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Modeling cortical networks

  • Neuroscience
  • Conference paper
  • First Online:
From Natural to Artificial Neural Computation (IWANN 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 930))

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Abstract

A simple model of a microcolumn is developed. Each neuron is taken as a particular oscillator that is strongly connected to several others in a specific network. To model neuronal and network activities non-linear dynamical systems are used. Through stability and bifurcation analysis the dependence of neuronal activities with parameters is studied. A neurophysiological-based heterogeneity among different oscillators could be guarantee selecting different values for parameters of each cell. It is shown that with this simple approach more complex and varied temporal patterns are obtained.

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References

  1. Silva L, Amitai Y and Connors B. 1991. Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science 251:432–435.

    PubMed  Google Scholar 

  2. Kandel ER, Schwartz JH and Jessel TM. 1991. Principles of Neural Sciences. Elsevier Science Publishing Co. Inc. 3th Ed.

    Google Scholar 

  3. Hodgkin AL and Huxley AF. 1952. A quantitative description of membrane current and its application to conduction and excitation in nerve. J.Physiol.Lond 117:500–544.

    PubMed  Google Scholar 

  4. Lambert JD. 1986. A stable sequence of step-lengths for Euler's rule applied to stiff systems of differential equations. Comp. Math with Appls 1213 5/6: 1141–1151.

    Google Scholar 

  5. Guckenheimer J and Holmes PJ. 1983. Nonlinear oscillations, dynamical systems and bifurcations of vector fields. Springer-Verlag: New York, Heidelberg, Berlin.

    Google Scholar 

  6. Chagnac-Amitai Y and Connors BW. 1989. Synchronized excitation and inhibition driven by intrinsically bursting neurons in neocortex. J.Neurophysiol. 62:1149–1162.

    PubMed  Google Scholar 

  7. Terman D. 1992. The transition from bursting to continuous spiking in excitable membrane models. J.Nonlin.Sci. 2:135–182.

    Google Scholar 

  8. Alexander JC and Cai DY. 1991. On the dynamics of bursting systems. J.Math. Biol. 29:405–423.

    PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. Complex Systems Research Group. Departament de Fisica i Enginyeria Nuclear, Universität Politécnica de Catalunya, Sor Eulàlia d'Anzizu s/n. Campus Nord, Mòdul, B4 08034, Barcelona, Spain

    Liset Menéndez de la Prida

Authors
  1. Liset Menéndez de la Prida
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Editor information

José Mira Francisco Sandoval

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© 1995 Springer-Verlag Berlin Heidelberg

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de la Prida, L.M. (1995). Modeling cortical networks. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_150

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  • DOI: https://doi.org/10.1007/3-540-59497-3_150

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59497-0

  • Online ISBN: 978-3-540-49288-7

  • eBook Packages: Springer Book Archive

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