Abstract
Starting from single, spiking neurons, we derive a system of differential equations for the description of the dynamics of pools of extensively many neurons. The derivation is exact and axonal delays and memory effects such as refractory behavior are taken into account. Simulations show a good quantitative agreement with microscopically modeled pools both in a quasistationary and in a non-stationary dynamical regime including fast transients and oscillations.
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© 1997 Springer-Verlag Berlin Heidelberg
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Eggert, J., van Hemmen, J.L. (1997). Derivation of pool dynamics from microscopic neuronal models. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020141
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DOI: https://doi.org/10.1007/BFb0020141
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