Literature DB >> 17850196

Computational analysis of deep brain stimulation.

Cameron C McIntyre1, Svjetlana Miocinovic, Christopher R Butson.   

Abstract

Chronic, high-frequency electrical stimulation of subcortical brain structures (deep brain stimulation [DBS]) is an effective clinical treatment for several medically refractory neurological disorders. However, the clinical successes of DBS are tempered by the limited understanding of the response of neurons to applied electric fields and scientific definition of the therapeutic mechanisms of DBS remains elusive. In addition, it is presently unclear which electrode designs and stimulation parameters are optimal for maximum therapeutic benefit and minimal side effects. Detailed computer modeling of DBS has recently emerged as a powerful technique to enhance our understanding of the effects of DBS and to create a virtual testing ground for new stimulation paradigms. This review summarizes the fundamentals of neurostimulation modeling and provides an overview of some of the scientific contributions of computer models to the field of DBS. We then provide a prospective view on the application of DBS-modeling tools to augment the clinical utility of DBS and to design the next generation of DBS technology.

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Year:  2007        PMID: 17850196     DOI: 10.1586/17434440.4.5.615

Source DB:  PubMed          Journal:  Expert Rev Med Devices        ISSN: 1743-4440            Impact factor:   3.166


  26 in total

1.  Asymptotic model of electrical stimulation of nerve fibers.

Authors:  Jonathan P Cranford; Brian J Kim; Wanda Krassowska Neu
Journal:  Med Biol Eng Comput       Date:  2012-02-21       Impact factor: 2.602

2.  Current steering to activate targeted neural pathways during deep brain stimulation of the subthalamic region.

Authors:  Ashutosh Chaturvedi; Thomas J Foutz; Cameron C McIntyre
Journal:  Brain Stimul       Date:  2011-06-02       Impact factor: 8.955

3.  Computational Modeling of Neurotransmitter Release Evoked by Electrical Stimulation: Nonlinear Approaches to Predicting Stimulation-Evoked Dopamine Release.

Authors:  James K Trevathan; Ali Yousefi; Hyung Ook Park; John J Bartoletta; Kip A Ludwig; Kendall H Lee; J Luis Lujan
Journal:  ACS Chem Neurosci       Date:  2017-02-06       Impact factor: 4.418

4.  Functional anatomy of subthalamic nucleus stimulation in Parkinson disease.

Authors:  Sarah A Eisenstein; Jonathan M Koller; Kathleen D Black; Meghan C Campbell; Heather M Lugar; Mwiza Ushe; Samer D Tabbal; Morvarid Karimi; Tamara Hershey; Joel S Perlmutter; Kevin J Black
Journal:  Ann Neurol       Date:  2014-07-02       Impact factor: 10.422

5.  Deep brain stimulation of terminating axons.

Authors:  Kelsey L Bower; Cameron C McIntyre
Journal:  Brain Stimul       Date:  2020-09-09       Impact factor: 8.955

6.  Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

Authors:  Reuben R Shamir; Trygve Dolber; Angela M Noecker; Benjamin L Walter; Cameron C McIntyre
Journal:  Brain Stimul       Date:  2015-06-15       Impact factor: 8.955

7.  Mapping the "Depression Switch" During Intraoperative Testing of Subcallosal Cingulate Deep Brain Stimulation.

Authors:  Ki Sueng Choi; Patricio Riva-Posse; Robert E Gross; Helen S Mayberg
Journal:  JAMA Neurol       Date:  2015-11       Impact factor: 18.302

Review 8.  Engineering the next generation of clinical deep brain stimulation technology.

Authors:  Cameron C McIntyre; Ashutosh Chaturvedi; Reuben R Shamir; Scott F Lempka
Journal:  Brain Stimul       Date:  2014-07-30       Impact factor: 8.955

9.  Artificial neural network based characterization of the volume of tissue activated during deep brain stimulation.

Authors:  Ashutosh Chaturvedi; J Luis Luján; Cameron C McIntyre
Journal:  J Neural Eng       Date:  2013-09-24       Impact factor: 5.379

10.  The clinical utility of methods to determine spatial extent and volume of tissue activated by deep brain stimulation.

Authors:  Robert E Gross; John D Rolston
Journal:  Clin Neurophysiol       Date:  2008-07-15       Impact factor: 3.708

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