A novel metric for estimating connectivity between brain areas, namely the Phase Linearity Measurement (PLM), is presented. The purpose consists in measuring the amount of information exchanged between brain areas. Such scope is achieved by analyzing the similarities between the recorded signal phases. The PLM has been designed for exploiting both Electroencephalographic (EEG) and Magnetoencephalographic (MEG) data. We compared the results achieved by PLM in case of real MEG data with a widely adopted phase based connectivity metric, the Phase Lag Index (PLI). The PLM is characterized by interesting results, mainly in terms of noise resiliency.
A novel brain functional connectivity measurement based on phase similarity
Baselice, Fabio;Sorriso, Antonietta;Rucco, Rosaria;Sorrentino, Pierpaolo
2018-01-01
Abstract
A novel metric for estimating connectivity between brain areas, namely the Phase Linearity Measurement (PLM), is presented. The purpose consists in measuring the amount of information exchanged between brain areas. Such scope is achieved by analyzing the similarities between the recorded signal phases. The PLM has been designed for exploiting both Electroencephalographic (EEG) and Magnetoencephalographic (MEG) data. We compared the results achieved by PLM in case of real MEG data with a widely adopted phase based connectivity metric, the Phase Lag Index (PLI). The PLM is characterized by interesting results, mainly in terms of noise resiliency.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
