Cargando…
How reliable are MEG resting-state connectivity metrics?
MEG offers dynamic and spectral resolution for resting-state connectivity which is unavailable in fMRI. However, there are a wide range of available network estimation methods for MEG, and little in the way of existing guidance on which ones to employ. In this technical note, we investigate the exte...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Press
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5056955/ https://www.ncbi.nlm.nih.gov/pubmed/27262239 http://dx.doi.org/10.1016/j.neuroimage.2016.05.070 |
_version_ | 1782458969733726208 |
---|---|
author | Colclough, G.L. Woolrich, M.W. Tewarie, P.K. Brookes, M.J. Quinn, A.J. Smith, S.M. |
author_facet | Colclough, G.L. Woolrich, M.W. Tewarie, P.K. Brookes, M.J. Quinn, A.J. Smith, S.M. |
author_sort | Colclough, G.L. |
collection | PubMed |
description | MEG offers dynamic and spectral resolution for resting-state connectivity which is unavailable in fMRI. However, there are a wide range of available network estimation methods for MEG, and little in the way of existing guidance on which ones to employ. In this technical note, we investigate the extent to which many popular measures of stationary connectivity are suitable for use in resting-state MEG, localising magnetic sources with a scalar beamformer. We use as empirical criteria that network measures for individual subjects should be repeatable, and that group-level connectivity estimation shows good reproducibility. Using publically-available data from the Human Connectome Project, we test the reliability of 12 network estimation techniques against these criteria. We find that the impact of magnetic field spread or spatial leakage artefact is profound, creates a major confound for many connectivity measures, and can artificially inflate measures of consistency. Among those robust to this effect, we find poor test-retest reliability in phase- or coherence-based metrics such as the phase lag index or the imaginary part of coherency. The most consistent methods for stationary connectivity estimation over all of our tests are simple amplitude envelope correlation and partial correlation measures. |
format | Online Article Text |
id | pubmed-5056955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Academic Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-50569552016-10-14 How reliable are MEG resting-state connectivity metrics? Colclough, G.L. Woolrich, M.W. Tewarie, P.K. Brookes, M.J. Quinn, A.J. Smith, S.M. Neuroimage Technical Note MEG offers dynamic and spectral resolution for resting-state connectivity which is unavailable in fMRI. However, there are a wide range of available network estimation methods for MEG, and little in the way of existing guidance on which ones to employ. In this technical note, we investigate the extent to which many popular measures of stationary connectivity are suitable for use in resting-state MEG, localising magnetic sources with a scalar beamformer. We use as empirical criteria that network measures for individual subjects should be repeatable, and that group-level connectivity estimation shows good reproducibility. Using publically-available data from the Human Connectome Project, we test the reliability of 12 network estimation techniques against these criteria. We find that the impact of magnetic field spread or spatial leakage artefact is profound, creates a major confound for many connectivity measures, and can artificially inflate measures of consistency. Among those robust to this effect, we find poor test-retest reliability in phase- or coherence-based metrics such as the phase lag index or the imaginary part of coherency. The most consistent methods for stationary connectivity estimation over all of our tests are simple amplitude envelope correlation and partial correlation measures. Academic Press 2016-09 /pmc/articles/PMC5056955/ /pubmed/27262239 http://dx.doi.org/10.1016/j.neuroimage.2016.05.070 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technical Note Colclough, G.L. Woolrich, M.W. Tewarie, P.K. Brookes, M.J. Quinn, A.J. Smith, S.M. How reliable are MEG resting-state connectivity metrics? |
title | How reliable are MEG resting-state connectivity metrics? |
title_full | How reliable are MEG resting-state connectivity metrics? |
title_fullStr | How reliable are MEG resting-state connectivity metrics? |
title_full_unstemmed | How reliable are MEG resting-state connectivity metrics? |
title_short | How reliable are MEG resting-state connectivity metrics? |
title_sort | how reliable are meg resting-state connectivity metrics? |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5056955/ https://www.ncbi.nlm.nih.gov/pubmed/27262239 http://dx.doi.org/10.1016/j.neuroimage.2016.05.070 |
work_keys_str_mv | AT colcloughgl howreliablearemegrestingstateconnectivitymetrics AT woolrichmw howreliablearemegrestingstateconnectivitymetrics AT tewariepk howreliablearemegrestingstateconnectivitymetrics AT brookesmj howreliablearemegrestingstateconnectivitymetrics AT quinnaj howreliablearemegrestingstateconnectivitymetrics AT smithsm howreliablearemegrestingstateconnectivitymetrics |