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Scaling Power Laws in the Restoration of Perception with Increasing Stimulus in Deficitary Natural Neural Network

  • Isabel Gonzalo-Fonrodona
  • Miguel A. Porras
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5601)

Abstract

Measurements of the restoration of visual and tactile perceptions with increasing stimulus, carried out by Justo Gonzalo (1910-1986) in patients with lesions in the cerebral cortex, constitute exceptional examples of quantification of perception. From an analysis of the data for different types of stimulus, we find that, at high enough intensity of stimulus, perception follows scaling power laws with dominance of quarter exponents, which are similar to the scaling laws found in the improvement of perception by multisensory facilitation, reflecting general mechanisms in the respective neural networks of the cortex. The analysis supports the idea that the integrative cerebral process, initiated in the projection path, reaches regions of the cortex of less specificity.

Keywords

Middle Line High Stimulus Biological Neural Network Functional Gradient Multisensory Interaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Gonzalo, J.: Investigaciones sobre la nueva dinámica cerebral. La actividad cerebral en función de las condiciones dinámicas de la excitabilidad nerviosa. Publicaciones del Consejo Superior de Investigaciones Científicas, Inst. S. Ramón y Cajal, Madrid, vol. I (1945), II (1950) (available in: Instituto Cajal, CSIC, Madrid)Google Scholar
  2. 2.
    Gonzalo, J.: La cerebración sensorial y el desarrollo en espiral. Cruzamientos, magnificación, morfogénesis. Trab. Inst. Cajal Invest. Biol. 43, 209–260 (1951)Google Scholar
  3. 3.
    Gonzalo, J.: Las funciones cerebrales humanas según nuevos datos y bases fisiológicas: Una introducción a los estudios de Dinámica Cerebral. Trab. Inst. Cajal Invest. Biol. 44, 95–157 (1952)Google Scholar
  4. 4.
    Gonzalo, I., Gonzalo, A.: Functional gradients in cerebral dynamics: The J. Gonzalo theories of the sensorial cortex. In: Moreno-Díaz, R., Mira, J. (eds.) Brain Processes, Theories and Models. An Int. Conf. in honor of W.S. McCulloch 25 years after his death, pp. 78–87. MIT Press, Massachusetts (1996)Google Scholar
  5. 5.
    Gonzalo-Fonrodona, I.: Functional grsdients through the cortex, multisensory integration and scaling laws in brain dynamics. Neurocomputing 72, 831–838 (2009)CrossRefGoogle Scholar
  6. 6.
    Gonzalo-Fonrodona, I.: Inverted or tilted perception disorder. Revista de Neurología 44, 157–165 (2007)Google Scholar
  7. 7.
    Martuzzi, R., Murray, M.M., Michel, C.M., et al.: Multisensory interactions within human primary cortices revealed by BOLD dynamics. Cereb. Cortex 17, 1672–1679 (2007)CrossRefGoogle Scholar
  8. 8.
    Wallace, M.T., Ramachandran, R., Stein, B.E.: A revised view of sensory cortical parcellation. Proc. Natl. Acad. Sci. USA 101, 2167–2172 (2004)CrossRefGoogle Scholar
  9. 9.
    Gonzalo, I.: Allometry in the J. Gonzalo’s model of the sensorial cortex. In: McCune, W. (ed.) CADE 1997. LNCS, vol. 1249, pp. 169–177. Springer, Heidelberg (1997)Google Scholar
  10. 10.
    Gonzalo, I.: Spatial Inversion and Facilitation in the J. Gonzalo’s Research of the Sensorial Cortex. Integrative Aspects. In: Mira, J. (ed.) IWANN 1999. LNCS, vol. 1606, pp. 94–103. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  11. 11.
