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Cui J, Mivalt F, Sladky V, Kim J, Richner TJ, Lundstrom BN, Van Gompel JJ, Wang HL, Miller KJ, Gregg N, Wu LJ, Denison T, Winter B, Brinkmann BH, Kremen V, Worrell GA. Acute to long-term characteristics of impedance recordings during neurostimulation in humans. J Neural Eng 2024; 21:10.1088/1741-2552/ad3416. [PMID: 38484397 PMCID: PMC11044203 DOI: 10.1088/1741-2552/ad3416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 03/14/2024] [Indexed: 03/26/2024]
Abstract
Objective.This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus, and posterior hippocampus over an extended period.Approach.Impedance was periodically sampled every 5-15 min over several months in five subjects with drug-resistant epilepsy using an investigational neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24 h impedance cycle throughout the multi-month recording.Main results.Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 d to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24 h impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures.Significance.Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.
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Affiliation(s)
- Jie Cui
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
- Mayo College of Medicine and Science, Mayo Clinic, Rochester, Minnesota, USA
| | - Filip Mivalt
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
| | - Vladimir Sladky
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
- Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Jiwon Kim
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | | | - Hai-long Wang
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Kai J. Miller
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Nicholas Gregg
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Long Jun Wu
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Timothy Denison
- Department of Engineering Science, University of Oxford; MRC Brain Network Dynamics Unit, University of Oxford, OX3 7DQ UK
| | - Bailey Winter
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Mayo College of Medicine and Science, Mayo Clinic, Rochester, Minnesota, USA
| | - Benjamin H. Brinkmann
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
| | - Vaclav Kremen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University, Prague, Czech Republic
| | - Gregory A. Worrell
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
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Cui J, Mivalt F, Sladky V, Kim J, Richner TJ, Lundstrom BN, Van Gompel JJ, Wang HL, Miller KJ, Gregg N, Wu LJ, Denison T, Winter B, Brinkmann BH, Kremen V, Worrell GA. Acute to long-term characteristics of impedance recordings during neurostimulation in humans. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.23.24301672. [PMID: 38343858 PMCID: PMC10854350 DOI: 10.1101/2024.01.23.24301672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
Objective This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus (AMG-HPC), and posterior hippocampus (post-HPC) over an extended period. Approach Impedance was periodically sampled every 5-15 minutes over several months in five subjects with drug-resistant epilepsy using an experimental neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24-hour impedance cycle throughout the multi-month recording. Main results Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 days to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24-hour impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures. Significance Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.
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Affiliation(s)
- Jie Cui
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
- Mayo College of Medicine and Science, Mayo Clinic, Rochester, Minnesota, USA
| | - Filip Mivalt
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
| | - Vladimir Sladky
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
- Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Jiwon Kim
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | | | - Hai-long Wang
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Kai J. Miller
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Nicholas Gregg
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Long Jun Wu
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Timothy Denison
- Department of Engineering Science, University of Oxford; MRC Brain Network Dynamics Unit, University of Oxford, OX3 7DQ UK
| | - Bailey Winter
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Mayo College of Medicine and Science, Mayo Clinic, Rochester, Minnesota, USA
| | - Benjamin H. Brinkmann
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
| | - Vaclav Kremen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University, Prague, Czech Republic
| | - Gregory A. Worrell
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
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