Posters.

Decomposing Predictive Information in Social Dynamics

Akira Kawano·EMBL Rome

Neural Unmixing: Separating Recurrent Dynamics and Structured Inputs

Akshay Gautam·University of Edinburgh

An EEG and computational investigation of visual working memory: Bridging the gap between Marr’s levels of analysis

Alberto Petrin·University of Padova

Rethinking Activation Functions in Deep Learning: A Theoretical Physics Perspective

Alejandro Chinea Manrique de Lara·UNED

Intracranial Neural Signatures of Decision Uncertainty Based on an Active Inference Model for Probabilistic Three-Armed Bandit Task

Alessandra N. C. Yu·Icahn School of Medicine at Mount Sinai

An integrative framework for the human sense of control

Alireza Modirshanechi·Helmholtz Munich & MPI Bio Cybernetics

MECHANISTIC FOUNDATIONS OF GOAL-DIRECTED CONTROL

Alma Lago·CSIC, UPV/EHU

From composition to coordination: Network principles governing emergent frog limb circuits

August Winther·University of Copenhagen, Denmark

Embodied Decision Making in Active inference

basile LEBRE·Paris Nanterre University, LICAE

Node-Wise Parameter Estimation in The Virtual Brain via HCP-Informed Optimization on a Mean Head Model

Benedetta Gambosi·Sapienza University of Rome

Discovering Features of Human Decision-Making with Mechanistic Interpretability

Beste Tasci·Helmholtz Munich

A High-Fidelity Whole-Brain Simulation Engine for AI-Driven EEG Source Reconstruction

Christian Buda·Sapienza University of Rome

Physical Network Constraints Generate Lognormal Connectome Architecture Through Multiplicative Branching

Daniel Barabasi·MIT/Harvard

Clique-bait: convergent suboptimal strategies on a visual inference problem in humans and machines

Daniele Tirinnanzi·International School for Advanced Studies (SISSA), Trieste, Italy

Putting Neural Networks to Sleep: Oscillations and Hebbian Learning in RNNs

Dashiell Fairborn·Pomona College

Solving the binding problem with overlapping neural representations

Davide Maioli·University of Groningen

The Nematode Digital Twin: Simulating Neural Dynamics, Behavior, and In Silico Lesions in C. elegans

Davide Nuzzi·Istituto di Scienze e Tecnologie della Cognizione (ISTC) - CNR

Neural encoding of sensory “surprise” in the mouse brain

Diego Benusiglio·EMBL

Neural Signatures of Human Motor Adaptation

Dmitrii Todorov·INSERM / Sorbonne University (Paris, France)

Emergent specialization of distributed networks in cortically-embedded RNNs with macroscopic gradients

Eva Sevenster·University of Bristol

Scaling generative vision models for high level statistics in large images

Ferenc Csikor·HUN-REN Wigner Research Centre for Physics, Budapest, Hungary

Compressibility of Neuronal Activity Across Dynamical Regimes

Lochan Chaudhari·Northeastern University Boston

Egocentric Navigation Induces Square Grids: An Account of Distortions in Grid Cells through Reference Frames

Atri Ghosh·University of Trento

Building higher-order invariance in mouse visual cortex

Miguel Nunez-Ochoa·HHMI Janelia Research Campus

Comparing Neural Dynamics by Identifying Optimal Linearizing Embeddings

Mitchell Ostrow·MIT

Beyond the Deficit: The Neurodivergent Root of OCD as Dysfunctional Expression of an Atypical Cognitive System

Caterina Bartucca·Independent Researcher, University of Turin

Carlos Stein·Night City Labs

Eugenio Bertolini·RIKEN, Pioneering Research Institute, Adaptive Motor Control RIKEN Hakubi Research Team. The University of Tokyo, Graduate School of Engineering.