    Gonzalo, I., Porras, M.A.: Time-dispersive effects in the J. Gonzalo’s research on cerebral dynamics. In: Mira, J., Prieto, A.G. (eds.) IWANN 2001. LNCS, vol. 2084, pp. 150–157. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  12. 12.
    Gonzalo, I., Porras, M.A.: Intersensorial summation as a nonlinear contribution to cerebral excitation. In: Mira, J., Álvarez, J.R. (eds.) IWANN 2003. LNCS, vol. 2686, pp. 94–101. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  13. 13.
    Arias, M., Gonzalo, I.: La obra neurocientífica de Justo Gonzalo (1910-1986): El síndrome central y la metamorfopsia invertida. Neurología 19, 429–433 (2004)Google Scholar
  14. 14.
    Gonzalo-Fonrodona, I., Porras, M.A.: Physiological Laws of Sensory Visual System in Relation to Scaling Power Laws in Biological Neural Networks. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2007. LNCS, vol. 4527, pp. 96–102. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  15. 15.
    Delgado, A.E.: Modelos Neurocibernéticos de Dinámica Cerebral. Ph.D.Thesis. E.T.S. de Ingenieros de Telecomunicación, Univ. Politécnica, Madrid (1978)Google Scholar
  16. 16.
    Mira, J., Delgado, A.E., Moreno-Díaz, R.: The fuzzy paradigm for knowledge representation in cerebral dynamics. Fuzzy Sets and Systems 23, 315–330 (1987)CrossRefGoogle Scholar
  17. 17.
    Mira, J., Manjarrés, A., Ros, S., Delgado, A.E., Álvarez, J.R.: Cooperative Organization of Connectivity Patterns and Receptive Fields in the Visual Pathway: Application to Adaptive Thresholdig. In: Sandoval, F., Mira, J. (eds.) IWANN 1995. LNCS, vol. 930, pp. 15–23. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  18. 18.
    Stevens, S.S.: On the psychophysical law. Psychol. Rev. 64, 153–181 (1957)CrossRefGoogle Scholar
  19. 19.
    Arthurs, O.J., Stephenson, C.M.E., Rice, K., Lupson, V.C., Spiegelhalter, D.J., Boniface, S.J., Bullmore, E.T.: Dopaminergic effects on electrophysiological and functional MRI measures of human cortical stimulus-response power laws. NeuroImage 21, 540–546 (2004)CrossRefGoogle Scholar
  20. 20.
    Nieder, A., Miller, E.K.: Coding of cognitive magnitude. Compressed scaling of numerical information in the primate prefrontal cortex. Neuron 37, 149–157 (2003)CrossRefGoogle Scholar
  21. 21.
    West, G.B., Brown, J.H.: A general model for the origin of allometric scalling laws in biology. Science 276, 122–126 (1997)CrossRefGoogle Scholar
  22. 22.
    Banavar, J.R., Maritan, A., Rinaldo, A.: Size and form in efficient transportation networks. Nature 399, 130–132 (1999)CrossRefGoogle Scholar
  23. 23.
    West, G.B., Brown, J.H.: Life’s Universal Scaling Laws. Phys. Today, 36–42 (September 2004)Google Scholar
  24. 24.
    West, G.B., Brown, J.H.: The origin of allometric scaling laws in biology from genomes to ecosystems: towards a quantitative unifying theory of biological structure and organization. J. Exper. Biol. 208, 1575–1592 (2005)CrossRefGoogle Scholar
  25. 25.
    Anderson, R.B.: The power law as an emergent property. Mem. Cogn. 29, 1061–1068 (2001)CrossRefGoogle Scholar
  26. 26.
    Gisiger, T.: Scale invariance in biology: coincidence or footprint of a universal mechanisms? Biol. Rev. 76, 161–209 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Isabel Gonzalo-Fonrodona
    • 1
  • Miguel A. Porras
    • 2
  1. 1.Departamento de Óptica, Facultad de Ciencias FísicasUniversidad Complutense de MadridMadridSpain
  2. 2.Departamento de Física Aplicada, ETSIMUniversidad Politécnica de MadridMadridSpain

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