Model neurons: From Hodgkin-Huxley to hopfield

  • Abbott L
  • Kepler T
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Abstract

Anew technique is used to reduce the classic Hodgkin-Huxley model to a two-dimensional neuronal model which retains the essential features of the full description. The resulting equations are similar in spirit to those of the FitzHugh-Nagumo model, but they exhibit some essential differences which provide a more accurate representation of the full dynamics. By further simplifying the two-dimensional model we derive linear and nonlinear integrate and fire models and an interesting binary model with time-dependent threshold and hys- teresis. All the parameters of these simplified models are obtained through the reduction procedure from the underlying Hodgkin-Huxley equations. Thus, our methods establish di- rect connections between highly simplified models of neuronal dynamics and more realistic descriptions in terms of time- and voltage-dependent conductances.

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Abbott, L. F., & Kepler, T. B. (2008). Model neurons: From Hodgkin-Huxley to hopfield. In Statistical Mechanics of Neural Networks (pp. 5–18). Springer Berlin Heidelberg. https://doi.org/10.1007/3540532676_37

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