Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 207305, 9 pages
Research Article

Redundancy as a Graph-Based Index of Frequency Specific MEG Functional Connectivity

1Department of Neuroscience and Imaging, “G. d'Annunzio” University of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy
2Institute of Advanced Biomedical Technologies, “G. d'Annunzio” University Foundation, Via dei Vestini 31, 66100 Chieti, Italy
3Neuroelectrical Imaging and BCI Lab, IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179 Rome, Italy
4Department of Physiology and Pharmacology, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy

Received 30 March 2012; Revised 26 July 2012; Accepted 30 August 2012

Academic Editor: Danielle Bassett

Copyright © 2012 Claudia Di Lanzo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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 ( ) 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.