P-2B: Posters 2B
Fri, 25 Aug, 13:00 - 15:00 United Kingdom Time (UTC +1)
Location: Marquee
Session Type: Poster
Track: Cognitive science

P-2B.61: Characterising representation dynamics in recurrent neural networks for object recognition

Sushrut Thorat, Adrien Doerig, Tim Kietzmann, Osnabrück University, Germany

P-2B.63: Neural correlates of uncertainty- and reward-based strategies for directed exploration

Alexander Paunov, Maëva L’Hôtellier, INSERM / CEA / University Paris-Saclay, France; Dalin Guo, Zoe He, University of California San Diego, United States; Angela Yu, Technical University of Darmstadt, Germany; Florent Meyniel, INSERM / CEA / University Paris-Saclay, France

P-2B.64: Learning from Disinformation

Juan Vidal-Perez, Raymond J. Dolan, UCL, United Kingdom; Rani Moran, Queen Mary University of London, United Kingdom

P-2B.65: Speech features are weighted by selective attention

Nika Jurov, Grayson Wolf, William Idsardi, Naomi Feldman, University of Maryland, United States

P-2B.66: Distilling the neural code for word recognition

Aakash Agrawal, Stanislas Dehaene, Neurospin,, France

P-2B.67: Interplay of episodic memory and recency effects in an odor-in-context association task

Nikolaos Chrysanthidis, Florian Fiebig, KTH Royal Institute of Technology, Sweden; Anders Lansner, KTH Royal Institute of Technology, Stockholm University, Sweden; Pawel Herman, KTH Royal Institute of Technology, Digital Futures, Sweden

P-2B.68: An Interplay of Nucleus Accumbens and Anterior Insula Activity Predicts Risky Choice

Leili Mortazavi, Brian Knutson, Stanford University, United States

P-2B.69: Unravelling the computational mechanisms underlying choice history biases.

Robin Vloeberghs, KU Leuven, Belgium; Anne Urai, Leiden University, Netherlands; Kobe Desender, KU Leuven, Belgium

P-2B.71: EEG-fMRI fusion analysis of attention and visual working memory

Viljami Salmela, University of Helsinki, Finland; Lijing Guo, Sichuan Normal University, China; Kimmo Alho, University of Helsinki, Finland; Chaoxiong Ye, University of Jyväskylä, Finland

P-2B.72: Predictive Coding Meets Deep Learning: Learning By Predicting Representations

Ibrahim Hashim, Mario Senden, Rainer Goebel, Maastricht University, Netherlands

P-2B.73: Enumerating and discovering highly discriminative tasks for probing the cognitive architecture underlying complex behavior

Tzuhsuan Ma, Rishika Mohanta, Glenn Turner, Ann Hermundstad, HHMI Janelia Research Campus, United States

P-2B.74: Common neural choice signals emerge artifactually amidst multiple distinct value signals

Romy Froemer, University of Birmingham, United Kingdom; Matthew R. Nassar, Brown University, United States; Benedikt V. Ehinger, University of Stuttgart, Germany; Amitai Shenhav, Brown University, United States

P-2B.75: Leveraging Artificial Neural Networks to Enhance Diagnostic Efficiency in Autism Spectrum Disorder: A Study on Facial Emotion Recognition

Kushin Mukherjee, University of Wisconsin-Madison, United States; Na Yeon Kim, California Institute of Technology, United States; Shirin Taghian Alamooti, York University, Canada; Ralph Adolphs, California Institite of Technology, United States; Kohitij Kar, York University, Canada

P-2B.76: Probing Brain Context-Sensitivity with Masked-Attention Generation

Alexandre Pasquiou, Inria, France; Yair Lakretz, INSERM, CEA, France; Bertrand Thirion, Inria, France; Christophe Pallier, INSERM, CEA, France

P-2B.77: Generic Discriminative Features Exhibit Signatures of Human Numerical Perception

Daniel Janini, Talia Konkle, George Alvarez, Harvard University, United States

P-2B.78: Face-voice –integration in dorsal STS

Ilkka Muukkonen, Viljami Salmela, University of Helsinki, Finland

P-2B.79: Optimal feedback control under uncertainty explains errors, variability and behavioral strategies in human navigation

Fabian Kessler, Julia Frankenstein, Constantin A. Rothkopf, TU Darmstadt, Germany

P-2B.80: Allocentric representation of goal locations at reward-time but not during navigation in mouse mPFC

Peter Doohan, Beatriz Godinho, Mark Walton, Timothy Behrens, Thomas Akam, University of Oxford, United Kingdom

P-2B.81: Hierarchical Planning using Active Inference and Successor Representations

Prashant Rangarajan, Rajesh P. N. Rao, University of Washington, United States

P-2B.82: Abstract representations encoded by human hippocampal neurons support behavioral inference and can be induced through verbal instruction.

