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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...

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Related Experiment Video

Updated: May 5, 2026

fMRI Validation of fNIRS Measurements During a Naturalistic Task

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Published on: June 15, 2015

The relationship between MEG and fMRI.

Emma L Hall¹, Siân E Robson¹, Peter G Morris¹

¹Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, UK.

|November 19, 2013

Summary

This summary is machine-generated.

This study explores the relationship between functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) to better understand brain activity. Combining these techniques offers deeper insights into neuro-electrical and neuro-chemical processes.

Keywords:

BOLD MEG Neural oscillations Resting state fMRI

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Area of Science:

Neuroscience
Biophysics
Medical Imaging

Background:

Functional neuroimaging techniques like fMRI, MEG, EEG, and PET provide extensive data on brain function.
Current methods infer brain activity from indirect metrics (e.g., hemodynamics in fMRI, magnetic fields in MEG), not direct neuro-electrical or neuro-chemical processes.

Purpose of the Study:

To explore the relationship between functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) measurements.
To understand how combining complementary modalities like fMRI and MEG can overcome individual limitations.
To investigate the relationship between fMRI and MEG signals across different neural oscillatory frequency bands and during resting-state conditions.

Main Methods:

Review of existing studies characterizing the spatial relationship between fMRI and MEG.
Analysis of studies exploiting MEG's information content to explore frequency-band-specific relationships with fMRI.
Discussion of magnetic resonance spectroscopy (MRS) for probing neurochemistry in conjunction with MEG/fMRI.

Main Results:

fMRI and MEG provide complementary spatial and temporal resolution for studying brain function.
The relationship between fMRI and MEG signals can vary across different neural oscillatory frequency bands.
Resting-state functional connectivity metrics derived from MEG and fMRI show recent interest and comparative evidence.

Conclusions:

Combining fMRI and MEG offers a powerful multi-modal approach to understanding brain function.
Understanding the relationship between fMRI and MEG metrics is crucial for realizing the full potential of combined neuroimaging.
Future research should focus on parallel fMRI and MEG use and integrating neurochemical data via MRS.