Optimal estimation of the parameters affecting the Parkinson´s disease state of thalamic cell model

Author

Luxia Zhang ; Jiang Wang ; Bin Deng ; Xile Wei ; Haitao Yu

Author_Institution

Sch. of Electr. & Autom. Eng., Tianjin Univ., Tianjin, China

fYear

2014

fDate

14-16 Oct. 2014

Firstpage

467

Lastpage

471

Abstract

The Parkinson´s disease (PD) state can be distinguished by relay reliability of thalamic cell (TC). Among numerous parameters of single-compartment conductance-based TC model, only two of them mainly modulate the relay reliability of TC. In order to explore the relationship between the two parameters and the firing relay, a parameter estimation method based on particle swarm optimization (PSO) algorithm is proposed and conducted on the TC model with two adjustable parameters. The simulation results estimated respectively from spiking features of PD state and normal state both achieve good performance.

Keywords

bioelectric potentials; cellular biophysics; diseases; neurophysiology; parameter estimation; particle swarm optimisation; physiological models; PD state spiking features; Parkinson disease state; firing relay reliability modulation; parameter estimation method; particle swarm optimization algorithm; single-compartment conductance-based thalamic cell model; Brain modeling; Estimation; Firing; Parkinson´s disease; Relays; Reliability; Trajectory; Parkinson´s disease (PD); parameter estimation; particle swarm optimization (PSO); thalamic cell (TC);

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2014 7th International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4799-5837-5

Type

conf

DOI

10.1109/BMEI.2014.7002820

Filename

7002820