Literature DB >> 26447925

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods.

George C O'Neill1, Eleanor L Barratt, Benjamin A E Hunt, Prejaas K Tewarie, Matthew J Brookes.   

Abstract

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ability to estimate this connectivity. In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5 mm) spatial resolution and excellent (~1 ms) temporal resolution. The rich information content of MEG facilitates many disparate measures of connectivity between spatially separate regions and in this paper we discuss a single metric known as power envelope correlation. We review in detail the methodology required to measure power envelope correlation including (i) projection of MEG data into source space, (ii) removing confounds introduced by the MEG inverse problem and (iii) estimation of connectivity itself. In this way, we aim to provide researchers with a description of the key steps required to assess envelope based functional networks, which are thought to represent an intrinsic mode of coupling in the human brain. We highlight the principal findings of the techniques discussed, and furthermore, we show evidence that this method can probe how the brain forms and dissolves multiple transient networks on a rapid timescale in order to support current processing demand. Overall, power envelope correlation offers a unique and verifiable means to gain novel insights into network coordination and is proving to be of significant value in elucidating the neural dynamics of the human connectome in health and disease.

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Year:  2015        PMID: 26447925     DOI: 10.1088/0031-9155/60/21/R271

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  23 in total

1.  Electrophysiological Brain Connectivity: Theory and Implementation.

Authors:  Bin He; Laura Astolfi; Pedro A Valdes-Sosa; Daniele Marinazzo; Satu Palva; Christian G Benar; Christoph M Michel; Thomas Koenig
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-07       Impact factor: 4.538

2.  MEG Oscillatory Slowing in Cognitive Impairment is Associated with the Presence of Subjective Cognitive Decline.

Authors:  Ricardo Bruña; David López-Sanz; Fernando Maestú; Ann D Cohen; Anto Bagic; Ted Huppert; Tae Kim; Rebecca E Roush; Betz Snitz; James T Becker
Journal:  Clin EEG Neurosci       Date:  2022-02-21       Impact factor: 2.046

3.  Long-Range Amplitude Coupling Is Optimized for Brain Networks That Function at Criticality.

Authors:  Arthur-Ervin Avramiea; Anas Masood; Huibert D Mansvelder; Klaus Linkenkaer-Hansen
Journal:  J Neurosci       Date:  2022-01-26       Impact factor: 6.709

4.  Electroencephalography Source Functional Connectivity Reveals Abnormal High-Frequency Communication Among Large-Scale Functional Networks in Depression.

Authors:  Alexis E Whitton; Stephanie Deccy; Manon L Ironside; Poornima Kumar; Miranda Beltzer; Diego A Pizzagalli
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2017-07-13

5.  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

6.  The heritability of multi-modal connectivity in human brain activity.

Authors:  Giles L Colclough; Stephen M Smith; Thomas E Nichols; Anderson M Winkler; Stamatios N Sotiropoulos; Matthew F Glasser; David C Van Essen; Mark W Woolrich
Journal:  Elife       Date:  2017-07-26       Impact factor: 8.140

Review 7.  Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence.

Authors:  Golnoush Alamian; Ana-Sofía Hincapié; Etienne Combrisson; Thomas Thiery; Véronique Martel; Dmitrii Althukov; Karim Jerbi
Journal:  Front Psychiatry       Date:  2017-03-17       Impact factor: 4.157

8.  Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer's disease.

Authors:  Tatiana A Sitnikova; Jeremy W Hughes; Seppo P Ahlfors; Mark W Woolrich; David H Salat
Journal:  Neuroimage Clin       Date:  2018-05-22       Impact factor: 4.881

9.  Changes in electrophysiological markers of cognitive control after administration of galantamine.

Authors:  Lauren E Gascoyne; Karen J Mullinger; Siân E Robson; Jyothika Kumar; George C O'Neill; Lena Palaniyappan; Peter G Morris; Elizabeth B Liddle; Matthew J Brookes; Peter F Liddle
Journal:  Neuroimage Clin       Date:  2018-07-23       Impact factor: 4.881

10.  A multi-layer network approach to MEG connectivity analysis.

Authors:  Matthew J Brookes; Prejaas K Tewarie; Benjamin A E Hunt; Sian E Robson; Lauren E Gascoyne; Elizabeth B Liddle; Peter F Liddle; Peter G Morris
Journal:  Neuroimage       Date:  2016-02-22       Impact factor: 6.556

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