Journal
CLINICAL NEUROPHYSIOLOGY
Volume 129, Issue 4, Pages 731-742Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.clinph.2018.01.015
Keywords
Deep brain stimulation; Neuromodulation; Neurostimulation; Neural activation; Computational modeling; Parkinson's disease
Categories
Funding
- National Institutes of Health [NIH R01 NS085188, NIH R01 MH102238, F32 NS096839, T32 GM007250, TL1 TR000441, T32 EB004314]
- Louis Stokes Cleveland Veterans Affairs Medical Center
- United States Department of Education [GAANN P200A100112]
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Objective: To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS). Methods: We experimentally interrogated the Medtronic Activa PC DBS IPG and defined an equivalent circuit model that accurately captured the output of the IPG. We then compared the detailed circuit model of the clinical stimulus waveforms to simplified representations commonly used in computational models of DBS. We quantified the errors associated with these simplifications using theoretical activation thresholds of myelinated axons in response to DBS. Results: We found that the detailed IPG model generated substantial differences in activation thresholds compared to simplified models. These differences were largest for bipolar stimulation with long pulse widths. Average errors were similar to 3 to 24% for voltage-controlled stimulation and similar to 2 to 11% for current-controlled stimulation. Conclusions: Our results demonstrate the importance of including basic circuit elements (e.g. blocking capacitors, lead wire resistance, electrode capacitance) in model analysis of DBS. Significance: Computational models of DBS are now commonly used in academic research, industrial technology development, and in the selection of clinical stimulation parameters. Incorporating a realistic representation of the IPG output is necessary to improve the accuracy and utility of these clinical and scientific tools. (C) 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
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