Estimation of neuron parameters from imperfect observations.

ABSTRACT: The estimation of parameters controlling the electrical properties of biological neurons is essential to determine their complement of ion channels and to understand the function of biological circuits. By synchronizing conductance models to time series observations of the membrane voltage, one may construct models capable of predicting neuronal dynamics. However, identifying the actual set of parameters of biological ion channels remains a formidable theoretical challenge. Here, we present a regularization method that improves convergence towards this optimal solution when data are noisy and the model is unknown. Our method relies on the existence of an offset in parameter space arising from the interplay between model nonlinearity and experimental error. By tuning this offset, we induce

SUBMITTER: Taylor JD 

PROVIDER: S-EPMC7386621 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature