Transcript AnimatLab: A Toolkit for Analysis and Simulation of the

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
• 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
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Outline
• What is AnimatLab?
• Why build AnimatLab?
• Modeling and simulation of crayfish
escape behavior
• The next generation AnimatLab and the
Grid
• Summary
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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
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AnimtLab Interface
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System Architecture
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Neural (Behavior) Editor
Create hierarchal neural
circuits with multiple pages
Add nodes to connect
neurons on one page to
neurons on another page
Drag neurons
from the toolbox
into your network
Draw connections
between neurons
to add synapses
Edit the properties
of the selected
neuron
Behavioral Editor
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3D Body Editor
Project Workspace
Data Chart
Property Grid
Behavioral Editor
Simulation Window
Body Plan Editor
Simulation Controller
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Sensory Receptor
Receptive
Fields
A
Receptive Field Gain
Neurons
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2
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One receptive field
can stimulate
multiple neurons
Receptive
Field/Neuron
Pairs
Sensory
Receptive Field
Receptive
Fields
Neurons
A
B
C
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2
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Or one neuron can be
stimulated by multiple
receptive fields
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Simulation
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Data Display
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How does AnimatLab work?
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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
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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
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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
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Related Works
• AnimatLab and other computational
neuroscience tools (e.g. NEURON and
GENESIS)
• AnimatLab and computational
neuroethology
• AnimatLab and biorobots
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Related Works
• Other computational simulations
of animal behavior exist
• But they were built for a specific
animal
• AnimatLab is a general purpose
toolkit
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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
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Crayfish Escape Behavior
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Create a 3D Crayfish Model
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Simulation of Crayfish Escape
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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
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Next Generation AnimatLab
• A more powerful and extensible neural
simulator
• A more extensible and transparent physics
simulator architecture
• A more sophisticated muscle simulator
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Next Generation AnimatLab
• An improved hydrodynamic simulator
• A better 3D body editor
• Optimization for new computer hardware
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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
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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.
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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
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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
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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
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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
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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
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Thank you!
• Questions?
[email protected] (Ying Zhu)
or
[email protected] (Don Edwards)
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