Multi-modal causality analysis of eyes-open and eyes-closed data from simultaneously recorded EEG and MEG

Owing to the recent advances in multi-modal data analysis, the aim of the present study was to analyze the functional network of the brain which remained the same during the eyes-open (EO) and eyes-closed (EC) resting task. The simultaneously recorded electroencephalogram (EEG) and magnetoencephalogram (MEG) were used for this study, recorded from five distinct cortical regions of the brain. We focused on the `alpha' functional network, corresponding to the individual peak frequency in the alpha band. The total data set of 120 seconds was divided into three segments of 18 seconds each, taken from start, middle, and end of the recording. This segmentation allowed us to analyze the evolution of the underlying functional network. The method of time-resolved partial directed coherence (tPDC) was used to assess the causality. This method allowed us to focus on the individual peak frequency in the `alpha' band (7-13 Hz). Because of the significantly higher power in the recorded EEG in comparison to MEG, at the individual peak frequency of the alpha band, results rely only on EEG. The MEG was used only for comparison. Our results show that different regions of the brain start to `disconnect' from one another over the course of time. The driving signals, along with the feedback signals between different cortical regions start to recede over time. This shows that, with the course of rest, brain regions reduce communication with each another.

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