Brain Network - Thalamocortical Motif

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Speaker: Jimmy Lu
Topics: Brain Network - Thalamocortical Motif
Date: 2010.03.20

WECO Lab, CSIE, FJU

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Brain Network - Thalamocortical Motif

  1. 1. Brain Networks Thalamocortical Motif Speaker : Jimmy Lu Advisor : Hsing Mei Web Computing Laboratory(WECO Lab) Computer Science and Information Engineering Department Fu Jen Catholic University
  2. 2. Outline  Report proposal  Background and review  Small-world network  Scale-free network  Reentrant mapping  Links, issues, and opinions  Future work WECO Lab, CSIE dept., FJU 2010/3/19 2 http://www.weco.net
  3. 3. Report Proposal  Thalamocortical motif  Polysynatic loop structure  Diffuse ascending projection  Cognitive science  Social networks  Collective intelligence  Web intelligence WECO Lab, CSIE dept., FJU 2010/3/19 3 http://www.weco.net
  4. 4. Background and Review (1/3)  Thalamus  process sensory information as well as relaying it  As a gateway, a switch, or a relay  Reticular nucleus, intralaminar nuclei WECO Lab, CSIE dept., FJU 2010/3/19 4 http://www.weco.net
  5. 5. Background and Review (2/3)  Cerebral cortex  Brain map  Plays a key role in memory, attention, perceptual awareness, thought, language, and consciousness  Small-world, Scale-free WECO Lab, CSIE dept., FJU 2010/3/19 5 http://www.weco.net
  6. 6. Background and Review (3/3) Thalamocortical radiations  Reentrant mapping  Sensory information go through the spine cord to the thalamus, and then relay it to the cortical areas  Dynamic core WECO Lab, CSIE dept., FJU 2010/3/19 6 http://www.weco.net
  7. 7. Small-world network (1/7)  The intermediate region between regular and random WECO Lab, CSIE dept., FJU 2010/3/19 7 http://www.weco.net
  8. 8. Small-world network (2/7)  Clustering coefficient and path length WECO Lab, CSIE dept., FJU 2010/3/19 8 http://www.weco.net
  9. 9. Small-world network (3/7)  Three examples  Film actors  Power grid  C. elegans WECO Lab, CSIE dept., FJU 2010/3/19 9 http://www.weco.net
  10. 10. Small-world network (4/7)  The time to global infection is nearly as short as for a random graph WECO Lab, CSIE dept., FJU 2010/3/19 10 http://www.weco.net
  11. 11. Small-world network (5/7)  Small-world in the brain: micro view WECO Lab, CSIE dept., FJU 2010/3/19 11 http://www.weco.net
  12. 12. Small-world network (6/7)  Small-world in the brain: macro view WECO Lab, CSIE dept., FJU 2010/3/19 12 http://www.weco.net
  13. 13. Small-world network (7/7)  Small-world in the brain  Truncated power law  Economical(close, cost, conservation)  Global efficiency, short cut  High degree nodes are less often highly clustered  Isomorphism, patterns of connectivity  Robust, less vulnerable, balance WECO Lab, CSIE dept., FJU 2010/3/19 13 http://www.weco.net
  14. 14. Scale-free network (1/3)  The problem of ER and WS model  The probability with which a new vertex connects to the existing vertices is not uniform  Most real world networks are open. The number of vertices may increase WECO Lab, CSIE dept., FJU 2010/3/19 14 http://www.weco.net
  15. 15. Scale-free network (2/3)  Two mechanisms  Networks expand continuously by the addition of new vertices  New vertices attach preferentially to sites that are already well connected  The development of large networks is governed by robust-organizing phenomena WECO Lab, CSIE dept., FJU 2010/3/19 15 http://www.weco.net
  16. 16. Scale-free network (3/3)  Power law distribution  Citation of scientific papers  Rich-get-richer WECO Lab, CSIE dept., FJU 2010/3/19 16 http://www.weco.net
  17. 17. Reentrant mapping (1/3)  Directions  Corticocortical  Thalamocortical  Corticothalamic  Mutual information WECO Lab, CSIE dept., FJU 2010/3/19 17 http://www.weco.net
  18. 18. Reentrant mapping (2/3)  Theory of Neuronal Group Selection WECO Lab, CSIE dept., FJU 2010/3/19 18 http://www.weco.net
  19. 19. Reentrant mapping (3/3)  Reentrant mapping and consciousness WECO Lab, CSIE dept., FJU 2010/3/19 19 http://www.weco.net
  20. 20. Links, issues, and opinions (1/4)  Undirected and Directed graph(I/O)?  Hubs/weighted graph ?  Does a vertex which connect to a hub increase the probability of being attached?  The region between small-world and scale-free? WECO Lab, CSIE dept., FJU 2010/3/19 20 http://www.weco.net
  21. 21. Links, issues, and opinions (2/4)  Three types of projections and structural, functional, and effective point of view  Micro/macro, local/global  Structural-functional relation  Reconfiguration, dynamics  Is the hypothesis of reentry right? WECO Lab, CSIE dept., FJU 2010/3/19 21 http://www.weco.net
  22. 22. Links, issues, and opinions (3/4)  What parameters can be mapped from brain to social networks? Small-world Degeneracy? WECO Lab, CSIE dept., FJU 2010/3/19 22 http://www.weco.net
  23. 23. Links, issues, and opinions (4/4)  What’s the stimulus of social network?  What stimulus force the structure of social networks change?  What characteristics should a brain simulator has?  Degeneracy, evolutionary, self-organize, etc… WECO Lab, CSIE dept., FJU 2010/3/19 23 http://www.weco.net
  24. 24. Reference  [1] Ed Bullmore, Olaf Sporns, “Complex brain networks: graph theoretical analysis of structural and functional systems”, Nature Reviews Neuroscience 10, 186-198 (March 2009)  [2] Duncan J. Watts, Steven H. Strogatz, “Collective dynamics of 'small- world' networks”, Nature 393, 440-442 (4 June 1998)  [3] Albert-László Barabási, Réka Albert, “Emergence of Scaling in Random Networks”, Science 15 October 1999: Vol. 286. no. 5439, pp. 509 – 512  [4] Gerald M. Edelman, “Wider than the Sky: The Phenomenal Gift of Consciousness”, Yale University Press (March 10, 2004) WECO Lab, CSIE dept., FJU 2010/3/19 24 http://www.weco.net

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