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Encyclopedia of Computational Neuroscience pp 1–4Cite as

Computational Models Supporting Parameter Finding for Deep Brain Stimulation

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Definition

Deep brain stimulation is a surgical therapy involving electrical stimulation of the brain via chronically implanted electrodes.

Once implanted, there are a number of stimulation parameters which must be set by the clinician in order to suppress the pathological symptoms, while not inducing any unwanted side effects.

Computational models can be used to estimate the optimal parameter settings for DBS to aid this process.

Detailed Description

Deep Brain Stimulation

Over 20 years ago (Benabid et al. 1987), deep brain stimulation (DBS) was introduced as a clinical therapy for a number of neurological and more recently psychological disorders. The treatment involves chronic electrical stimulation via quadripolar electrodes implanted into various regions of the human brain in a disorder-specific manner. Most commonly, DBS is used to treat a range of movement disorders such as essential tremor, Parkinson’s disease, and dystonia (Vidailhet et al. 2005; Deuschl et al. 2006; Kupsch...

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References

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Author information

Authors and Affiliations

  1. Division of Brain Sciences, Imperial College London, London, UK

    Nada Yousif

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  1. Nada Yousif
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Correspondence to Nada Yousif .

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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Yousif, N. (2014). Computational Models Supporting Parameter Finding 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_367-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_367-1

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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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