Hristos Courellis, Juri Minxha, California Institute of Technology, United States; Araceli Cardenas, Taufik Valiante, Toronto Western Hospital, Canada; Adam Mamelak, Cedars-Sinai Medical Center, United States; Ralph Adolphs, California Institute of Technology, United States; Stefano Fusi, Columbia University, United States; Ueli Rutishauser, California Institute of Technology, United States

P-2B.83: A visuospatial reference frame structures perceptual and memory interactions

Adam Steel, Dartmouth College, United States; Edward Silson, University of Edinburgh, United Kingdom; Brenda Garcia, Caroline Robertson, Dartmouth College, United States

P-2B.84: Two determinants of adaptability in learning magnitudes and probabilities

Cedric Foucault, Florent Meyniel, University of Paris-Saclay, France

P-2B.85: A Hidden Markov Model Reveals Neural Correlates of Motivation-States in Monkeys

Luke Priestley, Matthew Rushworth, Nima Khalighinejad, University of Oxford, United Kingdom

P-2B.86: The Elusive Relationship between Mental Health Profiles and Valence-related Biases in Reinforcement Learning

Zoe Koopmans, Sophie Bavard, Stefano Palminteri, École normale supérieure, France

P-2B.87: Selective memory for reward-relevant features is modulated by expertise during reward learning

Yirong Xiong, University of Tübingen, Germany; Nir Moneta, Max Planck Institute for Human Development, Germany; Mihaly Banyai, Max Planck Institute for Biological Cybernetics, Germany; Charley Wu, University of Tübingen, Germany

P-2B.88: Structured Credit Assignment in Mice

Kevin Miller, DeepMind and University College London, United Kingdom; Laurence Freeman, Yu Jin Oh, University College London, United Kingdom; Matthew Botvinick, DeepMind, United Kingdom; Kenneth Harris, University College London, United Kingdom

P-2B.89: Evidence for macroscopic traveling waves from sEEG

David Alexander, Laura Dugué, Université Paris Cité, CNRS, France

P-2B.91: Diagnosing Catastrophe: Large Parts of Accuracy Loss in Continual Learning Can Be Accounted for by Readout Misalignment

Daniel Anthes, Sushrut Thorat, Peter König, Tim Kietzmann, Osnabrück University, Germany

P-2B.92: Using Generated Object Reconstructions to Study Object-based Attention

Seoyoung Ahn, Hossein Adeli, Gregory Zelinsky, Stony Brook University, United States

P-2B.94: Mental Imagery: Weak Vision or Compressed Vision?

Tiasha Saha Roy, Jesse Breedlove, Ghislain St-Yves, Kendrick Kay, Thomas Naselaris, University of Minnesota, United States

P-2B.95: Dimensions That Matter – Interpretable Object Dimensions in Humans and Deep Neural Networks

Florian Mahner, Max Planck Institute for Human Cognitive and Brain Sciences, Germany; Lukas Muttenthaler, TU Berlin, Germany; Umut Güçlü, Donders Institute for Brain, Cognition and Behaviour, Netherlands; Martin Hebart, Max Planck Institute for Human Cognitive and Brain Sciences, Germany

P-2B.96: Consistency or Fluctuations? How Humans Manage Limited Search Capacity Over Consecutive Uncertain Choices

Alice Vidal, Salvador Soto-Faraco, Ruben Moreno-Bote, Universitat Pompeu Fabra, Spain

P-2B.97: Understanding Learning Trajectories With Infinite Hidden Markov Models

Sebastian Bruijns, Max-Planck-Institute Tübingen, Germany; International Brain Laboratory, International Brain Laboratory, Germany; Peter Dayan, Max-Planck-Institute Tübingen, Germany

P-2B.98: Empirically Identifying and Computationally Modelling the Brain-Behaviour Relationship for Human Scene Categorization

Agnessa Karapetian, Antoniya Boyanova, Freie Universität Berlin, Germany; Muthukumar Pandaram, Bernstein Centre for Computational Neuroscience Berlin, Germany; Klaus Obermayer, Technische Universität Berlin, Germany; Tim C. Kietzmann, Universität Osnabrück, Germany; Radoslaw M. Cichy, Freie Universität Berlin, Germany

P-2B.100: Softer labels support more robust generalization

Ruairidh Battleday, Ilia Sucholutsky, Princeton University, United States; Katherine Collins, Adrian Weller, University of Cambridge, United Kingdom; Thomas Griffiths, Princeton University, United States

P-2B.101: Simulating the Scaling of Long-Term Memory Retrieval

Susanne Haridi, Mirko Thalmann, Eric Schulz, Max-Planck Institute for Biological Cybernetics, Germany

P-2B.102: CHASE – A novel neurocomputational approach to assessing mentalization capabilities

Niklas Bürgi, Gökhan Aydogan, University of Zurich, Switzerland; Arkady Konovalov, University of Birmingham, United Kingdom; Christian Ruff, University of Zurich, Switzerland

P-2B.104: One bottleneck is not enough

Mani Hamidi, Mihaly Banyai, Charley Wu, University of TÜBINGEN, Germany

P-2B.105: Monte Carlo Predictive Coding: Representing the Posterior Distribution of Latent States in Predictive Coding Networks

Gaspard Oliviers, Rafal Bogacz, University of Oxford, United Kingdom; Alexander Meulemans, ETH Zurich, Switzerland

P-2B.106: Representational learning in forming relational memory

Quinn Lin, Beijing Normal University, China; Wei Ding, Jia Liu, Tsinghua University, China

P-2B.107: Synergies between Synaptic Working Memory Mechanisms in Spiking Network Models

Florian Fiebig, Nikolaos Chrysanthidis, Anders Lansner, Pawel Herman, KTH Royal Institute of Technology, Sweden

P-2B.108: Precision mapping of human extra-striate visual cortex with high-resolution fMRI inter-subject alignment

Alexis Thual, CEA Neurospin, Inria Saclay, France; Thomas Dighiero-Brecht, Minye Zhan, CEA Neurospin, France; Bertrand Thirion, Inria Saclay, CEA Neurospin, France; Stanislas Dehaene, CEA Neurospin, France

P-2B.109: Feature-disentangled reconstruction of perception from multi-unit recordings

Thirza Dado, Radboud University, Netherlands; Paolo Papale, Antonio Lozano, Netherlands Institute for Neuroscience, Netherlands; Lynn Le, Marcel van Gerven, Radboud University, Netherlands; Pieter Roelfsema, Netherlands Institute for Neuroscience, Netherlands; Yağmur Güçlütürk, Umut Güçlü, Radboud University, Netherlands

P-2B.110: Biases towards compositionally simpler hypotheses are robust and unaffected by learning

Valerio Rubino, University of Trento, Italy; Peter Dayan, Charley Wu, University of Tubingen, Germany

P-2B.111: What aspects of NLP models and brain datasets affect brain-NLP alignment?

SUBBA REDDY OOTA, Inria Bordeaux, France; Mariya Toneva, MPI for Software Systems, Germany

P-2B.112: Normative Modeling of Auditory Memory for Natural Sounds

Bryan Medina, Josh McDermott, Massachusetts Institute of Technology (MIT), United States

P-2B.114: Learning progress and uncompensated rewards as motivational drivers of engagement

Franziska Brändle, Max Planck Institute for Biological Cybernetics, Germany; Charley M. Wu, University of Tübingen, Germany; Eric Schulz, Max Planck Institute for Biological Cybernetics, Germany

P-2B.115: The Dynamic Nature of Procrastination

Peiyuan Zhang, New York University, United States; Yijun Lin, University of Florida, United States; Falk Lieder, Max Planck Institute for Intelligent Systems, Germany; Wei Ji Ma, New York University, United States

P-2B.116: Self-supervised transformers predict dynamics of object-based attention in humans

Hossein Adeli, Seoyoung Ahn, Stony Brook University, United States; Nikolaus Kriegeskorte, Columbia University, United States; Gregory Zelinsky, Stony Brook University, United States

P-2B.117: Latent space decomposition supports efficient less-than-one-shot learning

Ilia Sucholutsky, Thomas L. Griffiths, Princeton University, United States

P-2B.118: A Hierarchical Structure for Perceptual Awareness in the Human Brain

Nadine Dijkstra, Oliver Warrington, Peter Kok, Stephen Fleming, University College London, United Kingdom

P-2B.119: An architecture for zero-shot decision-making using plastic attractors

Sanjay Manohar, Oxford, United Kingdom; Christopher Whyte, Cambridge, United Kingdom; Eva Feredoes, Reading, United Kingdom; Alexandra Woolgar, Cambridge, United Kingdom

P-2B.120: Brain signal variability tracks uncertainty in Bayesian inference

Alexander Skowron, Douglas D. Garrett, Max Planck Institute for Human Development, Germany