Yasser Binbisher·University of Southern California

Anna Sofia Lippolis·University of Bologna

Harry Woodward·KCL

Jang Hur·KCL

Kapila Paskarathas·KCL

William Zhang·KCL

Dimitra Maoutsa·Independent

Hearing the Shape of Space: A Spectral Geometric Account of Grid-Cell Scaling

Jesús Reyes Torres·Institute of Computer Science, University of Tartu

Mere exposure to others' exploration strategy is not sufficient for strategy contagion

Dr. Alexandra Witt·RIKEN-CBS

Expected information gain during goal-directed causal learning is encoded and broadcast within the sensorimotor system

Andrea Brovelli·Aix Marseille Université

The hippocampus as a hierarchical predictive map

Changmin Yu·University of Cambridge

Building Brain Anatomy From Scratch With Simple Generative Dynamical Models

Daniel Graham·Hobart and William Smith Colleges

Modeling human synchronization to rhythmic patterns with varying statistical regularities

Dr. Dunia Giomo·Sapienza University of Rome

Hippocampal–Parietal Dissociation in Mapping and Moving Through Conceptual Space

Dr. Giuliano Giari·Center for Mind/Brain Sciences, University of Trento

Human–AI Alignment in Specialized Domains where Experience Is Scarce

Eeshan Hasan·The Ohio State University

Brain-Inspired Recurrent Neural Network Featuring Dendrites for Efficient and Accurate Learning in Timeseries Classification Tasks

Eirini Troullinou·IMBB-FORTH

Decoding Visual Imagery from fMRI Data through Latent Functional Alignment

Fabrizio Spera·Tor Vergata, University of Rome

Surprise-evoked sensorimotor disruptions explained through hierarchical Active Inference

Flàvia Ferrús Marimón·EMBL

DIP-BID: Dual IP-Adapters for Structural Brain-to-Image Decoding from fMRI

Grigorii Rashkov·University of Rome, Tor Vergata

Fleeing is Believing: Adaptive behavior under social threat as an inference process

Hridai Khurana·European Molecular Biology Laboratory, Rome

Dynamic Network Segregation at Inter-task Rest Predicts Structural Transfer in Human Continual Learning

Hyunhoe An·Center for Neuroscience Imaging Research

Somatic Clonal Evolution as a Hidden Constraint on Neural Circuit Stability in Chronic Traumatic Encephalopathy

Irene Antony·Harvard Medical School

Physics-Guided Virtual Sensor Networks for Task-Based Neural Field Reconstruction from OPM-MEG Signals.

Jacob Ninan·Kottackal Business Solutions Private Ltd.

NLDisco: A pipeline for interpretable neural latent discovery

Jai Bhagat·University College London Stanford University Metamorphic

Unifying normative and scaffold models of grid cells

Janis Keck·Max Planck Institute CBS

Neural Manifold Geometry Encodes Feature Fields

Julian Yocum·UC Berkeley

Biological profits of irrational computations in the orbitofrontal cortex

Juliette Bénon·University of Zürich - Zurich Center for Neuroeconomics

Maximizing Memory Capacity in Heterogeneous Networks

Kaining Zhang·Abdus Salam International Centre for Theoretical Physics (ICTP)

Structural basis of functional specialization in the dentate gyrus

Khashayar Baghizadeh·Centre for Genomic Regulation (CRG)

Network Dynamics under Connectivity Variability: Evidence for Topological Stochastic Resonance

Konstantin Nikolic·University of West London, London, UK

Topological features in hippocampus cognitive maps dynamics

Konstantin Sorokin·National Research University Higher School of Economics

Challenging Backpropagation: Evidence for Target-Based Learning in the Neocortex

Lhea Beumer·ETH Zurich

Separate or share? Hierarchical balancing of orthogonalization, alignment, and abstraction in continual learning

Márton Hajnal·HUN-REN Wigner Research Centre for Physics, Budapest, Hungary

Clara Kümpel·ETH Zurich & Gatsby Unit, UCL

Fabian Renz·Max-Planck-Institute for Human Cognitive and Brain Sciences

Francesco Innocenti·University of Oxford

Francisco José Maldonado Torralba·Institute of Computer Science, University of Tartu

Ghanendra Singh·PhD Student Independent Researcher

Gianfrancesco Angelini·Medical Physics Section, Department of Biomedicine and Prevention, University of Rome Tor Vergata

Dr. Hayder Amin·Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE)

Hongkun Wu·University of Edinburgh

Julian Kędys·Poznan Supercomputing and Networking Center, Polish Academy of Sciences

Kirubeswaran Obula Ramesh Babu·Technische Universität Darmstadt

Isabella Costa Maia·Grenoble INP

Signatures of hierarchical, heuristic-guided planning in real-world human conceptual navigation

Denis Lan·University College London

How task difficulty shapes the emergence of temporal ordering in human planning

Dr. Mattia Eluchans·Institute of Cognitive Sciences and Technologies (ISTC-CNR)

