The document outlines the development of a brain simulator, discussing its connection to brain informatics, the current status of brain simulators, and the proposed architecture and approaches. It emphasizes the need for a modular modeling approach to simplify complex brain functions and interactions. The next steps focus on creating a comprehensive, extendable framework for brain simulation, integrating neuroanatomy and cognitive psychology.

1. On the Development of
a Brain Simulator
Speaker : Jimmy Lu
Advisor : Hsing Mei
Web Computing Laboratory(WECO Lab)
Computer Science and Information Engineering Department
Fu Jen Catholic University

2. Outline
 Reviews of the braininformatics
 Current status of brain simulators
 The approaches and architecture of the
proposed brain simulator
 Modular models of brain function
 Next steps and the focus
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3. Reviews of The Brain Informatics
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4. Web Infrastructure
Overlay Model
Layered Protocol
Deep Web Intelligence
Deep Web
Intelligence
Behavioral : Learning, Education
Cognitive : Psychology
Cognitive Neuroscience
Science (Brain)
Macro : Brain
Micro : Neuron
BrainInformatics
The relationship between the braininformatics and other research fields
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5. Network analysis
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6. Three basic brain networks
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7. Internet Human Brain
Scale Billions of unit elements 1011 unit elements
Anatomical structure,
Layered structure OSI model network overlay, and
functional outputs
Error correction, Degeneracy
Mechanisms of fault
recomputation of routing mechanism, replaceable
tolerance
pathway functional area
Motif, communities,
Properties of Motif, communities, hubs,
hubs, shortest path way,
complex networks shortest path way, etc.
etc.
Capability of an unit
Versatile Specific
element
Global functions Not shown diverse
Physical structure Stable Dynamic
Internet vs. the human brain
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8. Current Status of the Brain Simulator
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9. Proposed Brain
IBM’s C2 Blue Brain
Simulator
Neuron-Level Neuron-Level Brain-Level
Perspective
Microscopic Microscopic Macroscopic
Nuclei, Region,
Basic Component Neuron Neuron
Tracts
Communication
Connection Synapse Synapse
Pathway
Protocol Data
Communication Electrical Signal Electrical Signal
Unit
layered layered
Architecture P2P Network
Architecture Architecture
Neocortical
Focus Area Cortex Whole Brain
column
Supercomputer Supercomputer Cloud Computing
Computation
Blue Gene Blue Gene Environment
The comparison among C2, Blue Brain and proposed brain simulator
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10. The Approach and Architecture of
Proposed Brain Simulator
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11. Case-based incremental delivery approach
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12. Short Long
Term Term
Time Scale
Sleep Learning Brain Disease Aging
Resting State Decision Brain Disease Neural Darwin
Making Model Model Selection Application Layer
……
REM
Stage N1
Stage N2 Network Network (Behavior/Disease
Damage Model Development
Stage N3
Model
Layer)
Causal Layer
…… (Overlay Layer)
By case
……… Processing Layer
Thalamocortical Motif Polysynaptic Loops Diffuse Ascending Projection
Brain Connectivity
Layer

13. Modular Models of Brain Function
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14. Modular approach
 Much of computational neuroscience focuses on
properties of single neurons and small circuits
 However, modular approach to modeling is needed
 A complex system may be analyzed by being
decomposed into a set of interacting subsystems
because the complexity has been reduced.
 If we try to model “everything all at once” we will
understand nothing
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15. 3 views of modules for modeling
 Modules as brain structures
 Corresponds to physical structure of the human brain
 Modules as schemas
 Combine functionality of actual brain regions in a single
abstract schema
 Decompose a schema into finer schema and simulate their
interaction, and some but not all of them will be mapped
onto detailed neural structures
 Modules as interface
 Designed to help the user interact with the model
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16. A basic model of reflex control of saccades
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17. Neural simulation language
 Neural Simulation Language (NSL) was developed
to support such modular modeling
 Object-oriented approach
 Run atop C++, Java, or Matlab
 http://www.neuralsimulationlanguage.org/
 http://nsl.usc.edu/nsl/Homepage.php
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18. Interoperable simulator (1/2)
 The further issue is "simulator independent"
descriptions of models
 The objective is to separate the model from a
particular software implementation which then allows
modelers to use models from other simulators within
their preferred simulator
 This work is based in XML and can be further
examined at the following:
 Systems Biology Markup Language
(SBML) http://sbml.org/index.psp
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19. Interoperable simulator (2/2)
 CellML http://cellml.org/
 XML for computational neuroscience
(NeuroML) http://www.neuroml.org/
 XML for Neuronal Morphology
Data: http://www.morphml.org/ and http://www.morphml.o
rg:8080/NeuroMLValidator/
 NeuroML Interfaces for GENESIS 3: http://www.genesis-
sim.org/GENESIS/G3
 ChannelDB: http://www.genesis-
sim.org/hbp/channeldb/ChannelDB.html
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20. Next Steps and the Focus
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21. Next Steps and the Focus
 A comprehensive study of the neuroanatomy,
Neurophysiology, and cognitive psychology in order
to design and construct the components and
mechanisms of the brain simulator
 Try to provide a extendable brain simulator
framework, not just a workable application (needs to
be well-architected and -documented)
 Focusing on AD, trying to simulate the dynamicity of
the brain connectivity and the matches between
structural patterns and explicit behavior
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22. Reference
 [1] Wen-Hsien Tseng, Song-Yun Lu, Hsing Mei, “On the development of a
brain simulator”, 2nd ICCCI (2010).
 [2] Michael A Arbib (2007), Scholarpedia,
2(3):1869.doi:10.4249/scholarpedia.1869revision #59679
 [3] Thomas M. Morse (2007), Scholarpedia,
2(4):3036.doi:10.4249/scholarpedia.3036revision #39060
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