Estimating Time-Varying Applied Current in the Hodgkin-Huxley Model

Applied Sciences

Andrea Arnold¹  Laura Staugler¹  Kayleigh Campbell¹ 

[1] Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA 01609, USA;

关键词: inverse problems;    time-varying parameter estimation;    ensemble kalman filter;    hodgkin-huxley;    neuron dynamics;   

DOI  :  10.3390/app10020550

来源: DOAJ

【 摘 要 】

The classic Hodgkin-Huxley model is widely used for understanding the electrophysiological dynamics of a single neuron. While applying a low-amplitude constant current to the system results in a single voltage spike, it is possible to produce multiple voltage spikes by applying time-varying currents, which may not be experimentally measurable. The aim of this work is to estimate time-varying applied currents of different deterministic forms given noisy voltage data. In particular, we utilize an augmented ensemble Kalman filter with parameter tracking to estimate four different time-varying applied current parameters and associated Hodgkin-Huxley model states, along with uncertainty bounds in each case. We test the efficiency of the parameter tracking algorithm in this setting by analyzing the effects of changing the standard deviation of the parameter drift and the frequency of data available on the resulting time-varying applied current estimates and related uncertainty.

【 授权许可】

Unknown