Literature DB >> 19118551

Experimental and theoretical characterization of the voltage distribution generated by deep brain stimulation.

Svjetlana Miocinovic1, Scott F Lempka, Gary S Russo, Christopher B Maks, Christopher R Butson, Ken E Sakaie, Jerrold L Vitek, Cameron C McIntyre.   

Abstract

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and current-controlled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.

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Year:  2008        PMID: 19118551      PMCID: PMC2645000          DOI: 10.1016/j.expneurol.2008.11.024

Source DB:  PubMed          Journal:  Exp Neurol        ISSN: 0014-4886            Impact factor:   5.330


  55 in total

1.  Chronaxie calculated from current-duration and voltage-duration data.

Authors:  J Holsheimer; E A Dijkstra; H Demeulemeester; B Nuttin
Journal:  J Neurosci Methods       Date:  2000-04-01       Impact factor: 2.390

2.  No tissue damage by chronic deep brain stimulation in Parkinson's disease.

Authors:  C Haberler; F Alesch; P R Mazal; P Pilz; K Jellinger; M M Pinter; J A Hainfellner; H Budka
Journal:  Ann Neurol       Date:  2000-09       Impact factor: 10.422

3.  Deep brain stimulation for Parkinson's disease.

Authors:  Alim-Louis Benabid; Günther Deuschl; Anthony E Lang; Kelly E Lyons; Ali R Rezai
Journal:  Mov Disord       Date:  2006-06       Impact factor: 10.338

4.  Matching geometry and stimulation parameters of electrodes for deep brain stimulation experiments--numerical considerations.

Authors:  Ulrike Gimsa; Ute Schreiber; Beate Habel; Jürgen Flehr; Ursula van Rienen; Jan Gimsa
Journal:  J Neurosci Methods       Date:  2005-08-10       Impact factor: 2.390

5.  Chronic subthalamic high-frequency deep brain stimulation in Parkinson's disease--a histopathological study.

Authors:  M S Nielsen; C R Bjarkam; J C Sørensen; M Bojsen-Møller; N Aa Sunde; K Østergaard
Journal:  Eur J Neurol       Date:  2007-02       Impact factor: 6.089

Review 6.  Mechanisms and targets of deep brain stimulation in movement disorders.

Authors:  Matthew D Johnson; Svjetlana Miocinovic; Cameron C McIntyre; Jerrold L Vitek
Journal:  Neurotherapeutics       Date:  2008-04       Impact factor: 7.620

Review 7.  Characteristics of the metal-tissue interface of stimulation electrodes.

Authors:  A M Dymond
Journal:  IEEE Trans Biomed Eng       Date:  1976-07       Impact factor: 4.538

Review 8.  Historical evolution of circuit models for the electrode-electrolyte interface.

Authors:  L A Geddes
Journal:  Ann Biomed Eng       Date:  1997 Jan-Feb       Impact factor: 3.934

9.  The impact on Parkinson's disease of electrical parameter settings in STN stimulation.

Authors:  E Moro; R J A Esselink; J Xie; M Hommel; A L Benabid; P Pollak
Journal:  Neurology       Date:  2002-09-10       Impact factor: 9.910

10.  Differences among implanted pulse generator waveforms cause variations in the neural response to deep brain stimulation.

Authors:  Christopher R Butson; Cameron C McIntyre
Journal:  Clin Neurophysiol       Date:  2007-06-19       Impact factor: 3.708

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  63 in total

1.  Anatomical connectivity between subcortical structures.

Authors:  Kyle Taljan; Cameron McIntyre; Ken Sakaie
Journal:  Brain Connect       Date:  2011

2.  Explaining clinical effects of deep brain stimulation through simplified target-specific modeling of the volume of activated tissue.

Authors:  B Mädler; V A Coenen
Journal:  AJNR Am J Neuroradiol       Date:  2012-02-02       Impact factor: 3.825

3.  Probabilistic analysis of activation volumes generated during deep brain stimulation.

Authors:  Christopher R Butson; Scott E Cooper; Jaimie M Henderson; Barbara Wolgamuth; Cameron C McIntyre
Journal:  Neuroimage       Date:  2010-10-23       Impact factor: 6.556

4.  In vivo impedance spectroscopy of deep brain stimulation electrodes.

Authors:  Scott F Lempka; Svjetlana Miocinovic; Matthew D Johnson; Jerrold L Vitek; Cameron C McIntyre
Journal:  J Neural Eng       Date:  2009-06-03       Impact factor: 5.379

5.  Measurement of evoked potentials during thalamic deep brain stimulation.

Authors:  Alexander R Kent; Brandon D Swan; David T Brocker; Dennis A Turner; Robert E Gross; Warren M Grill
Journal:  Brain Stimul       Date:  2014-10-05       Impact factor: 8.955

6.  Electrophysiology equipment for reliable study of kHz electrical stimulation.

Authors:  Mohamad FallahRad; Adantchede Louis Zannou; Niranjan Khadka; Steven A Prescott; Stéphanie Ratté; Tianhe Zhang; Rosana Esteller; Brad Hershey; Marom Bikson
Journal:  J Physiol       Date:  2019-03-18       Impact factor: 5.182

7.  Particle swarm optimization for programming deep brain stimulation arrays.

Authors:  Edgar Peña; Simeng Zhang; Steve Deyo; YiZi Xiao; Matthew D Johnson
Journal:  J Neural Eng       Date:  2017-01-09       Impact factor: 5.379

Review 8.  Computational modeling of deep brain stimulation.

Authors:  Cameron C McIntyre; Thomas J Foutz
Journal:  Handb Clin Neurol       Date:  2013

9.  High efficiency electrodes for deep brain stimulation.

Authors:  Warren M Grill; Xuefeng F Wei
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

10.  Analysis of high-perimeter planar electrodes for efficient neural stimulation.

Authors:  Xuefeng F Wei; Warren M Grill
Journal:  Front Neuroeng       Date:  2009-11-10
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