Literature DB >> 16810675

Basic algorithms for the programming of deep brain stimulation in Parkinson's disease.

Jens Volkmann1, Elena Moro, Rajesh Pahwa.   

Abstract

The clinical success of deep brain stimulation (DBS) for treating Parkinson's disease (PD) critically depends on the quality of postoperative neurological management. Movement disorder specialists becoming involved with this therapy need to acquire new skills to adapt optimally stimulation parameters and medication after implantation of a DBS system. At first glance, the infinite number of theoretically possible parameter combinations seems to make programming a complex and time-consuming art. This article outlines a stepwise and standardized approach, reducing the possible parameter settings in DBS to a few relevant combinations. The basic programming algorithms for thalamic, subthalamic, and pallidal stimulation in PD are explained and summarized in flowcharts.

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Year:  2006        PMID: 16810675     DOI: 10.1002/mds.20961

Source DB:  PubMed          Journal:  Mov Disord        ISSN: 0885-3185            Impact factor:   10.338


  99 in total

Review 1.  Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

Authors:  Elliot Greenwald; Matthew R Masters; Nitish V Thakor
Journal:  Med Biol Eng Comput       Date:  2016-01-11       Impact factor: 2.602

2.  Deep brain stimulation in Parkinson's disease.

Authors:  S J Groiss; L Wojtecki; M Südmeyer; A Schnitzler
Journal:  Ther Adv Neurol Disord       Date:  2009-11       Impact factor: 6.570

3.  Patient-specific analysis of the volume of tissue activated during deep brain stimulation.

Authors:  Christopher R Butson; Scott E Cooper; Jaimie M Henderson; Cameron C McIntyre
Journal:  Neuroimage       Date:  2006-11-17       Impact factor: 6.556

4.  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

5.  Current steering to control the volume of tissue activated during deep brain stimulation.

Authors:  Christopher R Butson; Cameron C McIntyre
Journal:  Brain Stimul       Date:  2008-01       Impact factor: 8.955

6.  Multi-objective particle swarm optimization for postoperative deep brain stimulation targeting of subthalamic nucleus pathways.

Authors:  Edgar Peña; Simeng Zhang; Remi Patriat; Joshua E Aman; Jerrold L Vitek; Noam Harel; Matthew D Johnson
Journal:  J Neural Eng       Date:  2018-09-13       Impact factor: 5.379

7.  A retrospective evaluation of automated optimization of deep brain stimulation parameters.

Authors:  Johannes Vorwerk; Andrea A Brock; Daria N Anderson; John D Rolston; Christopher R Butson
Journal:  J Neural Eng       Date:  2019-11-06       Impact factor: 5.379

8.  Latency of subthalamic nucleus deep brain stimulation-evoked cortical activity as a potential biomarker for postoperative motor side effects.

Authors:  Zachary T Irwin; Mohammad Z Awad; Christopher L Gonzalez; Arie Nakhmani; J Nicole Bentley; Thomas A Moore; Kenneth G Smithson; Barton L Guthrie; Harrison C Walker
Journal:  Clin Neurophysiol       Date:  2020-03-12       Impact factor: 3.708

9.  Anodic stimulation misunderstood: preferential activation of fiber orientations with anodic waveforms in deep brain stimulation.

Authors:  Daria Nesterovich Anderson; Gordon Duffley; Johannes Vorwerk; Alan D Dorval; Christopher R Butson
Journal:  J Neural Eng       Date:  2018-10-02       Impact factor: 5.379

10.  Interventional psychiatry: how should psychiatric educators incorporate neuromodulation into training?

Authors:  Nolan R Williams; Joseph J Taylor; Jonathan M Snipes; E Baron Short; Edward M Kantor; Mark S George
Journal:  Acad Psychiatry       Date:  2014-02-20
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