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Encyclopedia of Computational Neuroscience pp 1–5Cite as

Computational Models to Optimize the Electrodes and Waveforms for Deep Brain Stimulation

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Definition

A computational model used to optimize electrodes and waveforms for deep brain stimulation (DBS) is typically composed of two separate models: a volume conductor model of an electrode in brain tissue used to calculate electrical potential distributions and cable models of neural elements (e.g., axons, local cells) used to calculate the response of neurons to the imposed stimulation. The integrated model is interfaced with an optimization algorithm to search for solutions that increase the performance of DBS, where performance could be related to the efficiency, selectivity, and/or safety of stimulation. The results from the two models are combined to evaluate a specified cost function, and the optimization algorithm searches for a set of parameters that minimize the cost.

Detailed Description

DBS is an established therapy for treating neurological disorders, in which an implanted array of cylindrical electrodes is used to deliver rectangular waveforms of electrical pulses to...

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Duke University, Hudson Hall, 100 Science Dr, Durham, NC, 27705, USA

    Bryan Howell & Warren M. Grill

Authors
  1. Bryan Howell
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  2. Warren M. Grill
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Corresponding author

Correspondence to Bryan Howell .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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© 2014 Springer Science+Business Media New York

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Howell, B., Grill, W.M. (2014). Computational Models to Optimize the Electrodes and Waveforms for Deep Brain Stimulation. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_366-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_366-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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