2023 - T1B - WS1 - Structural learning by the brain

Collection 2023 - T1B - WS1 - Structural learning by the brain

Organisateur(s) Galves, Antonio ; Löcherbach, Eva ; Pouzat, Christophe ; Vargas, Claudia D.
Date(s) 06/03/2023 - 10/03/2023
URL associée https://indico.math.cnrs.fr/event/7794/
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Why is it important to ground neuroscience in mathematics? What kind of mathematics are relevant in this scientific area where biology, perception; action and cognition are closely intermingled? What kind of relationships should be entertained with experimentalists and computationalists? In this lecture I will try to answer these questions through examples drawn from the analysis of the activity of large populations of neurons by mathematical methods from probability, statistics, and geometry.

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Bibliographie

  • A. L. Hodgkin, A. F. Huxley / A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, vol. 117 n°4, 1952. online
  • E. M. Izhikevich / Dynamical Systems in Neuroscience: The Geometry of Excitability And Bursting. 2007. online
  • John W. Evans / Nerve Axon Equations: 1 Linear Approximations. Indiana University Mathematics Journal, vol. 21 n°9, pp. 877–885, 1972. online

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