Hyperedge bundling: A practical solution to spurious interactions in MEG/EEG source connectivity analyses.
Inter-areal functional connectivity (FC), neuronal synchronization in particular, is thought to constitute a key systems-level mechanism for coordination of neuronal processing and communication between brain regions. Evidence to support this hypothesis has been gained largely using invasive electrophysiological approaches. In humans, neuronal activity can be non-invasively recorded only with magneto- and electroencephalography (MEG/EEG), which have been used to assess FC networks with high temporal resolution and whole-scalp coverage. However, even in source-reconstructed MEG/EEG data, signal mixing, or "source leakage", is a significant confounder for FC analyses and network localization. Signal mixing leads to two distinct kinds of false-positive observations: artificial interactions (AI) caused directly by mixing and spurious interactions (SI) arising indirectly from the spread of signals from true interacting sources to nearby false loci. To date, several interaction metrics have been developed to solve the AI problem, but the SI problem has remained largely intractable in MEG/EEG all-to-all source connectivity studies. Here, we advance a novel approach for correcting SIs in FC analyses using source-reconstructed MEG/EEG data. Our approach is to bundle observed FC connections into hyperedges by their adjacency in signal mixing. Using realistic simulations, we show here that bundling yields hyperedges with good separability of true positives and little loss in the true positive rate. Hyperedge bundling thus significantly decreases graph noise by minimizing the false-positive to true-positive ratio. Finally, we demonstrate the advantage of edge bundling in the visualization of large-scale cortical networks with real MEG data. We propose that hypergraphs yielded by bundling represent well the set of true cortical interactions that are detectable and dissociable in MEG/EEG connectivity analysis.
['Wang|Sheng H|SH|', 'Lobier|Muriel|M|', 'Siebenhühner|Felix|F|', 'Puoliväli|Tuomas|T|', 'Palva|Satu|S|', 'Palva|J Matias|JM|']
D001921:Brain D001931:Brain Mapping D003198:Computer Simulation D004569:Electroencephalography D006801:Humans D015225:Magnetoencephalography D008959:Models, Neurological D009415:Nerve Net D012815:Signal Processing, Computer-Assisted
MEG EEG Signal mixing Artificial correlation Graph theory Point spread Signal leakage Spurious correlation Volume conduction