Skip to main content
SpringerLink
Log in
Book cover

Bio-Inspired Self-Organizing Robotic Systems pp 195–212Cite as

Brain Like Temporal Processing

  • Chapter

Part of the book series: Studies in Computational Intelligence ((SCI,volume 355))

Abstract

This chapter presents a general purpose model of the brain, called Developmental Networks (DN). Rooted in the biological genomic equivalence principle, our model proposes a general-purpose cell-centered in-place learning scheme to handle all levels of brain development and operation, from the cell level all the way to the brain level. It clarifies five necessary “chunks” of the brain “puzzle”: development, architecture, area, space and time. Then, this chapter analyzes how such a model enables a developmental robot to deal with temporal contexts. It deals with temporal context of any length without a dedicated temporal component.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Albus, J.S.: Outline for a theory of intelligence. IEEE Trans. Systems, Man and Cybernetics 21(3), 473–509 (1991)

    Article  MathSciNet  Google Scholar 

  2. Albus, J.S.: A model of computation and representation in the brain. Information Science 180(9), 1519–1554 (2010)

    Article  Google Scholar 

  3. Callaway, E.M.: Feedforward, feedback and inhibitory connections in primate visual cortex. Neural Networks 17, 625–632 (2004)

    Article  MATH  Google Scholar 

  4. Elman, J.L., Bates, E.A., Johnson, M.H., Karmiloff-Smith, A., Parisi, D., Plunkett, K.: Rethinking Innateness: A connectionist perspective on development. MIT Press, Cambridge (1997)

    Google Scholar 

  5. Emami, A., Jelinek, F.: A neural syntactic language model. Machine Learning 60, 195–227 (2005)

    Article  Google Scholar 

  6. George, D., Hawkins, J.: Towards a mathematical theory of cortical micro-circuits. PLoS Computational Biology 5(10), 1–26 (2009)

    Article  MathSciNet  Google Scholar 

  7. Hecht-Nielsen, R.: Confabulation Theory. Springer, Berlin (2007)

    Google Scholar 

  8. Jelinek, F.: Self-organized language modeling for speech recognition. In: Waibel, A., Lee, K. (eds.) Readings in Speech Recognition, pp. 450–506. Morgan Kaufmann, San Mateo (1990)

    Google Scholar 

  9. Lee, T.S., Mumford, D.: Hierarchical bayesian inference in the visual cortex. J. Opt. Soc. Am. A 20(7), 1434–1448 (2003)

    Article  Google Scholar 

  10. Luciw, M., Weng, J.: Where What Network 3: Developmental top-down attention with multiple meaningful foregrounds. In: Proc. IEEE International Joint Conference on Neural Networks, Barcelona, Spain, July 18-23, pp. 4233–4240 (2010)

    Google Scholar 

  11. Luciw, M., Weng, J., Zeng, S.: Motor initiated expectation through top-down connections as abstract context in a physical world. In: IEEE International Conference on Development and Learning, August 9-12, Monterey, CA, pp. +1–6. (2008)

    Google Scholar 

  12. Miyan, K., Weng, J.: WWN-Text: Cortex-like language acquisition with What and Where. In: Proc. IEEE 9th International Conference on Development and Learning, Ann Arbor, August 18-21, pp. 280–285 (2010)

    Google Scholar 

  13. Piaget, J.: The Construction of Reality in the Child. Basic Books, New York (1954)

    Google Scholar 

  14. Purves, W.K., Sadava, D., Orians, G.H., Heller, H.C.: Life: The Science of Biology, 7th edn. Sinauer, Sunderland, MA (2004)

    Google Scholar 

  15. Solgi, M., Weng, J.: Developmental stereo: Emergence of disparity preference in models of visual cortex. IEEE Trans. Autonomous Mental Development 1(4), 238–252 (2009)

    Article  Google Scholar 

  16. Tenenbaum, J.B., Griffithsb, T.L., Kemp, C.: Theory-based bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences 10(7), 309–318 (2006)

    Article  Google Scholar 

  17. Weng, J.: Task muddiness, intelligence metrics, and the necessity of autonomous mental development. Minds and Machines 19(1), 93–115 (2009)

    Article  MathSciNet  Google Scholar 

  18. Weng, J.: A 5-chunk developmental brain-mind network model for multiple events in complex backgrounds. In: Proc. Int’l Joint Conf. Neural Networks, Barcelona, Spain, July 18-23, pp. 1–8 (2010)

    Google Scholar 

  19. Weng, J., Ahuja, N., Huang, T.S.: Learning recognition and segmentation of 3-D objects from 2-D images. In: Proc. IEEE 4th Int’l Conf. Computer Vision, pp. 121–128 (May 1993)

    Google Scholar 

  20. Weng, J., Ahuja, N., Huang, T.S.: Learning recognition and segmentation using the Cresceptron. International Journal of Computer Vision 25(2), 109–143 (1997)

    Article  Google Scholar 

  21. Weng, J., Luciw, M.: Dually optimal neuronal layers: Lobe component analysis. IEEE Trans. Autonomous Mental Development 1(1), 68–85 (2009)

    Article  Google Scholar 

  22. Weng, J., McClelland, J., Pentland, A., Sporns, O., Stockman, I., Sur, M., Thelen, E.: Autonomous mental development by robots and animals. Science 291(5504), 599–600 (2001)

    Article  Google Scholar 

  23. Weng, J., Zhang, Q., Chi, M., Xue, X.: Complex text processing by the temporal context machines. In: Proc. IEEE 8th International Conference on Development and Learning, Shanghai, China, June 4-7, pp. +1–8 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Michigan State University, East Lansing, MI, USA

    Juyang Weng

Authors
  1. Juyang Weng
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Stevens Institute of Technology, Castle Point on Hudson, 07030, Hoboken, NJ, USA

    Yan Meng

  2. Department of Computing, University of Surrey, GU2 7XH, Guildford, Surrey, UK

    Yaochu Jin

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Weng, J. (2011). Brain Like Temporal Processing. In: Meng, Y., Jin, Y. (eds) Bio-Inspired Self-Organizing Robotic Systems. Studies in Computational Intelligence, vol 355. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20760-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-20760-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20759-4

  • Online ISBN: 978-3-642-20760-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation