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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Impaired autobiographical remembering and future thinking in temporal lobe epilepsy.

Epilepsy & behavior : E&B·2026
Same author

Multimodal Cross-Attention Fusion of B-Mode Ultrasound and Strain Elastography for Tumor Segmentation in Robotics-Assisted Surgery.

IEEE transactions on medical robotics and bionics·2026
Same author

How Do I: How and When Do I Inject Suboccipital Muscles in Cervical Dystonia.

Movement disorders clinical practice·2026
Same author

Is levodopa induced freezing of gait a paradox or an expected phenomenon?: a clinico-pathophysiological hypothesis.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2026
Same author

Enhancing PPO With Trajectory-Aware Hybrid Policies.

IEEE transactions on neural networks and learning systems·2026
Same author

Impact of DaTscan on the Management of Clinically Uncertain Parkinsonian Syndromes: A Retrospective Canadian Cohort Study.

The Canadian journal of neurological sciences. Le journal canadien des sciences neurologiques·2026

Related Experiment Video

Updated: Dec 23, 2025

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

9.2K

Intraoperative Localization of STN During DBS Surgery Using a Data-Driven Model.

Mahsa Khosravi1,2, S Farokh Atashzar3,4,5, Greydon Gilmore6

  • 11Department of Electrical and Computer EngineeringUniversity of Western OntarioLondonONN6A 3K7Canada.

IEEE Journal of Translational Engineering in Health and Medicine
|April 21, 2020
PubMed
Summary

This study introduces a new machine learning method using microelectrode recordings to precisely locate the Subthalamic Nucleus (STN) during Deep Brain Stimulation (DBS) surgery for Parkinson's Disease patients.

Keywords:
Deep brain stimulationParkinson’s diseasedeep neural networkintraoperative localization of STN

More Related Videos

Intra-Operative Behavioral Tasks in Awake Humans Undergoing Deep Brain Stimulation Surgery
12:04

Intra-Operative Behavioral Tasks in Awake Humans Undergoing Deep Brain Stimulation Surgery

Published on: January 6, 2011

13.4K
Deep Brain Stimulation with Simultaneous fMRI in Rodents
11:09

Deep Brain Stimulation with Simultaneous fMRI in Rodents

Published on: February 15, 2014

14.5K

Related Experiment Videos

Last Updated: Dec 23, 2025

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

9.2K
Intra-Operative Behavioral Tasks in Awake Humans Undergoing Deep Brain Stimulation Surgery
12:04

Intra-Operative Behavioral Tasks in Awake Humans Undergoing Deep Brain Stimulation Surgery

Published on: January 6, 2011

13.4K
Deep Brain Stimulation with Simultaneous fMRI in Rodents
11:09

Deep Brain Stimulation with Simultaneous fMRI in Rodents

Published on: February 15, 2014

14.5K

Area of Science:

  • Neurosurgery
  • Computational Neuroscience
  • Machine Learning

Background:

  • Deep Brain Stimulation (DBS) is a key treatment for Parkinson's Disease (PD).
  • Accurate localization of the Subthalamic Nucleus (STN) is critical for effective DBS surgery.
  • Current methods for STN localization rely on intraoperative microelectrode recordings (MERs).

Purpose of the Study:

  • To develop an objective, data-driven approach for precise STN localization during DBS surgery.
  • To improve the accuracy and reliability of identifying the neurophysiological borders of the STN.
  • To implement a real-time system for guiding electrode placement in STN DBS procedures.

Main Methods:

  • Processing microelectrode recording (MER) signals to extract wavelet transformation features.
  • Utilizing a machine learning (ML) algorithm, specifically a deep neural network, for STN border detection.
  • Developing a novel classification approach to identify both dorsal and ventral STN boundaries.

Main Results:

  • The proposed ML approach achieved 92% accuracy in detecting the STN borders.
  • Wavelet transformation features effectively characterized MER signals for STN localization.
  • The deep neural network model demonstrated robust performance in a study of 100 PD patients.

Conclusions:

  • The developed computational method offers a significant advancement in real-time STN localization for DBS surgery.
  • This approach enhances the precision of electrode placement, potentially improving DBS therapy outcomes for Parkinson's Disease.
  • The system effectively models neurophysiological nonlinearities encountered during electrode insertion.