On the Development of a Brain Simulator
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The document presents an overview of a proposed brain simulator that models brain structures and functions to enhance understanding of human cognition and related diseases. It highlights brain informatics as an interdisciplinary field that utilizes advanced technologies including network analysis to study complex brain networks. The ongoing development of the simulator aims to create an accurate representation of the human brain for further research and testing.
On the Development of a Brain Simulator
- 1. On the Development of a Brain Simulator Author: Wen-Hsien Tseng, Song-Yun Lu, Hsing Mei Web Computing Laboratory(WECO Lab) Computer Science and Information Engineering Department Fu Jen Catholic University
- 2. Outline Introduction Background The proposed brain simulator Conclusion and future work 2011/6/1 ICCCI 2010 2
- 3. Introduction 2011/6/1 ICCCI 2010 3
- 4. Introduction Brain Informatics (BI) is a new interdisciplinary field to study Human Information Processing System (HIPS) mechanism systematically from both macro and micro points of view by cooperatively using Experimental brain/cognitive technology Web intelligence centric advanced information technology Ex: data mining, graph analysis, layered analysis 2011/6/1 ICCCI 2010 4
- 5. Introduction Web Infrastructure Overlay Model Layered Protocol Deep Web Intelligence Deep Web Intelligence Behavioral : Learning, Education Cognitive : Psychology Macro : Brain Micro : Neuron Cognitive Neuroscience Science (Brain) Brain Informatics 2011/6/1 ICCCI 2010 5
- 6. Introduction Brain simulator is a computer simulation in modeling brain structural dynamics and functionality Can be applied to the studies of brain related disease Ex: Alzheimer’s disease, sleep disorder, epilepsy, etc. It is a great steps toward better understanding of the human brain 2011/6/1 ICCCI 2010 6
- 7. Background 2011/6/1 ICCCI 2010 7
- 8. Background Network analysis Brain networks are complex networks complex network analysis has been developed as an emerging research field It is based on the classical graph theory and mathematical models We applied network analysis to describe the brain networks 2011/6/1 ICCCI 2010 8
- 9. Background The human connectome project Aims to map the connectivity of the human brain. Brain networks Three basic brain networks: Thalamocortical Motif Polysynaptic Loop Structure Diffuse Ascending Projection 2011/6/1 ICCCI 2010 9
- 10. Background Thalamocortical motif Polysynaptic loop Defuse ascending projection 2011/6/1 ICCCI 2010 10
- 11. Background Internet vs. human brain Internet Human Brain Scale Millions of unit elements 1011 unit elements Anatomical structure, network Layered structure OSI model overlay, and functional outputs Mechanisms of fault Error correction, recomputation Degeneracy mechanism, tolerance of routing pathway replaceable functional area Properties of complex Motif, communities, hubs, Motif, communities, hubs, shortest networks shortest path way, etc. path way, etc. Capability of an unit Versatile Specific element Physical structure Relatively Stable Relatively Dynamic 2011/6/1 ICCCI 2010 11
- 12. Background Current Status of the Brain Simulator Our Proposed IBM’s C2 Blue Brain Brain Simulator Neuron-Level Neuron-Level Brain-Level Perspective Microscopic Microscopic Macroscopic Basic Nuclei, Region, Neuron Neuron Component 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 Granularity Fine-grained Fine-grained Coarse-grained 2011/6/1 ICCCI 2010 12
- 13. The Proposed Brain Simulator 2011/6/1 ICCCI 2010 13
