Unknown

Dataset Information

0

A symmetric multivariate leakage correction for MEG connectomes.


ABSTRACT: Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process enables the straightforward application of network modelling methods, including partial correlation or multivariate autoregressive modelling, to infer connectomes, or functional networks, from the corrected ROIs. Here, we apply the correction to simulated MEG recordings of simple networks and to a resting-state dataset collected from eight subjects, before computing the partial correlations between power envelopes of the corrected ROItime-courses. We show accurate reconstruction of our simulated networks, and in the analysis of real MEGresting-state connectivity, we find dense bilateral connections within the motor and visual networks, together with longer-range direct fronto-parietal connections.

SUBMITTER: Colclough GL 

PROVIDER: S-EPMC4528074 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

A symmetric multivariate leakage correction for MEG connectomes.

Colclough G L GL   Brookes M J MJ   Smith S M SM   Woolrich M W MW  

NeuroImage 20150407


Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process enables the straightforward application of network modelling methods, including partial correlation or multivariate autoregressive modelling, to infer connectomes, or  ...[more]

Similar Datasets

| S-EPMC7612292 | biostudies-literature
| S-EPMC7979694 | biostudies-literature
| S-EPMC6005563 | biostudies-literature
| S-EPMC6823434 | biostudies-literature
| S-EPMC8055878 | biostudies-literature