title: Redundancy as a graph-based index of frequency specific MEG functional connectivity.
abstract: We used a recently proposed graph index to investigate connectivity redundancy in resting state MEG recordings. Usually, brain network analyses consider indexes linked to the shortest paths between cerebral regions. However, important information might be lost about alternative trails by neglecting longer pathways. We measured the redundancy of the connectivity by considering the multiple paths at the global level (i.e., scalar redundancy), across different path lengths (i.e., vector redundancy), and between node pairs (i.e., matrix redundancy). We applied this approach to a robust frequency domain functional connectivity measure, the corrected imaginary part of coherence. The redundancy in the MEG networks, for each frequency band, was significantly (P < 0.05) higher than in the random graphs, thus, confirming a natural tendency of the brain to present multiple interaction pathways between different specialized areas. Notably, this difference was more evident and localized among the channels covering the parietooccipital areas in the alpha range of MEG oscillations (7.5-13 Hz), as expected in the resting state conditions. Interestingly enough, the results obtained with the redundancy indexes were poorly correlated with those obtained using shortest paths only, and more sensitive with respect to those obtained by considering walk-based indexes.
authors.affiliation: Department of Neuroscience and Imaging, G. d'Annunzio University of Chieti-Pescara, Via dei Vestini 31, Chieti, Italy. claudia.dilanzo@unich.it
authors.forename: Claudia
authors.initials: C
authors.lastname: Di Lanzo
authors.forename: Laura
authors.initials: L
authors.lastname: Marzetti
authors.forename: Filippo
authors.initials: F
authors.lastname: Zappasodi
authors.forename: Fabrizio
authors.initials: F
authors.lastname: De Vico Fallani
authors.forename: Vittorio
authors.initials: V
authors.lastname: Pizzella
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D019295:Computational Biology / Q000379:methods; D004569:Electroencephalography / Q000379:methods; D005583:Fourier Analysis; D006439:Hemodynamics; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical; D009473:Neuronal Plasticity; D009778:Occipital Lobe / Q000473:pathology; D009991:Oscillometry / Q000379:methods; D010296:Parietal Lobe / Q000473:pathology; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult