Reduced Order Model of a Neuron-Electrode Interface Coupled to a Hodgkin-Huxley Model

Abstract

– The electric properties of an interface between an electrode and a neuron are highly dependent on interface geometry and other parameters. Finite element models can be used to study these properties to a certain extent. Unfortunately, such models are computationally very expensive. By reducing these models, the computational time can be decreased. In this work, we use Krylov-subspace based model order reduction to reduce a simplified, linearized finite element model of an electrode-neuron interface. This facilitates the coupling to the Hodgkin-Huxley model at system level and reduces the computational time considerably. The accuracy of the original finite element model is preserved to a large extent.