Skip to main content
SpringerLink
Log in

Attractors in Neurodynamical Systems

  • Conference paper
  • First Online:
Advances in Cognitive Neurodynamics (II)

  • 688 Accesses

Abstract

Analysis of the number, type and properties of attractors in complex neurodynamical systems is quite difficult. Fuzzy Symbolic Dynamics (FSD) creates visualization of trajectories that are easier to interpret than recurrence plots, showing basins of attractors. The variance of the trajectory within the attraction basin plotted against the variance of the synaptic noise provides some information about sizes and shapes of their basins. Semantic layer of dyslexia model implemented in the Emergent neural simulator is analyzed.

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

Access this chapter

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
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

Institutional subscriptions

References

  1. Marwan, N., Romano, M.C., Thiel, M., Kurths, J.: Recurrence plots for the analysis of complex systems. Phys. Rep. 438 (2007) 237–329.

    Article  Google Scholar 

  2. Shakhnarovish, G., Darrell, T., Indyk, P., eds.: Nearest-Neighbor Methods in Learning and Vision. Cambridge, MA: MIT Press (2005).

    Google Scholar 

  3. Hao, B., Zheng, W., eds.: Applied Symbolic Dynamics and Chaos. Singapore: World Scientific (1998).

    Google Scholar 

  4. Dobosz, K., Duch,W.: Understanding Neurodynamical Systems Via Fuzzy Symbolic Dynamics. Neural. Netw. 23 (2010) 487–496.

    Google Scholar 

  5. O’Reilly, R.C., Munakata, Y.: Computational Explorations in Cognitive Neuroscience. Cambridge, MA: MIT Press (2000).

    Google Scholar 

  6. Spivey, M.: The Continuity of Mind. New York, NY: Oxford University Press (2007).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  2. Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Torun, Poland

    Krzysztof Dobosz

Authors
  1. Włodzisław Duch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Krzysztof Dobosz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Włodzisław Duch .

Editor information

Editors and Affiliations

  1. , Institute for Cognitive Neurodynamics, East China University of Science and Tec, Meilong Road 130, Shanghai, 200237, China, People's Republic

    Rubin Wang

  2. Fudan University, Shanghai, China, People's Republic

    Fanji Gu

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media B.V.

About this paper

Cite this paper

Duch, W., Dobosz, K. (2011). Attractors in Neurodynamical Systems. In: Wang, R., Gu, F. (eds) Advances in Cognitive Neurodynamics (II). Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9695-1_25

Download citation

Publish with us

Policies and ethics

Search

Navigation