The 5th CiNet Conference: Computation and representation in brains and machines (Registration-closed)

Recent advancements in machine learning and artificial intelligence techniques have facilitated a quantitative and generalizable understanding of representations and computations in the brain. This interdisciplinary trend also opens new opportunities for lively discussions on topics including the effective handling and interpretation of large-scale models and data, the design of brain-inspired machine intelligence, and real-world applications. This conference aims to bring together cognitive and systems neuroscientists as well as AI researchers to discuss the cutting-edge findings and future directions by cross-referencing brain and machine studies.

Presentations and slides partially available

     February 20 (Wed.) 1:30 pm to 22 (Fri.) 6 pm, 2019

     Conference Room, CiNet Bldg. (1-4 Yamadaoka, Suita, Osaka, Japan)


Program: download

     Shun-ichi Amari, RIKEN
        “Statistical Neurodynamics of Deep Networks: Signal Propagation and Fisher Information”
     Matthew Botvinick, DeepMind
        “A distributional code for value in dopaminergic reinforcement learning”
     David Cox, MIT-IBM Watson AI Lab/Harvard University
        “Predictive Coding Models of Perception”
     Dileep George, Vicarious
“Understanding the brain by building machines that generalize like the brain”
     Marcel van Gerven, Radboud University
        “AI-Driven Neuroscience”
     Iris Groen, New York University
        “Mind the gap: comparing multiple models of scene representation in brain and behavior”
     Michael Hanke, Otto-von-Guericke University/Center for Behavioral Brain Sciences
        “Perpetual, decentralized management of digital objects for collaborative open science
         – conclusions from the project”
     Uri Hasson, Princeton University
       “Robust-fit to nature: taking evolutionary perspective for biological (and artificial) neural networks”
     Aapo Hyvärinen, University College London/University of Helsinki
       “Nonlinear independent component analysis: A principled framework for unsupervised learning”
     Yukiyasu Kamitani, Kyoto University/ATR Computational Neuroscience Laboratories
       “Deep image reconstruction from the human brain”
     Shigeru Kitazawa, Osaka University/CiNet
      “Error signals in reaching: neural representations and their roles in optimizing the movement”
     Nikolaus Kriegeskorte, Columbia University
      “Cognitive computational neuroscience of vision”
     Jun Morimoto, ATR/CiNet
       “Model-based approaches to humanoid motor learning”
     Tomoya Nakai, NICT/CiNet
       “Quantitative models reveal the structure and organization of diverse cognitive functions in the human
     Satoshi Nishida, NICT/CiNet
       “Brain decoding of human natural perception using statistical language
 Nishimoto, NICT/CiNet
       “Representation and computation in brains and machines”
     Ana Luísa Pinho, Inria, CEA, Paris-Saclay University
        “Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping of the human brain”
     Odelia Schwartz, University of Miami
        “Image statistics and cortical visual processing: V1, V2, and deep learning”
     Taro Toyoizumi, RIKEN 
        “An Optimization Approach to Understand Biological Search”
     Kai Wang, NEC Corporation
        “Experimental Platform for brain function model design”
     Dan Yamins, Stanford University
       “Cognitively Inspired Artificial Intelligence for Neuroscience”
     Takufumi Yanagisawa, Osaka University/CiNet
       “Semantic decoding of visual stimulus using electrocorticogram and application for BCI”

     National Institute of Information and Communications Technology (NICT)
     Center for Information and Neural Networks (CiNet)

     Grant-in-Aid for Scientific Research on Innovative Areas, MEXT, Japan
        “Chronogenesis: How the Mind Generates Time”
     NEC Corporation
     NTT Data Institute of Management Consulting, Inc.

Financial support:
     Ichimura Foundation for New Technology

Meeting Chair:  Shinji Nishimoto (NICT/CiNet)
Co-chair:  Shigeru Kitazawa (Osaka University/CiNet),  Takafumi Suzuki (NICT/CiNet)
Meeting Director: Takahisa Taguchi (NICT/CiNet)

Language: English
Seating capacity: 

Inquires to:
(Japanese or English)