4.7 Article

Optimising experimental design for MEG resting state functional connectivity measurement

期刊

NEUROIMAGE
卷 155, 期 -, 页码 565-576

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2016.11.064

关键词

Functional connectivity; Networks; Magnetoencephalography; MEG; Resting state; Beamformer

资金

  1. Medical Research Council (MRC) [MR/M006301/1]
  2. University of Nottingham
  3. Medical Research Council [MR/K005464/1]
  4. MRC [MR/K005464/1, MR/M006301/1] Funding Source: UKRI
  5. Medical Research Council [MR/M006301/1, MR/K005464/1] Funding Source: researchfish

向作者/读者索取更多资源

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.

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