A central question in neuroscience is how the brain processes real-world sensory input. For decades most classical studies focus on carefully controlled artificial stimuli. More recently researchers started to investigate brain activity under more realistic conditions. The main challenge in this setting is the analysis of the complex signals obtained with modern neuroimaging methods in response to natural stimuli. Inter-subject correlations (ISCs) have become a popular paradigm to study brain activation under natural stimulation. The underlying assumption of this analysis is that features of natural stimuli that are perceived and processed by all subjects exposed to the same stimulus result in similar activation patterns across subjects. Higher degrees of realism in stimulation, for instance audiovisual stimulation is more realistic than auditory stimulation, is usually associated with higher ISC values. We can confirm these findings in experiments in which we present a movie stimulus with varying degrees of realism. Extending previous findings we highlight the importance of artifact removal when evaluating ISCs and show that the impact of realism in natural stimulation on ISCs is frequency-dependent. A major challenge associated with this type of analysis is that it can be difficult to attribute the correlation strength to the physiological process of interest. In this study, we demonstrate that ISCs of neural activation as measured by electroencephalogram (EEG) recordings are influenced significantly by non-neural artifacts such as occulograms. Our findings highlight the potential of inter-subject correlations as a biomarker for immersion: If more realistic stimuli consistently lead to higher inter-subject correlations, then inter-subject correlations can serve as a quantitative marker for how engaging audiovisual stimuli are perceived.Clinical relevance- Future research will evaluate if correlation levels among subjects, who are exposed to natural stimuli are affected by neurological diseases such as Alzheimers, Parkinsons, and Schizophrenia among others.