Estimating Nonlinear Spatiotemporal Membrane Dynamics in Active Dendrites

Abstract

Recent advances in measurement technology enables us to obtain spatotemporal data from neural systems as imaging data. In this study, we propose a statistical method to estimate nonlinear spatiotemporal membrane dynamics of active dendrites. We formulate generalized state space model of active dendrite, based on multi-compartment model. Membrane dynamics and its underlying electrical properties are simultaneously estimated by using sequential Monte-Carlo method and EM algorithm. Using the proposed method, we show that nonlinear spatiotemporal dynamics in active dendritic can be extracted from partially observable data.