Graph Analysis on Functional Connectivity Networks during an Emotional Paradigm

Abstract

Electroencephalographic (EEG) signals were recorded from 28 participants as they passively viewed emotional stimuli from International Affective Picture System (IAPS), categorized in 4 groups ranging in pleasure and arousal. The aim of the study was to examine if the Functional Connectivity Networks estimated during different emotional stimuli, differ in their characteristics. Functional Connectivity Networks were estimated for the four categories of emotional stimuli using coherence between each pair of electrodes on the frequency band of alpha rhythm. Graph metrics were calculated for each network and they were statistically analyzed. Pleasure was found to modify the local efficiency of the networks with unpleasant stimuli appearing to form networks with clusters easier than pleasant stimuli. Arousal also affected the global efficiency of the functional networks, with high arousing stimuli appearing to form networks with more efficient communication among nodes.