Computational Modeling of the Effects of Deep Brain Stimulation

Cameron McIntyre
Biomedical Engineering, Johns Hopkins University

(February 3, 2003 4:30 PM - 5:30 PM)

Computational Modeling of the Effects of Deep Brain Stimulation

Abstract

Deep brain stimulation (DBS) represents a dramatically effective treatment for clinically intractable movement disorders such as essential tremor and Parkinson's disease; however the underlying mechanisms of its therapeutic action are unknown. The goal of my research program is to develop a systems level understanding of the effects DBS using detailed computer modeling techniques. My work couples the results of functional imaging and basic neurophysiology to computer models of extracellular electric fields and their effects on the nervous system. These models consist of three basic stages. The first step is the development of 3D finite element models of the electric field generated by DBS electrodes where the electrical properties of the tissue are based on diffusion tensor MRI. The second step is coupling the electric field to 3D reconstructions of neurons surrounding the electrode where the ion channel biophysics of the neuron models are based on experimental data. The outcome of steps 1 & 2 are predictions on the volume of tissue surrounding the electrode that are affected by the stimulation. The final step is then to apply those stimulation effects to large scale neuronal network models of the thalamo-cortical-basal ganglia system that DBS modulates thereby providing experimentally testable hypotheses on the effects of stimulation in the different nuclei of the network. In addition, the results of this work can be coupled to PET/fMRI to provide a contiunum from the single cell to the network to the behavior.