S26 of ICCPB2011

 May 31 - June 5, 2011
 Organized by IACPB, JSCPB and SCJ
 Supported by the COJWE ('70)
 In cooperation with JNTO

S26

Analysis and Synthesis in Invertebrate Neuroscience:
From Genes, Neural Networks, and Behavior to Robots

Organizers:

Ryohei Kanzaki (Res. Center Adv. Sci. Tech., Univ. Tokyo, Japan)
Mark A. Willis (Dept. Biol., Case Western Reserve Univ., USA)

For many decades, neuroethology has provided insights into how nervous systems organize and generate behavior. Important contributions from work in invertebrate preparations, particularly insects, have been made to brain research in the past, expanding our general understanding of sensory and motor systems. Insects are uniquely suited for multidisciplinary studies in brain research involving a combined approach at various levels, from molecules over single neurons to neural networks, behavior, modeling, and robotics, owing to their seamless accessibility to a wide variety of methodological approaches. In this symposium, we focus on the numerous interdisciplinary contributions of insect models to our recent understanding of sensory and motor control by central nervous systems. Interdisciplinary approaches combining biology, informatics, theory, and engineering will be important for expanding our understanding of nervous systems.

Speakers:

1) Mark A Willis (Case Western Reserve Univ., USA)
Environment, locomotion and sensor structure interact to structure odor-tracking

2) Takeshi Sakurai (Univ. Tokyo, Japan)
A single sex pheromone receptor determines chemical response specificity of sexual behavior in the silkmoth Bombyx mori

3) Hidetoshi Ikeno (Univ. Hyogo, Japan)
Neuroinformatics in invertebrate: neuromodeling of insect sensory motor system

4) Zenon Mathews (Univ. Pompeu Fabra, Spain)
The usage of forward models in dynamic landmark navigation: from insects to robotic mapless autonomous navigators

5) Hirotaka Sato (Univ. California at Berkeley, USA)
Remote radio control of insect flight

6) Ryohei Kanzaki (Univ. Tokyo, Japan)
Insect-robot hybrid system for understanding the neural basis of adaptive behavior