Literature DB >> 27903441

Optimising experimental design for MEG resting state functional connectivity measurement.

Lucrezia Liuzzi1, Lauren E Gascoyne1, Prejaas K Tewarie1, Eleanor L Barratt1, Elena Boto1, Matthew J Brookes2.   

Abstract

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.
Copyright © 2016. Published by Elsevier Inc.

Entities:  

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

Mesh:

Year:  2016        PMID: 27903441     DOI: 10.1016/j.neuroimage.2016.11.064

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


  20 in total

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Journal:  Netw Neurosci       Date:  2022-06-01

4.  An intra-neural microstimulation system for ultra-high field magnetic resonance imaging and magnetoencephalography.

Authors:  Paul M Glover; Roger H Watkins; George C O'Neill; Rochelle Ackerley; Rosa Sanchez-Panchuelo; Francis McGlone; Matthew J Brookes; Johan Wessberg; Susan T Francis
Journal:  J Neurosci Methods       Date:  2017-07-23       Impact factor: 2.390

5.  Imaging human cortical responses to intraneural microstimulation using magnetoencephalography.

Authors:  George C O'Neill; Roger H Watkins; Rochelle Ackerley; Eleanor L Barratt; Ayan Sengupta; Michael Asghar; Rosa Maria Sanchez Panchuelo; Matthew J Brookes; Paul M Glover; Johan Wessberg; Susan T Francis
Journal:  Neuroimage       Date:  2019-01-09       Impact factor: 6.556

6.  Consistency of magnetoencephalographic functional connectivity and network reconstruction using a template versus native MRI for co-registration.

Authors:  Linda Douw; Dagmar Nieboer; Cornelis J Stam; Prejaas Tewarie; Arjan Hillebrand
Journal:  Hum Brain Mapp       Date:  2017-10-08       Impact factor: 5.038

7.  Non-invasive laminar inference with MEG: Comparison of methods and source inversion algorithms.

Authors:  James J Bonaiuto; Holly E Rossiter; Sofie S Meyer; Natalie Adams; Simon Little; Martina F Callaghan; Fred Dick; Sven Bestmann; Gareth R Barnes
Journal:  Neuroimage       Date:  2017-12-01       Impact factor: 6.556

8.  A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks.

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Journal:  PLoS Comput Biol       Date:  2018-02-23       Impact factor: 4.475

9.  Quantifying the performance of MEG source reconstruction using resting state data.

Authors:  Simon Little; James Bonaiuto; Sofie S Meyer; Jose Lopez; Sven Bestmann; Gareth Barnes
Journal:  Neuroimage       Date:  2018-07-17       Impact factor: 6.556

10.  Mapping the topological organisation of beta oscillations in motor cortex using MEG.

Authors:  Eleanor L Barratt; Susan T Francis; Peter G Morris; Matthew J Brookes
Journal:  Neuroimage       Date:  2018-06-28       Impact factor: 6.556

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