will be considered and which will be ignored, how will the streamlined representation of network affect behavior? We proposed a computational account whereby individuals with limited cognitive resource represent social networks optimally to facilitate social learning. In 4 separate lab and field studies, network representations derived from our model were compared with those revealed by subjects choices and graph neural network (GNN) trained to mimic human learning. Our model offers a normative explanation for DeGroot learning, one of the most influential heuristics for learning on social networks; unifies a variety of seemingly disparate biases reported in social relationship perception; and provides a window into the cognitive root of important societal conundrums.

**Authors:**

Yulin Dong: Peking University; Xiyuan Wang: Peking University; Yaomin Jiang: Max Planck Institute for Human Development; Muhan Zhang: Peking University; Lusha Zhu: Peking University

Optimal mental representation of social networks explains biases in social learning and perception

Self-other integration plays a vital role in efficient synchronization with other humans. Previous research has shown that in simple rhythmic joint action tasks (e.g., tapping), self-other integration can be described using mathematical models of coupled oscillators, representing within- and between-person action-perception links. The present study focuses on investigating self-other behavioral and inter-brain dynamics (dual-EEG) when synchronization is either the goal of the task itself or rather an emergent phenomenon in complex continuous interactions. More specifically, participants produce improvised movements in a ‘mirror-game’ paradigm while being explicitly asked to synchronize with the partner (synchronized condition) or produce independent movements with visual feedback of each other (spontaneous condition). Mathematical models of coupled oscillators will be used to reveal emergent dynamics of self-other integration on behavioral and neural level. Moreover, we hypothesize that stronger interpersonal synchronization in the spontaneous condition will lead to stronger sensorimotor alpha and beta desynchronization and higher inter-brain synchronization.

**Authors:**

Kyveli Kompatsiari: Technical University of Denmark; Marius Zimmermann: Institute of Psychology; Aliaksandr Dabranau: Technical University of Denmark; Qianliang Li: Technical University of Denmark; Ivana Konvalinka: Technical University of Denmark

Self-other dynamics in spontaneous interpersonal synchronization.

Recognizing the limitations of standard vision assessments in capturing the real-world capabilities of individuals with low vision, we investigated the potential of the Seguin Form Board Test (SFBT), an intelligence assessment employing a visual-tactile shape-fitting task, as an estimator of vision's practical utility. We present findings from 23 children from India, who underwent treatment for congenital bilateral dense cataracts, and 21 control participants. To assess the development of functional visual ability, we conducted the SFBT and the standard measure of visual acuity, before and longitudinally after treatment. We observed a dissociation in the development of shape-fitting and visual acuity. Improvements of patients’ shape-fitting preceded enhancements in their visual acuity post-surgery and emerged even with acuity worse than that of control participants. Our findings highlight the potential of shape-fitting tests, like the SFBT, in reflecting functional performance. This suggests a promising avenue for refining assessments of vision's impact on daily activities.

**Authors:**

Shlomit Ben-Ami: Massachusetts Institute of Technology; Vishakha Shukla: New York University; Priti Gupta: Dr. Shroff's Charity Eye Hospital; Pragya Shah: Dr. Shroff's Charity Eye Hospital; Dr. Chetan Ralekar: Massachusetts Institute of Technology; Dr. Suma Ganesh: Dr. Shroff's Charity Eye Hospital; Dr. Sharon Gilad-Gutnick: Massachusetts Institute of Technology; Paula Rubio-Fernández: Max Planck Institute for Psycholinguistics; Pawan Sinha: Massachusetts Institute of Technology

Form Perception as a Bridge to Real-World Functional Proficiency

In a preregistered experiment, we tested whether interfering with primary motor cortex (M1) activation can change how people construe meaning from language. Participants were presented with sentences describing motor actions and asked to choose between a concrete and an abstract interpretation of their meaning. Prior to this task, participants’ M1 was disrupted using repetitive transcranial magnetic stimulation (rTMS). The results suggested strong evidence against the idea that M1-rTMS affects meaning construction. Additional analyses and experiments suggest that the absence of effect cannot be accounted for by failure to inhibit M1, lack of task validity, or lack of power to detect a small effect. These results do not support a causal role for primary motor cortex in building meaning from action language.

