Evaluation of high-perimeter electrode designs for deep brain stimulation

J Neural Eng. 2014 Aug;11(4):046026. doi: 10.1088/1741-2560/11/4/046026. Epub 2014 Jul 16.

Abstract

Objective: Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, complications including infections and mis-programing following surgical replacement of the battery-powered implantable pulse generator adversely impact the safety profile of this therapy. We sought to decrease power consumption and extend battery life by modifying the electrode geometry to increase stimulation efficiency. The specific goal of this study was to determine whether electrode contact perimeter or area had a greater effect on increasing stimulation efficiency.

Approach: Finite-element method (FEM) models of eight prototype electrode designs were used to calculate the electrode access resistance, and the FEM models were coupled with cable models of passing axons to quantify stimulation efficiency. We also measured in vitro the electrical properties of the prototype electrode designs and measured in vivo the stimulation efficiency following acute implantation in anesthetized cats.

Main results: Area had a greater effect than perimeter on altering the electrode access resistance; electrode (access or dynamic) resistance alone did not predict stimulation efficiency because efficiency was dependent on the shape of the potential distribution in the tissue; and, quantitative assessment of stimulation efficiency required consideration of the effects of the electrode-tissue interface impedance.

Significance: These results advance understanding of the features of electrode geometry that are important for designing the next generation of efficient DBS electrodes.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Animals
  • Axons / physiology
  • Cats
  • Computer Simulation
  • Deep Brain Stimulation / instrumentation*
  • Electrodes*
  • Electromyography
  • Equipment Design
  • Finite Element Analysis
  • Models, Neurological