Brain-inspired IT 3, Volume 3
Kiyohisa Natsume, Akitoshi Hanazawa, Tsutomu Miki
Elsevier, 2007 - Computers - 310 pages
BRAIN-INSPIRED IT III is the third volume of the Brain-Inspired IT series intended for researchers and students who are involved or interested in the brain sciences, technology, and engineering. It includes 4 invited papers, 7 COE papers, 57 selected papers from the Third International Symposium BrainIT 2006, which was held in Kitakyushu, Japan, on September 27-29, 2006. The last two International symposiums BrainIT 2004 and 2005 were great success, and provided the participants with good opportunities to exchange valuable information and various ideas from multidisciplinary research area. We made a survey of the current state-of-the-art and explored the possibility to establish new research fields in the Brain-Inspired Information Technology. The first 4 invited papers are contributed by outstanding researchers in the area, Dr. M. Kawato (ATR Computational Neuroscience Laboratories), Prof. Ryohei Kanzaki (The University of Tokyo), Prof. Asla Pitkänen (University of Kuopio), Prof. Helge Ritter (Bielefeld University), who were presented in the special and invited sessions of BrainIT2006 to discuss how the brain processes the information and how we apply the processing to technology. Technical papers cover vision system, other sensory systems, cognition and languages, learning and memory, behavior and emotion, motor controls, dynamics, neural computation, neural networks, and brain-inspired intelligent machines.
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2007 Published activity actuator adaptive algorithm amygdala astrocytes B.V. All rights behavior Brain Science brain-inspired circle map circuit classifier computational control system Corresponding author cortex dentate gyrus Department of Brain detection dynamics E-mail address edge elements Elsevier B.V. Keywords environment fear conditioning frequency function Furukawa granule cells Hibikino hippocampal Institute of Technology interneurons Japan Japan Abstract Kitakyushu Kyushu Institute learning mechanism membrane method mnSOM mobile robot modular network module monkeys motion motor movement muscle network model neural network neural oscillators neuromorphic neuron model Neurosci noise dots noise shaping nonlinear optic flow orexin output parameter performance pheromone processing proposed Published by Elsevier receptor responses rights reserved rotation self-organizing map sensory shown in Fig shows signal sleep–wake patterns spiking STDP stimulus synaptic weight synchronization synergies taste bud taste bud cells TBCs temporal theta rhythm Type II cells variability velocity visual Wakamatsu-ku www.ics-elsevier.com