Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Computational analysis of deep brain stimulation.

Cameron C McIntyre1, Svjetlana Miocinovic, Christopher R Butson

  • 1Department of Biomedical Engineering, Cleveland Clinic Foundation, Cleveland, OH 44195, USA. mcintyc@ccf.org

Expert Review of Medical Devices
|September 14, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Pallidal Deep Brain Stimulation in Dystonia: Investigating Differential Response by Dystonia Distribution.

Tremor and other hyperkinetic movements (New York, N.Y.)·2026
Same author

Localizing beta synchronous neurons in the STN using directional DBS recordings and patient-specific biophysical models.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2026
Same author

Optimal Deep Brain Stimulation Locations for Gilles de la Tourette Syndrome.

medRxiv : the preprint server for health sciences·2026
Same author

Model-based design of subthalamic nucleus neurons using hybrid optimization.

Journal of neurophysiology·2026
Same author

Consensus expert recommendations for referral of Parkinson's disease patients for deep brain stimulation surgery.

NPJ Parkinson's disease·2026
Same author

Motor evoked potentials as a side effect biomarker for deep brain stimulation.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2025
Same journal

Review of regulatory requirements for benefit - risk assessment for medical devices: uncovering existing methodologies.

Expert review of medical devices·2026
Same journal

Two sides to every wrist: trans-ulnar access for cardiac interventions.

Expert review of medical devices·2026
Same journal

Comparative review of coronary CT angiography versus conventional catheter angiography: diagnostic value, clinical outcomes, and underlying technical principles.

Expert review of medical devices·2026
Same journal

Assessing the MYNX CONTROL arterial vascular closure device after catheterization procedures that enter the body through the femoral arteries.

Expert review of medical devices·2026
Same journal

Efficacy of two anatomically preformed supraglottic devices, the BlockBuster Laryngeal mask airway and the Ambu AuraGain, for ventilation in anesthetised paralyzed pediatric patients: a randomized trial.

Expert review of medical devices·2026
Same journal

Prismatic treatment combined with binocular visual training for intermittent exotropia: impact on visual function and quality of life.

Expert review of medical devices·2026
See all related articles

Computer models enhance understanding of deep brain stimulation (DBS) for neurological disorders. These tools help optimize electrode designs and stimulation parameters for improved patient outcomes and next-generation DBS technology.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Computational Modeling

Background:

  • Deep brain stimulation (DBS) effectively treats refractory neurological disorders.
  • The precise mechanisms and optimal parameters for DBS remain unclear.
  • Understanding neuronal response to electrical fields is crucial for DBS efficacy.

Purpose of the Study:

  • To review the fundamentals of neurostimulation modeling for DBS.
  • To highlight the scientific contributions of computer models in DBS research.
  • To explore the future applications of DBS modeling in clinical practice and technology development.

Main Methods:

  • Review of existing literature on deep brain stimulation (DBS) and neurostimulation modeling.
  • Analysis of computer modeling techniques applied to DBS.

Related Experiment Videos

  • Discussion of the role of computational tools in understanding DBS mechanisms.

    • Main Results:

    • Computer modeling provides a powerful virtual platform for studying DBS effects.
    • Modeling aids in understanding neuronal responses to electrical stimulation.
    • It facilitates the exploration of optimal electrode designs and stimulation parameters.

    Conclusions:

    • DBS computer modeling is essential for advancing the understanding of therapeutic mechanisms.
    • Modeling tools can guide the optimization of current DBS therapies.
    • Future applications include designing next-generation DBS devices and improving clinical utility.