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

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 Stimulation (TMS).

You might also read

Related Articles

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

Sort by
Same author

Instrumental Activities of Daily Living in Older Adults with Epilepsy: A Cross-Sectional and Longitudinal Multicenter Study.

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

Alzheimer's disease neuroimaging signature aids identification of cognitive impairment in older adults with early-onset epilepsy.

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

AT(N) Framework in Older Adults with Epilepsy: Plasma Biomarkers and Associations with Demographic, Clinical, and Cognitive Features.

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

The minimally invasive grid approach for seizure localization: patient series.

Journal of neurosurgery. Case lessons·2026
Same author

Face-name associative memory in temporal lobe epilepsy: Region-specific insights in right-hemisphere onset.

Epilepsy research·2026
Same author

Neuromuscular Basis of Kinematic Adaptations During Bidirectional Walking.

bioRxiv : the preprint server for biology·2026
Same journal

Thyroid Dysfunction and the Risk of Clinically Relevant Depression: A Longitudinal Cohort Study.

Mayo Clinic proceedings·2026
Same journal

37-Year-Old Woman With Jaundice.

Mayo Clinic proceedings·2026
Same journal

34-Year-Old Woman With An Unidentified Overdose.

Mayo Clinic proceedings·2026
Same journal

Use of Bronchoscopic Cryobiopsy in Evaluating Interstitial Lung Disease: Radiologic Predictors of Diagnostic Yield and Safety.

Mayo Clinic proceedings·2026
Same journal

Advancing Pulmonary Fibrosis Care: Integrating Genomic Insights Into Clinical Practice.

Mayo Clinic proceedings·2026
Same journal

RAAS Inhibition in the ICU: Stop, Continue, or Restart?

Mayo Clinic proceedings·2026
See all related articles

Related Experiment Video

Updated: May 25, 2026

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
06:34

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

Brain-computer interfaces in medicine.

Jerry J Shih1, Dean J Krusienski, Jonathan R Wolpaw

  • 1Department of Neurology, Mayo Clinic, 4500 San Pablo Rd., Jacksonville, FL 32224, USA. shih.jerry@mayo.edu

Mayo Clinic Proceedings
|February 14, 2012
PubMed
Summary
This summary is machine-generated.

Brain-computer interfaces (BCIs) restore function for individuals with neuromuscular disorders by translating brain signals into device commands. Future advancements require improved hardware, real-world validation, and enhanced reliability for widespread adoption.

More Related Videos

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

Related Experiment Videos

Last Updated: May 25, 2026

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
06:34

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Rehabilitation Technology

Background:

  • Brain-computer interfaces (BCIs) bypass traditional neuromuscular pathways.
  • BCIs aim to restore or replace lost function in individuals with conditions like ALS, cerebral palsy, stroke, and spinal cord injury.
  • Current BCI applications range from basic communication to controlling advanced prosthetics and wheelchairs.

Purpose of the Study:

  • To provide an overview of the current state and future directions of Brain-Computer Interface (BCI) technology.
  • To highlight the potential of BCIs for individuals with disabilities and in medical applications.
  • To identify key areas for future research and development in BCI.

Main Methods:

  • Review of existing BCI research and development.
  • Analysis of various signal acquisition techniques including electroencephalography (EEG), intracortical, and electrocorticography (ECoG).
  • Discussion of BCI applications in controlling external devices like cursors, robotic arms, and wheelchairs.

Main Results:

  • BCIs have demonstrated increasing complexity in controlling devices.
  • Potential applications extend to stroke rehabilitation and augmenting professional performance.
  • Significant progress has been made from basic spelling devices to sophisticated motor control.

Conclusions:

  • Future BCI success hinges on advancements in convenient, portable, and safe signal-acquisition hardware.
  • Long-term validation in real-world settings and effective dissemination models are crucial.
  • Improving the reliability of BCI performance to match natural motor function is essential for widespread adoption.