Identifying true cortical interactions in MEG using the nulling beamformer

• Published in: NeuroImage (Orlando, Fla.) Vol. 49; no. 4; pp. 3161 - 3174
• Main Authors: Hui, Hua Brian, Pantazis, Dimitrios, Bressler, Steven L., Leahy, Richard M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15-02-2010; Elsevier Limited
• Subjects: Algorithms; Brain Mapping - methods; Coherence; Computer Simulation; Cortical interaction; Functional connectivity; Granger causality; Humans; LCMV; Macaca; Magnetoencephalography - methods; Methods; Models, Neurological; MVAR; Nerve Net - physiology; Noise; Nulling beamformer; Phase synchrony; Functional connectivity; LCMV; Coherence; Cortical interaction; MVAR; Phase synchrony; Granger causality; Nulling beamformer
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2009.10.078

Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recording data. This is because most interaction measures are not robust to the cross-talk (interference) between cortical regions, which may arise due to the limited spatial resolution of EEG/MEG inverse procedures. In this article, we describe a modified beamforming approach to accurately measure cortical interactions from EEG/MEG data, designed to suppress cross-talk between cortical regions. We estimate interaction measures from the output of the modified beamformer and test for statistical significance using permutation tests. Since the underlying neuronal sources and their interactions are unknown in real MEG data, we demonstrate the performance of the proposed beamforming method in a novel simulation scheme, where intracranial recordings from a macaque monkey are used as neural sources to simulate realistic MEG signals. The advantage of this approach is that local field potentials are more realistic representations of true neuronal sources than simulation models and therefore are more suitable to indicate the performance of our nulling beamforming method.