Effect of Electrode Geometry on Deep Brain Stimulation: Monopolar Point Source vs. Medtronic 3389 Lead
Deep brain stimulation (DBS) has emerged as an effective treatment for a variety of neurological and movement disorders; however, the fundamental mechanisms by which DBS works are not well understood. Computational models of DBS can be used to gain insights into these fundamental mechanisms and typically require two steps: computation of the electrical potentials generated by DBS and, subsequently, determination of the effects of the extracellular potentials on neurons. The objective of this study was to assess the validity of utilizing the point source approximation versus realistic finite element models (FEMs) in calculating the potentials generated by monopolar DBS. The distributions of extracellular potentials generated in a homogenous isotropic volume conductor were calculated using either the point source approximation or a realistic finite element model of the DBS lead. These extracellular potentials were then coupled to populations of simulated axons, and input-output curves of the number of stimulated axons as a function of stimulation intensity were calculated for different stimulus polarities, pulse durations, and axon orientations (parallel or perpendicular to the electrode). The differences in input-output curves calculated with the point source and FEM were small; FEM-predicted thresholds were on average 4.83% lower than point source predicted thresholds across all the conditions tested. The distance from and location relative to the electrode was the primary factor determining the error between point source and FEM geometries, and larger differences in predicted thresholds were evident in axons located immediately adjacent to the realistic electrode. Thus, under the conditions tested, the point source was a valid approximation for predicting population excitation in response to monopolar DBS. The results of this study reveal new insights that may aid in future computational modeling studies of DBS.
KeywordsElectrical Stimulation Finite Element Modeling Computational Modeling
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