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

Brain Imaging01:14

Brain Imaging

282
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
282

You might also read

Related Articles

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

Sort by
Same author

The 2026 global roadmap for textile-integrated wearable technologies in health.

Physiological measurement·2026
Same author

Interdigitated capacitive strain sensor enables precise yoga-inspired motion tracking.

Npj biosensing·2026
Same author

Lighting effects on optimal facial regions for remote heart rate measurement.

NPJ cardiovascular health·2026
Same author

Dataset effects outweigh algorithmic effects in determining fairness of healthcare machine learning.

NPJ digital medicine·2026
Same author

Roadmap of remote photoplethysmography from heart rate measurement toward clinical translation.

NPJ digital medicine·2026
Same author

Optimized sensor-embedded loose garment for accurate motion detection.

Communications engineering·2026

Related Experiment Video

Updated: Aug 23, 2025

Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
10:14

Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

Published on: May 10, 2024

1.1K

A Method for Using Neurofeedback to Guide Mental Imagery for Improving Motor Skill.

Nader Riahi, William Ruth, Ryan C N D'Arcy

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |November 1, 2022
    PubMed
    Summary

    This study introduces an individualized neurofeedback method using EEG to enhance motor skills through mental imagery. The technique significantly reduced tracing errors and showed lasting improvements, offering a practical approach to motor function therapy.

    More Related Videos

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
    09:42

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

    Published on: September 1, 2023

    1.4K
    A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
    07:05

    A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

    Published on: August 24, 2017

    11.1K

    Related Experiment Videos

    Last Updated: Aug 23, 2025

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality
    10:14

    Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

    Published on: May 10, 2024

    1.1K
    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
    09:42

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

    Published on: September 1, 2023

    1.4K
    A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
    07:05

    A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

    Published on: August 24, 2017

    11.1K

    Area of Science:

    • Neuroscience
    • Motor Control
    • Brain-Computer Interfaces

    Background:

    • Mental imagery (MI) is explored for endogenous brain stimulation to improve motor skills.
    • Neurofeedback (NF) is often used to guide MI and activate specific brain networks.
    • Individualized approaches are needed to optimize NF for motor skill enhancement.

    Purpose of the Study:

    • To investigate an individualized EEG-based neurofeedback (NF) method for motor skill improvement.
    • To explore the relationship between brain functional connectivity (FC) and motor skill acquisition.
    • To develop a practical, accessible strategy for personalized motor function therapy.

    Main Methods:

    • Utilized digital tracing tasks to measure motor skill changes via spatial error.
    • Employed partial least squares to identify brain networks correlating resting-state FC with motor skill.
    • Implemented real-time audio feedback of instantaneous FC to guide mental imagery during NF training.

    Main Results:

    • Achieved over 20% reduction in tracing error using NF with MI, without additional physical training.
    • Demonstrated retention of motor skill improvements for several days post-NF training.
    • Identified a specific brain network with high potential for FC increase as a target for NF.

    Conclusions:

    • The proposed individualized EEG-based NF method shows promise for enhancing motor skill.
    • This approach offers a practical, complementary strategy for personalized therapeutic interventions.
    • Accessible EEG technology can facilitate widespread application for improving motor function.