Dataset on Emotion with Naturalistic Stimuli (DENS) on Indian Samples

Abstract

Emotions are constructed and emerge through the dynamic interaction of multiple components. It is difficult to capture the dynamics using static or artificial stimuli. Hence, there is a need for an experiment paradigm using ecologically valid film stimuli. The data set described in this work results from an attempt to capture felt emotional experience at a particular point in time using physiological measures like EEG, ECG and EMG as well as self-reported scales. Sixteen emotional film stimuli were used from the film stimuli dataset validated in the Indian population. Participants self-reported the felt emotional category. Both the raw and pre-processed data are provided along with the pre-processing pipeline. The paradigm we have adopted is new which we have termed as Emotional Event Marker Paradigm (EEMP). Hence, the dataset has unique information about temporal markers of emotional experiences while watching the film stimuli, which is not available with any data to date. It is the first EEG data with emotional film stimuli on the Indian population. This data can be utilized to study dynamic activation and connectivity in a whole-brain source localization study, understand the mutual interactions between the central and autonomic nervous system, understand temporal hierarchy using multi-resolution tools, and perform machine learning-based classification and complex networks analysis associated with emotions.