Mental Health Correlates of Neural Dynamics During Passive Media Consumption and Resting State: An EEG Study

This study investigates the alterations in brain activity during short video scrolling silently as well as different social media exposure compared to an eye-closed resting state using electroencephalogram (EEG) signals recorded from four electrodes. Various parameters were extracted and the frequency band dynamics were analyzed. Private Dataset of EEG signals is developed using MOBITA data acquisition system. EEG signals are recorded from four electrodes like Fp1, Fpz, Fp2 and Both female and male subjects were included in experiment. All participants were instructed to undergo through two conditions like social media as well as short video scrolling and eye-closed resting. Different frequency band power for each signal recorded from electrodes and phase lag Index (PLI) as well as phase difference distribution between electrodes from frontal region are extracted in two conditions. Next, machine-learning classifiers were applied to differentiate the effect of passive social media consumption over youth as well as aged people. Conventional model performance parameters are calculated and presented in a tabulated manner. Our study indicates a reduction in alpha power and connectivity during video exposure, suggesting heightened sensory processing and decreased default-mode network (DMN) activity. Phase Lag Index (PLI) and phase difference distribution revealed diminished synchrony. Machine learning based classification using these EEG features achieved up to 89.29% accuracy in distinguishing resting and media states. In summary, the existing findings provide insights into the neural correlates of passive content consumption.