Almost-Linear Recurrent Neural Networks as a Forecasting-Based Framework for Assessing Dynamic Connectivity Identifiability in Resting-State fMRI

Leema Hamid·Goethe University Frankfurt

Self-referential behavior as a mechanism for self-regulation

Leo Breston·UCSD

Heterogeneous Grid Attractors: Stability and Geometry in Neuromorphic Systems

Leonardo Martinelli·Institute of Neuroinformatics, UZH & ETH, Zurich

Geometric regularization of representation spaces enables efficient learning of cognitive operators

Liebenow, Paul·Tu Darmstadt

Transformers learn factored representations

Loren Amdahl-Culleton·Astera Institute, Simplex

Generative Modeling of Intracranial EEG: Unveiling the Temporal Signatures of Cognitive Regions

Lorenzo Dall'Olio·IRCCS Istituto delle scienze neurologiche di Bologna

A recurrent circuit supporting both low- and high-dimensional population dynamics

Lorenzo Fontolan·Inserm, France

Learning Latent Representations of Shared Structure in Neural Population Dynamics

Lorenzo Ognibeni·National Research Council (CNR-ISTC), Rome, Italy

Representational bottlenecks induce sequential processing in recurrent neural networks

Marcel Graetz·Champalimaud Centre for the Unknown

Zero-shot learning of complex concepts via conceptual systems alignment

Marco Ciapparelli·University of Trento

Artificial intelligence models can track and collaboratively modulate human memory search dynamics

Mariana Duarte·Champalimaud Foundation

Consequences of synergistic organisation in language models

mariana meireles·UC Berkeley

Incremental alternative sampling as a lens into the temporal and representational resolution of linguistic prediction

Mario Giulianelli·University College London

Artificial Neuroscience: science and engineering of artificial brains

Mark Sandler·Queen Mary University of London

Adaptive Reluctant Plasticity

Mark van Rossum·University of Nottingham

Targeted input selects global spatiotemporal motifs in spatially structured inhibitory networks

Marta Tataryn·University of Copenhagen

Bayesian Model Comparison for Neural Models of Decision Making

Maryam Meghdadi·Helmholtz Institute for Human-Centered AI

The geometry of the neural state space of decisions

Mauro Monsalve·Center for Theoretical Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University

Mixed Selectivity as a Signature of Generalization in Neural Networks

Michele Viscione·ETH Zürich

Perception from Action: How Control Shapes Visual Representations

Mihai Bujanca·Qualcomm XR Labs

Modeling Hebbian Plasticity with Normalization

Mirabel Reid·TU Darmstadt

The influence of Expectations on Sensory Processing during Adversarial Image Recognition

MSc Paulo Ortiz Marto Fonseca·Donders Institute, Radboud University

Temporal encoding profiles of object-based visual attention

Niklas Mueller·University of Amsterdam

Robot Metacognition: Decision Making with Confidence for Tool Invention

Ajith Anil Meera·Neuro AI and Robotics group. Spanish National Research Council

Peter Keffer·University of Osnabrück

Predicting neural responses using scalable Gaussian Processes in closed loop

Pietro Zamberlan·Sorbonne University, Vision Institute.

Confidence Exposes Information-Theoretic Constraints in Decision Making

Poppy Collis·University of Sussex

The Dynamics of Memory: Replay, Diffusion, and Attractor Formation

Priyam Ghosh·Birla Institute of Science and Technology, Pilani

Recovering Neural Connectivity from Sparse Measurements: A Covariance-Based Framework for the Inverse Problem

Quilee Simeon·MIT

Beyond perception: Sequential efficient coding of perceptual and value representations

Saurabh Bedi·University of Zurich (Department of Economics).

Unsupervised Discovery of Individual Differences in Neural Network Models of Behavior

Marvin Mathony·Helmholtz Munich

Oleg Maslennikov·IAP RAS

Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity

Prashant Raju·Independent

Continual learning of one's spatial orientation through causal inference

Ajabi, Zaki·Harvard University

Generative AI collective behavior needs an interactionist paradigm

Bruno Lepri·Bruno Kessler Foundation

The BODHI Framework: Engineering and Testing Epistemic Virtues for Collaborative Intelligence in Clinical Decision Support

Max Lange·MIT / King’s College London

Geometric Stability: The Missing Axis of Representations

Prashant Raju·Independent

Federico Harjes & Prof. Volker Tresp·LMU Munich

Proto-Cognitive Signatures in Perturbed Proof Search

Phil Rohr & Ludwig Pouey·Specter Labs

Biologically inspired constraints reduce solution degeneracy in task-trained RNNs

