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AnimatLab: A Toolkit for Analysis and Simulation of the Neural Control of Behavior

SURA Cyberinfrastructure Workshop: Life Sciences and the Grid. AnimatLab: A Toolkit for Analysis and Simulation of the Neural Control of Behavior. Ying Zhu Department of Computer Science Georgia State University. My Research Background.

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AnimatLab: A Toolkit for Analysis and Simulation of the Neural Control of Behavior

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  1. SURA Cyberinfrastructure Workshop: Life Sciences and the Grid AnimatLab: A Toolkit for Analysis and Simulation of the Neural Control of Behavior Ying Zhu Department of Computer Science Georgia State University

  2. My Research Background • Extensive experience on real-time 3D graphics, visual simulation, and medical visualization • Recent projects • 3D visualization and simulation for neuroscience • Collaborative virtual environment for molecular modeling

  3. Outline • What is AnimatLab? • Why build AnimatLab? • Modeling and simulation of crayfish escape behavior • The next generation AnimatLab and the Grid • Summary

  4. What is AnimatLab? • A 3D computer graphics environment for neurobiologists to visualize and test computational models of neurons, neural circuits, sensors, and muscles, and their control of a model animal’s behavior in a physically realistic virtual world • Animat: artificial animals, including physical robots and virtual simulations

  5. AnimtLab Interface

  6. System Architecture

  7. Neural (Behavior) Editor

  8. 3D Body Editor

  9. Sensory Receptor

  10. Simulation

  11. Data Display

  12. How does AnimatLab work?

  13. Why build AnimatLab? • A central goal of neuroscience is to understand how the nervous system is organized to control behavior • This control must be dynamic and depend on a constant dialog between sensory input, including feedback, and motor commands

  14. Why build AnimatLab? • This important dynamic relationship between nervous function and behavior is poorly understood because of technical limitations to record neural activity in freely behaving animals • Currently it is only possible to record from central neurons in restrained or anesthetized animals

  15. Why build AnimatLab? • AnimatLab can help formalize and evaluate hypotheses about the neural and physical mechanisms for dynamic control of behavior by simulating freely behaving animals

  16. Related Works • AnimatLab and other computational neuroscience tools (e.g. NEURON and GENESIS) • AnimatLab and computational neuroethology • AnimatLab and biorobots

  17. Related Works • Other computational simulationsof animal behavior exist • But they were built for a specificanimal • AnimatLab is a general purposetoolkit

  18. Crayfish Escape Behavior • The neural circuits of crayfish escape are among the best understood neural circuits in any animal, and for 60 years have provided a model for sensorimotor integration

  19. Crayfish Escape Behavior

  20. Create a 3D Crayfish Model

  21. Simulation of Crayfish Escape

  22. The Result • We were able to use AnimatLab to simulate the fast abdominal flexion that evokes an upward directed movement of the model crayfish • But the subsequent abdominal re-extension and swimming are ineffective • The challenges: • Need more detailed neural model • Need more sophisticated muscle simulation • Need more realistic crayfish body parts • Some important circuit elements may not have been identified

  23. Next Generation AnimatLab • A more powerful and extensible neural simulator • A more extensible and transparent physics simulator architecture • A more sophisticated muscle simulator

  24. Next Generation AnimatLab • An improved hydrodynamic simulator • A better 3D body editor • Optimization for new computer hardware

  25. AnimtLab and the Grid • Grid computing can • provide the ability to search through vast parameter spaces such as various muscle parameters • allow the user to evolve the neural network, the body of the organism, or both at the same time in order to meet some desired goal

  26. AnimatLab and the Grid • The grid would allow us to perform the search in a parrallel fashion on thousands of computers simultaniously. • This vastly decreases the time it takes to perform such an evaluation.

  27. AnimatLab and the Grid • Grid services will be implemented as a plug-in for AnimatLab with four components • search algorithm • population generator • grid manager • visualization tools

  28. Grid Computing at GSU • GSU is deploying 1000 United Devices license across the campus • We are working closely with Art Vandenberg’s group to take full advantage of this resource as well as SURAgrid

  29. Summary • We have been developing AnimatLab for 2 years • Version 1.0 is expected to be released in the next six months for evaluation and user feedback • Version 2.0 will be our focus for the next 3 – 5 years • Interest among neuroscientists is high • AnimatLab will be a useful toolkit for computational neuroscience

  30. The Team • PI: Donald H. Edwards • Professor of Biology • Director of GSU Brains & Behavior Program • Co-PI: Ying Zhu (Computer Science) and Gennady Cymbalyuk (Physics) • Collaborators: William Heitler (University of St. Andrews, UK) and Andrei Olifer (Emory University) • PhD students: David Cofer, James Reid

  31. Sponsors Preliminary work has been funded by • NIH P20-GM065762 • GSU Brains & Behavior Program • A grant proposal was submitted to NSF Collaborative Research in Computational Neuroscience (CRCNS) in January 2006

  32. Thank you! • Questions? yzhu@cs.gsu.edu (Ying Zhu) or biodhe@langate.gsu.edu (Don Edwards)

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