- 14. The Proposed Brain Simulator Provides an overlay and P2P network to represent the complexity and dynamicity of brain in time and space Case-based Incremental Delivery Approach Define outline Assign requirements Design system requirements to increments architecture Develop system Validate Integrate Validate Final system increment increment increment system System incomplete 2011/6/1 ICCCI 2010 14
- 15. The Proposed Brain Simulator Architecture A layered architecture is used to design our brain simulator according to our study on human brain. The layered architecture consists of the following layer: Brain Connectivity Layer Processing Layer Causal Layer Application Layer 2011/6/1 ICCCI 2010 15
- 16. 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 16
- 17. Conclusion and Future Work 2011/6/1 ICCCI 2010 17
- 18. Conclusion and Future Work A brain simulator models brain structure and functionality for better understanding how cognition works and rapidly testing their ideas on an accurate replica of the brain The development of proposed brain simulator is still ongoing. In order to simulate more accurate human brain structure and function, further study is required. 2011/6/1 ICCCI 2010 18
- 19. Reference 1. Zhong, N., Li, K., Lu, S.; Chen, L. (Eds.): Brain Informatics. Springer (2010) 2. Sendhoff, B., Körner, E., Sporns, O., Ritter, H., Doya, K. (Eds.): Creating Brain- Like Intelligence: From Basic Principles to Complex Intelligent Systems. Springer (2009) 3. Catani, M., Ffytche, D. H.: The Rises and Falls of Disconnection Syndromes. J. Brain. 128, 2224--2239 (2005) 4. Catani, M., Ffytche, D. H.: Graph Theoretical Analysis of Magnetoencephalographic Functional Connectivity in Alzheimer’s Disease. J. Brain. 132, 213--224 (2009) 5. Deuschl, G. et al.: Deep-Brain Stimulation for Parkinson's Disease. J. Neurology. 249, 36--39 (2002) 6. Tononi,G., Edelman, G. M., Sporns, O.: Complexity and Coherency: Integrating Information in the Brain. J. Trends in Cognitive Science. 2, 474--484 (1998) 7. Strogatz, S. H.: Exploring complex network. J. Nature. 410, 268--276 (2001) 2011/6/1 ICCCI 2010 19
- 20. Reference 8. Bullmore, E., Sporns, O.: Complex Brain Networks: Graph Theoretical Analysis of Structural and Functional Systems. J. Nat. Rev. Neurosci. 10, 186--198 (2009) 9. Sporns, O., Chialvo, D. R., Kaiser, M., Hilgetag, C. C.: Organization, Development and Function of Complex Brain Networks. J. Trends in Cognitive Science. 8, 418--425 (2004) 10. Mikail Rubinov, Olaf Sporns, “Complex network measures of brain connectivity: uses and interpretations”, NeuroImage (2009) 11. NIH Launches the Human Connectome Project to Unravel the Brain Connections, http://www.nih.gov/news/health/jul2009/ninds-15.htm 12. Human Connectome Project, http://www.humanconnectomeproject.org/ 13. Sporns, O., Tononi, G., Kotter, R.: The Human Connectome: A Structural Description of the Human Brain. J. PLoS Comput. Biol. 1(4), e42 (2005) 14. Edelman, G. M.: Wider than the Sky: The Phenomenal Gift of Consciousness. Yale University Press (2004) 2011/6/1 ICCCI 2010 20
- 21. Reference 15. Thalamocortical Radiations, http://en.wikipedia.org/wiki/Thalamocortical_radiations 16. Basal Ganglia, http://en.wikipedia.org/wiki/Basal_ganglia 17. Neurotransmitter, http://en.wikipedia.org/wiki/Neurotransmitter 18. IBM Unveils a New Brain Simulator, http://spectrum.ieee.org/computing/hardware/ibm-unveils-a-new-brain- simulator 19. Blue Brain Project, http://bluebrain.epfl.ch/ 20. Markram, H.: The Blue Brain Project. J. Nat. Rev. Neurosci. 7, 153--160 (2006) 21. King, J. G. et al.: A Component-based Extension Framework for Large-scale Parallel Simulations in NEURON. J. Frontiers in Neuroinformatics. 3, (2009) 2011/6/1 ICCCI 2010 21
- 22. Thanks for Your Attention! Q&A 2011/6/1 ICCCI 2010 22