Pulkit Singh·The University of Chicago

Dynamic recruitment of mixed-selective neurons in the Anterior Cingulate Cortex supports complex task learning

Raimon Bullich Vilarrubias·Institute of Neuroinformatics, ETH Zurich and University of Zurich

Visualizing Voxel Selectivity in Human fMRI with Most Exciting Inputs

Riccardo Vella·IMT School for Advanced Studies, Lucca

Artificial Agency Program: Curiosity, compression, and communication in agents

Richard Csaky·Independent

Foundational Human Modeling: A roadmap for brain-grounded multi-modal AI

Richard Csaky·Independent

Revisiting the Information Bottleneck Through Overparameterisation and Gradient Dynamics

Ryan Singh·University of Sussex

A chess model that captures how humans evaluate and address complexity

Ryan Thomas Philips PhD·Azim Premji University

Making brain decoding interpretable: semantic bottlenecks enable voxel-wise concept maps.

Sara Cammarota·University of Rome, Tor Vergata

Graph-Structured Fusion of EEG and fNIRS for Motor Imagery Decoding: A Case for Geometric Deep Learning in Non-Invasive Upper-Limb Prosthetic BCI

Soham Mehra·Morph Labs

Hierarchical Graph Neural Networks for Mapping sEEG Topologies: Functional Specialization of Frontal vs. Posterior Cortical Zones

Stefano Polizzi, PhD in Physics·IRCCS Istituto delle Scienze Neurologiche di Bologna

Thermodynamics of Linear Regression

Sultan Daniels·UC Berkeley

Preference and belief uncertainties shape electoral outcomes: Democratic Deliberation with Hierarchical Gaussian Filter (HGF) Agent-Based Model

Sylvain Estebe·Aarhus University - Center for Humanities Computing

Sparse Nonlinearity and Low-Dimensional Task Representations Reveal Computational Structure in Multi-Task Learning

Sílvia García Hernández·Goethe University Frankfurt

Neuromorphic Implementation of Insect-inspired Path Integration and Homing Mechanisms

Tangwei Cao·University of Groningen

From Space to Syntax: Scaling Cognitive Maps to Hierarchical Formal Languages with MapFormers

Victor Rambaud·CNRS - LSCP

Noise or Change? A Computational Study of Human Learning in Dynamic Environments

Vignayanandam Ravindernath Muddapu·Azim Premji University

On the Reliability of AI Methods in Drug Discovery: Evaluation of Boltz-2 for Structure and Binding Affinity Prediction

Xibei Zhang·University College London

Neural State Machine for Brain-like State-dependent Execution, Sequential Recall and Online Learning

Xinyun Sheryl Zhang·Technical University of Munich; Institute of NeuroInformatics UZH&ETH

Statistical analysis of small-integer ratios in music cognition

Yannick Jadoul·Sapienza University of Rome

EEGNet-Based Decoding of Human Motor Adaptation from Magnetoencephalography Signals

Yassine Lakhdari·INSERM / Sorbonne University (Paris, France)

COGITAO: A Procedural and Object-Centric Framework to Evaluate Compositional and Systematic Generalization

Yassine Taoudi Benchekroun·Institute of Neuroinformatics, ETH Zurich

A Co-trained Model of Retina and Cortex Traces the Transformation of Visual Computations Across the Hierarchy

Youssef Faragalla (I am a presenter)·Stanford University

Persistent Adaptation through Dual-Timescale Regulation of Ion Channel Properties

Yugarshi Mondal·Brandeis University

Computational cognitive mechanisms of visual working memory in obsessive-compulsive disorder and sex differences

YunxuanZeng·the Second Xiangya Hospital, Central South University

The Library Theorem: Inscription as a Formal Mechanism for Agentic AI Scaling and Alignment

Zachary F. Mainen, Ph.D.·Champalimaud Neuroscience Programme Champalimaud Centre for the Unknown

Goncalo Guiomar·ETH AI Center, University of Zürich

Guillaume Pourcel·University of Groningen

Sander de Haan·ETH Zurich

Spiros Chavlis·IMBB-FORTH

Vito Dichio·École Normale Supérieure (ENS-PSL)

Rumeesa Rais·Reflectx

Concept-guided interpretability via neural chunking

Shuchen Wu·Allen Institute