Measuring functional connectivity in MEG: A multivariate approach insensitive to linear source leakage
By Matthew J. Brookes, Mark William Woolrich, Gareth Robert Barnes. NeuroImage, 2012
351 citations recorded by the source corpus.
A number of recent studies have begun to show the promise of magnetoencephalography (MEG) as a means to non-invasively measure functional connectivity within distributed networks in the human brain. However, a number of problems with the methodology still remain — the biggest of these being how to deal with the non-independence of voxels in source space, often termed signal leakage. In this paper we demonstrate a method by which non-zero lag cortico-cortical interactions between the power envelopes of neural oscillatory processes can be reliably identified within a multivariate statistical framework. The method is spatially unbiased, moderately conservative in false positive rate and removes linear signal leakage between seed and target voxels. We demonstrate this methodology in simulation and in real MEG data. The multivariate method offers a powerful means to capture the high dimensionality and rich information content of MEG signals in a single imaging statistic. Given a significant interaction between two areas, we go on to show how classical statistical tests can be used to quantify the importance of the data features driving the interaction.
Subfields: Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/9298bc29443bdfe48bed12456fabd3e8e7af03ed
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Mark William Woolrich
- Stephen M. Smith
- Matthew J. Brookes
- Giles L. Colclough
- Andrew J. Quinn
- Prejaas Kavish Baldewpersad Tewarie
- Christian F. Beckmann
- Timothy Edward John Behrens
Citations in the corpus
- How reliable are MEG resting-state connectivity metrics? (2016, methodology): “We estimated the amplitude coupling between ROIs using linear correlations and partial correlations of the envelopes of the band-pass filtered signals (Brookes et al., 2012; Hipp et al., 2012).”
- Exploring mechanisms of spontaneous functional connectivity in MEG: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations (2014, neutral): “This signal leakage is zero-lag and so is removed by orthogonalizing the time series (Brookes et al., 2012; Hipp et al., 2012).”