Optimising experimental design for MEG resting state functional connectivity measurement

Liuzzi, Lucrezia, Gascoyne, Lauren E., Tewarie, Prejaas K., Barratt, Eleanor L., Boto, Elena and Brookes, Matthew J. (2016) Optimising experimental design for MEG resting state functional connectivity measurement. NeuroImage . ISSN 1053-8119 (In Press)

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The study of functional connectivity using magnetoencephalography (MEG) is an expanding area of neuroimaging, and adds an extra dimension to the more common assessments made using fMRI. The importance of such metrics is growing, with recent demonstrations of their utility in clinical research, however previous reports suggest that whilst group level resting state connectivity is robust, single session recordings lack repeatability. Such robustness is critical if MEG measures in individual subjects are to prove clinically valuable. In the present paper, we test how practical aspects of experimental design affect the intra-subject repeatability of MEG findings; specifically we assess the effect of co-registration method and data recording duration. We show that the use of a foam head-cast, which is known to improve co-registration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation. We also show that recording duration is a critical parameter, with large improvements in repeatability apparent when using ten minute, compared to five minute recordings. Further analyses suggest that the origin of this latter effect is not underpinned by technical aspects of source reconstruction, but rather by a genuine effect of brain state; short recordings are simply inefficient at capturing the canonical MEG network in a single subject. Our results provide important insights on experimental design and will prove valuable for future MEG connectivity studies.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/826901
Keywords: Functional connectivity; Networks; Magnetoencephalography; MEG; Resting State; Beamformer
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Physics and Astronomy
Identification Number: https://doi.org/10.1016/j.neuroimage.2016.11.064
Depositing User: Liuzzi, Lucrezia
Date Deposited: 21 Feb 2017 11:20
Last Modified: 04 May 2020 18:19
URI: https://eprints.nottingham.ac.uk/id/eprint/40631

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