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In vivoimpedancespectroscopy of deepbrain stimulationelectrodes Scott F. LempkaSvjetlana MiocinovicMatthew D. Johnson2009 год

In vivoimpedance spectroscopy of deep brain stimulation electrodes
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Аннотация: Deep brain stimulation (DBS) represents a powerful clinical technology, but a systematic characterization of the electrical interactions between the electrode and the brain is lacking. The goal of this study was to examine the in vivo changes in the DBS electrode impedance that occur after implantation and during clinically relevant stimulation. Clinical DBS devices typically apply high-frequency voltage-controlled stimulation, and as a result, the injected current is directly regulated by the impedance of the electrode–tissue interface. We monitored the impedance of scaled-down clinical DBS electrodes implanted in the thalamus and subthalamic nucleus of a rhesus macaque using electrode impedance spectroscopy (EIS) measurements ranging from 0.5 Hz to 10 kHz. To further characterize our measurements, equivalent circuit models of the electrode–tissue interface were used to quantify the role of various interface components in producing the observed electrode impedance. Following implantation, the DBS electrode impedance increased and a semicircular arc was observed in the high-frequency range of the EIS measurements, commonly referred to as the tissue component of the impedance. Clinically relevant stimulation produced a rapid decrease in electrode impedance with extensive changes in the tissue component. These post-operative and stimulation-induced changes in impedance could play an important role in the observed functional effects of voltage-controlled DBS and should be considered during clinical stimulation parameter selection and chronic animal research studies.
Год издания: 2009
Авторы: Scott F. Lempka, Svjetlana Miocinovic, Matthew D. Johnson, Jerrold L. Vitek, Cameron C. McIntyre
Издательство: IOP Publishing
Источник: Journal of Neural Engineering
Ключевые слова: Neuroscience and Neural Engineering, Neurological disorders and treatments, EEG and Brain-Computer Interfaces
Другие ссылки: Journal of Neural Engineering (HTML)
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