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Dynamics of large-scale electrophysiological networks: a technical review

O'Neill, George C.; Tewarie, Prejaas K.; Vidaurre, Diego; Liuzzi, Lucrezia; Woolrich, Mark W.; Brookes, Matthew J.

Authors

George C. O'Neill george.oneill@nottingham.ac.uk

Prejaas K. Tewarie prejaas.tewarie@nottingham.ac.uk

Diego Vidaurre

Lucrezia Liuzzi lucrezia.liuzzi@nottingham.ac.uk

Mark W. Woolrich mark.woolrich@ohba.ox.ac.uk

Matthew J. Brookes matthew.brookes@nottingham.ac.uk



Abstract

For several years it has been argued that neural synchronisation is crucial for cognition. The idea that synchronised temporal patterns between different neural groups carries information above and beyond the isolated activity of these groups has inspired a shift in focus in the field of functional neuroimaging. Specifically, investigation into the activation elicited within certain regions by some stimulus or task has, in part, given way to analysis of patterns of co-activation or functional connectivity between distal regions. Recently, the functional connectivity community has been looking beyond the assumptions of stationarity that earlier work was based on, and has introduced methods to incorporate temporal dynamics into the analysis of connectivity. In particular, non-invasive electrophysiological data (magnetoencephalography / electroencephalography (MEG/EEG)), which provides direct measurement of whole-brain activity and rich temporal information, offers an exceptional window into such (potentially fast) brain dynamics. In this review, we discuss challenges, solutions, and a collection of analysis tools that have been developed in recent years to facilitate the investigation of dynamic functional connectivity using these imaging modalities. Further, we discuss the applications of these approaches in the study of cognition and neuropsychiatric disorders. Finally, we review some existing developments that, by using realistic computational models, pursue a deeper understanding of the underlying causes of non-stationary connectivity.

Journal Article Type Article
Publication Date Oct 4, 2017
Journal NeuroImage
Print ISSN 1053-8119
Electronic ISSN 1095-9572
Publisher Elsevier
Peer Reviewed Peer Reviewed
APA6 Citation O'Neill, G. C., Tewarie, P. K., Vidaurre, D., Liuzzi, L., Woolrich, M. W., & Brookes, M. J. (2017). Dynamics of large-scale electrophysiological networks: a technical review. NeuroImage, doi:10.1016/j.neuroimage.2017.10.003. ISSN 1053-8119
DOI https://doi.org/10.1016/j.neuroimage.2017.10.003
Keywords Dynamic functional connectivity; Magnetoencephalography; Dynamic functional networks; Electroencephalography; MEG; EEG
Publisher URL http://www.sciencedirect.com/science/article/pii/S1053811917308169
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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