RT Journal Article
T1 Multivariate extension of phase synchronization improves the estimation of region-to-region source space functional connectivity
A1 Bruña Fernández, Ricardo
A1 Pereda, Ernesto
AB The estimation of functional connectivity (FC) from noninvasive electrophysiological data recorded from sensors outside the skull requires transforming these data into a source space. As the number of sensors is much lower than the number of electrophysiological sources, the brain activity is usually parcellated into anatomical regions, and the FC between each pair of regions is then estimated.In this work, we generate a set of simulated scenarios with different configurations and coupling levels between synthetic time series. Then, this simulated brain activity is converted into simulated MEG sensor-space data and reconstructed back into the source space. Last, we estimated the FC between different regions using different approaches commonly used in the literature and compared them with a novel approach.Our results show that this novel approach, based on using all the information in each region, clearly outperforms classical approaches based on a representative time series. The proposed approach is more sensitive to the level of coupling and the extent of the area synchronized, and the resulting estimate better reflects the underlying FC. Based on these results, we strongly discourage using a representative time series to summarize large brain areas' activity when calculating FC.
PB Elsevier
SN 2666-5220
YR 2021
FD 2021-01-08
LK https://hdl.handle.net/20.500.14352/100252
UL https://hdl.handle.net/20.500.14352/100252
LA eng
NO Ministerio de Ciencia
NO Gobierno de las Islas Canarias
NO Comunidad de Madrid
DS Docta Complutense
RD 27 sept 2024