**Authors:**

Pablo Solana: University of Granada; Omar Escámez: University of Granada; Daniel Casasanto: Cornell University; Ana B. Chica: University of Granada; Julio Santiago: University of Granada

Transcranial magnetic stimulation of primary motor cortex does not change meaning construction from action sentences

Bipolar disorder (BD) is a mental health condition
characterized by large fluctuations in goal-directed energy and
mood. BD is defined by the presence of at least one lifetime
episode of mania, a prolonged period of excessive goaldirected
behavior, hyperactivity and elevated mood. In this
work, we use reinforcement learning (RL), a principled model
of goal-directed behavior and learning, to show how augmenting
RL agents with dynamic self-efficacy beliefs can give rise to
a range of symptoms characteristic of the mania phase of BD.
Our simulations demonstrate that a model-free RL agent that
dynamically updates its self-efficacy beliefs learns optimistic
overgeneralized value representations. We suggest that these
representations may underlie several behaviors associated with
mania, such as increased motivational drive and faster initiation
of approach behavior (i.e. impatience). We further show
that agents with more sensitive self-efficacy beliefs display increased
willingness to exert effort in order to achieve higher
goals even in the face of costs, a characteristic that is observed
in individuals at risk for BD. Finally, unrealistically high selfefficacy
beliefs that emerged with learning were accompanied
by behaviors such as distractibility and compulsive action selection
that have clinical parallels to symptoms of mania.

**Authors:**

Jing Li: Icahn School of Medicine at Mount Sinai; Angela Radulescu: Icahn School of Medicine at Mount Sinai

Dynamic self-efficacy updating as a computational mechanism of mania emergence

To fully grasp the underlying behavioral and neural processes of social cognition, it has been argued that interactive experimental paradigms and multi-person neuroimaging are needed. However, few studies have examined group interactions, beyond the dyad, as well as how higher-level social properties map onto coordination dynamics. Here, we investigated the role of friendship in group social coordination, by mapping student social networks, and recruiting groups of participants by manipulating their friendship strength. Participants were tasked with pressing their own individual pressure measuring (force) device to reach a designated target force together in groups of three (two friends, one non-friend), with or without live visual feedback, whilst three-person EEG hyperscanning was employed. Preliminary behavioral results indicate that lack of friendship with the other two participants results in greater force production relative to the other participants. We plan to explore the relationship between the social, behavioral, and neural dynamics.

**Authors:**

Qianliang Li: Technical University of Denmark; Kyveli Kompatsiari: Technical University of Denmark; Aliaksandr Dabranau: Technical University of Denmark; Ivana Konvalinka: Technical University of Denmark

The role of friendship in dynamic group coordination

The neural entrainment paradigm (Batterink & Paller, 2017) extended to infant statistical learning (SL; Choi, Batterink, Black, Paller, &Werker, 2020) provides a continuous, implicit measure of learning as infants are exposed to a syllable sequence in a classic word embedding paradigm (cf. Saffran, Aslin, & Newport, 1996). We investigated the potential for feedforward multi-layer perceptrons (MLPs) and Simple Recurrent Networks (SRNs; e.g., Elman, 1990, 1991) to simulate neural entrainment in statistical learning (SL). Similar to human SL, these artificial neural networks are capable of attuning to sequential regularities. We trained MLPs and SRNs on items based on those from Choi et al. (2020), with four 3-syllable word-like patterns in random order. The models’ task was to predict the next syllable given the current syllable. We transformed the model’s initial discrete activation per second into a continuous time-domain signal, expanding them into 1000 samples. Syllable rate was 3Hz, so word rate was 1Hz. Treating nodes like EEG channels, we applied standard neural entrainment analyses that assess phase-locked responses to stimulus characteristics (using Inter-Trial Coherence, or ITC). Both MLPs and SRNs exhibited human-like entrainment, with early entrainment to syllable frequency and later entrainment to word frequency, although only SRNs exhibited a human-like significant correlation between the relative strength of word vs. syllable ITC and preferences for word-like patterns after training. Later entrainment to word-rate is typically interpreted as an index of SL, on the logic that such entrainment emerges as the learner develops representations of word-like patterns. However, we also found ITC at syllable and word rate when we pushed the raw input sequence through our pipeline (with no learning, just a pattern of activations over localist input nodes). We discuss implications for theories of SL as well as interpreting neural entrainment.

**Authors:**

Qihui Xu: Ohio State University; Guro Stensby Sjuls: Norwegian University of Science and Technology; Marina Kalashnikova: Basque Center on Cognition, Brain and Language; James Magnuson: University of Connecticut

Modeling infant cortical tracking of statistical learning in simple recurrent networks

Accumulating behavioral and electrophysiological evidence demonstrates the effects of sentence context on word processing. However, there is a relative scarcity of research investigating both global and local effects during processing, particularly in terms of the influence of grammatically constraining and semantically selectional components, such as Chinese classifiers, as local (in)congruency. In this study, we manipulated congruency between global sentence context and head nouns, as well as congruency between classifiers and head nouns in highly constraining Chinese sentences using a two-by-two factorial design. The results revealed that the semantic and grammatical feature of highly predicted nouns can be pre-activated in advance of the bottom-up input. In addition, both global sentence context and local classifier-noun congruency significantly influenced head noun processing, with neither factor exhibiting overwhelming strength over the other. Both global and local information can be integrated during lexical processing.

**Authors:**

Zhenlin Chen: Leiden University; Leticia Pablos Robles: Leiden University; Niels O. Schiller: City University of Hong Kong

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