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Comparison of spatial leakage corrections.
Comparison of spatial leakage corrections

The brain produces its cognition by recruiting multiple brain areas across networks, and so we are developing novel methods for inferring brain networks from M/EEG data.

First, a parcellation is defined. These parcels are then treated as nodes in a network, and the relationships between them can be analysed leading to graphs of the functional connections between brain regions (i.e. a connectome). 

We are developing tools that can handle the spatial leakage and false connections induced by the uncertainties in M/EEG source reconstruction. Unlike many other methods, this is a multivariate (multi-brain-region) approach and so can account for so-called "inherited connections" or "ghost interactions". These approaches allow multi-region network analysis to be performed, providing more accurate estimation of M/EEG connectomes. 

These techniques are being applied to clinical research datasets, and to the Human Connectome Project MEG data to assess the heritability of functional connectivity.

Tools for doing this kind of analysis are contained in the osl-dynamics toolbox, which is available to download and use at the OHBA Analysis Group Software Page.


Colclough, G. L., Brookes, M., Smith, S. M. and Woolrich, M. W., "A symmetric multivariate leakage correction for MEG connectomes" NeuroImage 117, pp. 439-448 (2015).

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? NeuroImage (2016).

Colclough GL, Smith SM, Nichols TE, Winkler AM, Sotiropoulos SN, Glasser MF, Van Essen DC, Woolrich M. The heritability of multi-modal connectivity in human brain activity. ELife (2017).