Abstract
In the present study, we investigated whether global electroencephalography (EEG) synchronization can be a new promising index for tracking emotional arousal changes of a group of individuals during video watching. Global field synchronization (GFS), an index known to correlate with human cognitive processes, was evaluated; this index quantified the global temporal synchronization among multichannel EEG data recorded from a group of participants (n = 25) during the plays of two short video clips. The two video clips were each about 5 min long and were designed to evoke negative (fearful) or positive (happy) emotion, respectively. Another group of participants (n = 37) was asked to select the two most emotionally arousing (most touching or most fearful) scenes in each clip. The results of these questionnaire surveys were used as the ground-truth to evaluate whether the GFS could detect emotional highlights of both video clips. The emotional highlights estimated using the grand-averaged GFS waveforms of the first group were also compared with those evaluated from galvanic skin response, photoplethysmography, and multimedia content analysis, which are conventional methods used to estimate temporal changes in emotional arousal during video plays. From our results, we found that beta-band GFS values decreased during high emotional arousal, regardless of the type of emotional stimulus. Moreover, the emotional highlights estimated using the GFS waveforms coincided best with those found by the questionnaire surveys. These findings suggest that GFS might be applicable as a new index for tracking emotional arousal changes of a group of individuals during video watching, and is likely to be used to evaluate or edit movies, TV commercials, and other broadcast products.
Highlights
Understanding human emotional processes is an important research topic in neuroscience, since emotion plays a key role in the communications and interactions among people
Among various neuroimaging modalities, such as electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging that have been used to reveal the neural substrates of emotion (Peyk et al, 2008), EEG has been considered a most suitable tool to study the dynamics of emotion due to its excellent temporal resolution and reasonable cost (Millán et al, 2008)
The two-time points in each video clip at which the Global field synchronization (GFS) values dropped below the lower horizontal line (N1, N2, P1, and P2) matched well with the time points most frequently chosen as impressive or memorable by the participants in the second group
Summary
Understanding human emotional processes is an important research topic in neuroscience, since emotion plays a key role in the communications and interactions among people. Tracking Emotional Changes Using Electroencephalography and speech sounds (Black and Yacoob, 1997; Petrushin, 1999; Anderson and McOwan, 2006) These modalities have proven to be useful for evaluating and classifying emotional state, they are not applicable in nonverbal environments or in the absence of cameras. Since some of these signals exhibited relatively slow responses (e.g., heart rate variability index requires at least 1-min delay), the features extracted from them could not be effectively used to monitor immediate emotional changes. These signals are affected by changes in emotional state, and by other independent factors such as stress, physical fatigue, and alcohol intake. Decoding of emotional state from EEG has attracted increased attention because of the popularization of low-cost wearable EEG systems and their potential applications in affective braincomputer interfaces (aBCIs)
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