Fitting local field potentials generating model of the basal ganglia to actual recorded signals

Abstract

A population level model of the basal ganglia has been shown to reliably reproduce the local field potential (LFP) activity recorded from subthalamic nucleus (ST ) during typical microelectrode recording sessions. The purpose of the present work is to investigate optimization methods that can be used to fit that model to actual recorded LFPs. For that, we utilize data derived from seven parkinsonian subjects prior to the permanent implantation of the deep brain stimulation (DBS) electrode. For the fitting, five optimization methods are used, combined with two methods for estimating the error between the actual recorded and the model predicted LFP signals in the frequency domain. The procedures are focused on re-generating the characteristic beta peak of the ST LFP. The results indicate that the model is able to reproduce the beta peak in various frequencies in the range of both low and high beta, while at the same time, the values of the critical parameters bringing the model in that area of behavior reveal the crucial role of the synaptic strengths in Parkinson's disease pathophysiology.