Literature DB >> 24239589

The relationship between MEG and fMRI.

Emma L Hall1, Siân E Robson1, Peter G Morris1, Matthew J Brookes2.   

Abstract

In recent years functional neuroimaging techniques such as fMRI, MEG, EEG and PET have provided researchers with a wealth of information on human brain function. However none of these modalities can measure directly either the neuro-electrical or neuro-chemical processes that mediate brain function. This means that metrics directly reflecting brain 'activity' must be inferred from other metrics (e.g. magnetic fields (MEG) or haemodynamics (fMRI)). To overcome this limitation, many studies seek to combine multiple complementary modalities and an excellent example of this is the combination of MEG (which has high temporal resolution) with fMRI (which has high spatial resolution). However, the full potential of multi-modal approaches can only be truly realised in cases where the relationship between metrics is known. In this paper, we explore the relationship between measurements made using fMRI and MEG. We describe the origins of the two signals as well as their relationship to electrophysiology. We review multiple studies that have attempted to characterise the spatial relationship between fMRI and MEG, and we also describe studies that exploit the rich information content of MEG to explore differing relationships between MEG and fMRI across neural oscillatory frequency bands. Monitoring the brain at "rest" has become of significant recent interest to the neuroimaging community and we review recent evidence comparing MEG and fMRI metrics of functional connectivity. A brief discussion of the use of magnetic resonance spectroscopy (MRS) to probe the relationship between MEG/fMRI and neurochemistry is also given. Finally, we highlight future areas of interest and offer some recommendations for the parallel use of fMRI and MEG.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BOLD; MEG; Neural oscillations; Resting state; fMRI

Mesh:

Year:  2013        PMID: 24239589     DOI: 10.1016/j.neuroimage.2013.11.005

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  37 in total

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4.  Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story?

Authors:  Lori Sanfratello; Jon M Houck; Vince D Calhoun
Journal:  Brain Connect       Date:  2019-04

Review 5.  Modeling and interpreting mesoscale network dynamics.

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Journal:  Neuroimage       Date:  2017-06-20       Impact factor: 6.556

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Journal:  Brain Connect       Date:  2021-11-02

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Journal:  Cereb Cortex       Date:  2019-12-17       Impact factor: 5.357

8.  Relationships between cortical myeloarchitecture and electrophysiological networks.

Authors:  Benjamin A E Hunt; Prejaas K Tewarie; Olivier E Mougin; Nicolas Geades; Derek K Jones; Krish D Singh; Peter G Morris; Penny A Gowland; Matthew J Brookes
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-08       Impact factor: 11.205

9.  Selective auditory attention within naturalistic scenes modulates reactivity to speech sounds.

Authors:  Hanna Renvall; Jaeho Seol; Riku Tuominen; Bettina Sorger; Lars Riecke; Riitta Salmelin
Journal:  Eur J Neurosci       Date:  2021-11-03       Impact factor: 3.698

10.  Spatially and Temporally Distinct Encoding of Muscle and Kinematic Information in Rostral and Caudal Primary Motor Cortex.

Authors:  James Kolasinski; Diana C Dima; David M A Mehler; Alice Stephenson; Sara Valadan; Slawomir Kusmia; Holly E Rossiter
Journal:  Cereb Cortex Commun       Date:  2020-04-04
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