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Tutorials: Nov 13, 2011, Shanghai, China
Main Conference: Nov 14-17, 2011, Shanghai, China
Workshops: Nov 18, 2011, Hangzhou, China
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   Final program of ICONIP2011 and book of abstracts are available now.  
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Special Session on Brain-Realistic Models for Learning, Memory and Embodied Cognition


Dr. Huajin Tang
Institute for Infocomm Research, A*STAR, Singapore.
E-mail: htang@i2r.a-star.edu.sg

Dr. Jun Tani
RIKEN Brain Science Institute, Tokyo, Japan.
E-mail: tani@brain.riken.jp


It has been a challenge in neuroscience and computer science for many years to implement brain-style intelligence in an artificial neural system. Artificial intelligence, developed by computer scientists is highly limited in adaptive behavior and learning ability. Therefore, the synthetic neural modeling approach, by developing brain-realistic models and related algorithms with robotic simulation has become a prevailing method to target the core problem of brain-style intelligence. Based on neuro-anatomic and physiological features of local cortical regions and hippocampus as well as their integrated neuropsychological characteristics, the synthetic neural systems are then embedded in robotic system to emulate brain-style cognition and autonomy in a physical environment.

The ICONIP 2011 special session on “Brain-Realistic Models for Learning, Memory and Embodied Cognition�aims to reflect the efforts and achievements of the current research stream, by inviting scientists and researchers to report their state-of-the-art technologies and theories on computational modeling, theory, experiments and applications.

Topics of interest include but not limited to:

The main theme of the special session is brain-realistic models and algorithms for learning, memory and embodied cognition with applications to robotics. Topics of interest include but are not limited to:

  • Cognitive Memory (Associative Memory, Episodic Memory, LTM, STM, Working Memory, etc.)
  • Neural Circuits Modeling and Theory.
  • Neural Information Encoding and Decoding.
  • Neurophysiological Learning and Computing (STDP, Hebbian, recognition, decision making, etc).
  • Neuropsychological Macroscopic Brain Model for Behavior and Dynamic Cognition.
  • Embodied Cognition, Neuro-Robotics, Robotic Cognition and Autonomy, etc.

        Dr. Huajin Tang

        Institute for Infocomm Research, A*STAR, Singapore.

        Email: htang@i2r.a-star.edu.sg

        Dr. Jun Tani

        RIKEN Brain Science Institute, Tokyo, Japan.

        Email: tani@brain.riken.jp

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