Donghyeon Kim1, Jinmo Jeong2, Sangdo Jeong3, Sohee Kim4, Sung Chan Jun5, Euiheon Chung6. 1. School of Information and Communications, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju 500-712, South Korea. 2. School of Mechatronics, Gwangju Institute of Science and Technology, Gwangju, South Korea. 3. Department of Medical System Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea. 4. Department of Medical System Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea; School of Mechatronics, Gwangju Institute of Science and Technology, Gwangju, South Korea. 5. School of Information and Communications, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju 500-712, South Korea. Electronic address: scjun@gist.ac.kr. 6. Department of Medical System Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea; School of Mechatronics, Gwangju Institute of Science and Technology, Gwangju, South Korea. Electronic address: ogong50@gist.ac.kr.
Abstract
BACKGROUND: Although computational studies of electrical brain stimulation (EBS) have received attention as a cost-effective tool, few studies have validated the technique, particularly in invasive cortical stimulation. OBJECTIVE: In order to validate such studies, we used EBS to compare electric potential distributions generated by both numerical simulations and empirical measurements in three phantom head models (one-/three-layered spherical heads and MRI-based head). METHODS: We constructed spherical phantom heads that consisted of one or three layers, and an anatomical, MRI-based phantom that consisted of three layers and represented the brain or brain/skull/scalp in order to perform both numerical simulations using the finite element method (FEM) and experimental measurements. Two stimulation electrodes (cathode and anode) were implanted in the phantoms to inject regulated input voltage, and the electric potential distributions induced were measured at various points located either on the surface or deep within the phantoms. RESULTS: We observed that both the electric potential distributions from the numerical simulations and experiments behaved similarly and resulted in average relative differences of 5.4% (spherical phantom) and 10.3% (MRI-based phantom). CONCLUSIONS: This study demonstrated that numerical simulation is reasonably consistent with actual experimental measurements; thus, because of its cost-effectiveness, EBS computational studies may be an attractive approach for necessary intensive/extensive studies.
BACKGROUND: Although computational studies of electrical brain stimulation (EBS) have received attention as a cost-effective tool, few studies have validated the technique, particularly in invasive cortical stimulation. OBJECTIVE: In order to validate such studies, we used EBS to compare electric potential distributions generated by both numerical simulations and empirical measurements in three phantom head models (one-/three-layered spherical heads and MRI-based head). METHODS: We constructed spherical phantom heads that consisted of one or three layers, and an anatomical, MRI-based phantom that consisted of three layers and represented the brain or brain/skull/scalp in order to perform both numerical simulations using the finite element method (FEM) and experimental measurements. Two stimulation electrodes (cathode and anode) were implanted in the phantoms to inject regulated input voltage, and the electric potential distributions induced were measured at various points located either on the surface or deep within the phantoms. RESULTS: We observed that both the electric potential distributions from the numerical simulations and experiments behaved similarly and resulted in average relative differences of 5.4% (spherical phantom) and 10.3% (MRI-based phantom). CONCLUSIONS: This study demonstrated that numerical simulation is reasonably consistent with actual experimental measurements; thus, because of its cost-effectiveness, EBS computational studies may be an attractive approach for necessary intensive/extensive studies.
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