Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

Imaging Studies IV: Magnetic Resonance Imaging

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

You might also read

Related Articles

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

Sort by

Same author

Closed-loop stimulation modulates attention shifting in children.

Nature neuroscience·2026

Same author

Tissue-type Differences in Focused Ultrasound and Microbubble-mediated Drug Delivery to the Brain Exist at Vessel Level.

Theranostics·2025

Same author

Disease duration modulates BOLD representations of alpha oscillations in drug-resistant epilepsy: A concurrent EEG and fMRI study.

Epilepsia·2025

Same author

The network-based underpinnings of persisting symptoms after concussion: a multimodal neuroimaging meta-analysis.

Nature. Mental health·2025

Same author

Thalamus anatomy predicts cognitive performance and hippocampal atrophy in aging adults: a UK Biobank study.

Brain communications·2025

Same author

Publisher Correction: Ultra-high gradient connectomics and microstructure MRI scanner for imaging of human brain circuits across scales.

Nature biomedical engineering·2025

Search research articles

Related Experiment Video

Updated: Jul 3, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Linear constraint minimum variance beamformer functional magnetic resonance inverse imaging.

Fa-Hsuan Lin¹, Thomas Witzel, Thomas A Zeffiro

¹Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan. fhlin@nmr.mgh.harvard.edu

|August 2, 2008

Summary

This study introduces a new method for functional magnetic resonance imaging (fMRI) to precisely map brain activity timing. The linear constraint minimal variance (LCMV) beamformer improves detection sensitivity and localization accuracy for neural signals.

More Related Videos

A Randomized, Sham-Controlled Trial of Cranial Electrical Stimulation for Fibromyalgia Pain and Physical Function, Using Brain Imaging Biomarkers

A Randomized, Sham-Controlled Trial of Cranial Electrical Stimulation for Fibromyalgia Pain and Physical Function, Using Brain Imaging Biomarkers

Published on: January 5, 2024

Related Experiment Videos

Last Updated: Jul 3, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

A Randomized, Sham-Controlled Trial of Cranial Electrical Stimulation for Fibromyalgia Pain and Physical Function, Using Brain Imaging Biomarkers

A Randomized, Sham-Controlled Trial of Cranial Electrical Stimulation for Fibromyalgia Pain and Physical Function, Using Brain Imaging Biomarkers

Published on: January 5, 2024

Area of Science:

Neuroimaging
Biophysics
Signal Processing

Background:

Accurate timing of neural activity is crucial for understanding brain function.
Existing functional magnetic resonance imaging (fMRI) methods have limitations in temporal resolution for capturing fine neural dynamics.
Spatial filtering techniques are valuable for improving source localization in neuroimaging.

Purpose of the Study:

To develop and validate a novel method for reconstructing high-temporal-resolution functional magnetic resonance imaging (fMRI) data.
To enhance the detection sensitivity and localization accuracy of task-related neural activity.
To assess the performance of the linear constraint minimal variance (LCMV) beamformer for volumetric fMRI.

Main Methods:

Utilized the linear constraint minimal variance (LCMV) beamformer for reconstructing volumetric fMRI data.
Employed signals from a high-density radio-frequency (RF) coil array for simultaneous acquisition.
Validated the method using simulated and empirical data, including an event-related design in the primary visual cortex.

Main Results:

The LCMV beamformer achieved 100 ms temporal resolution and whole-brain spatial coverage.
Demonstrated superior detection sensitivity and localization accuracy compared to minimum-norm estimate (MNE) reconstructions.
Showcased high sensitivity and inter-subject reliability in detecting spatio-temporal brain activity modulations.

Conclusions:

The volumetric LCMV beamformer method offers significant improvements in accurately estimating neural activity timing.
This technique enhances the ability to detect the fine temporal structure of task-related brain activity.
The findings support the use of LCMV in fMRI for detailed analysis of neural information flow.