Towards a Neural-Networks Based Therapy for Limbs Spasticity

  • Alexandre Moreira Nascimento
  • D. Andina
  • Francisco Javier Ropero Peláez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4527)

Abstract

This article presents a neural network model for the simulation of the neurological mechanism that produces limbs hiper-rigidity (spasticity). In this model, we take into account intrinsic plasticity, which is the property of biological neurons that consists in the shifting of the action potential threshold according to experience. In accordance to the computational model, a therapeutic technique for diminishing limbs spasticity is proposed and discussed.

Keywords

Neural networks hypertonia spasticity intrinsic plasticity muscle treatment 

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References

  1. 1.
    Burke, D.: Critical examination of the case for and against fusimotor involvement in disorders of muscle tone. Adv. Neurol. 39, 133–155 (1983)Google Scholar
  2. 2.
    Pierrot-Deseilligny, E., Mazieres, L.: Spinal mechanism underlying spasticity. In: Delwaide, P.J., Young, R.R. (eds.) Clinical neurophysiology in spasticity, Elsevier, Amsterdam (1985)Google Scholar
  3. 3.
    N., D.: Homeostatic plasticity in the cns: synaptic and intrinsic forms. Journal of Physiology Paris 97, 391 (2003)CrossRefGoogle Scholar
  4. 4.
    Rutherford, L.C., Desai, N.S., Turrigiano, G.: Plasticity in the intrinsic excitability of cortical pyramidal neurons. Nature Neuroscience 2(6), 515–520 (1999)CrossRefGoogle Scholar
  5. 5.
    Turrigiano, G.G., Nelson, S.B.: Homeostatic plasticity in the developing nervous system. Nature Reviews in Neuroscience 5, 97–106 (2004)CrossRefGoogle Scholar
  6. 6.
    Chub, N., O’Donovan, M.J.: Blockade and recovery of spontaneous rhythmic activity after application of neurotransmitter antagonists to spinal networks of the chick embryo. Journal of Neuroscience 18, 294–306 (1998)Google Scholar
  7. 7.
    Obrietan, K., Van Den Pol, A.N., Belousov, A.: Glutamate hyperexcitability and seizure-like activity throughout the brain and spinal cord upon relief from chronic glutamate receptor blockade in culture. Neuroscience 74, 653–674 (1996)CrossRefGoogle Scholar
  8. 8.
    Connors, B.W., Bear, M.F.: Paradise, m.a. In: Neuroscience: Exploring the Brain, Lippincott, Williams and Wilkins, Philadelphia (2001)Google Scholar
  9. 9.
    Pelaéz, J.R., Piqueira, J.R.C.: Biological clues for up-to-date artificial neurons. In: Andina, D., Phan, D.T. (eds.) Computational Inteligence: for Engineering and Manufacturing, 1st edn., pp. 131–146. Springer, Berlin (2006)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Alexandre Moreira Nascimento
    • 1
  • D. Andina
    • 2
  • Francisco Javier Ropero Peláez
    • 1
  1. 1.Politechnique School of the University of Säo Paulo 
  2. 2.Group for Automation and Soft Computing, Technical Univ. of Madrid (GASC/UPM) 

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