Gastronomic gaze: decoding EEG-based discriminative patterns in four basic tastes with visual cues - Jaiswal, Arnav (Nanyang Technological University, 2024)
Does viewing food pictures invoke any taste-related response? Applications of the answer to this question lie in various fields such as neuromarketing. The intersection between neurotechnology and gastronomy, my research investigates using multimodal neural, physiological, and physical sensors to decode and classify taste perceptions with or without visual stimuli. This study aims to build a multi- stage experiment design with cognitive, smell, and taste profiling to evaluate how gastronomic visual stimuli are presented concurrently while administering different taste stimuli. Our experiment is trying to answer how EEG combined with other sensors improves the classification accuracy of the five basic tastes: sweet, sour, salty, bitter, and neutral in the presence of food or non-food images. One of our research hypotheses is "Does the congruency of the visual and taste stimuli increase decoding and classification performance among four tastes and control (neutral)? From this regard, I designed an experiment encompassing the above conditions and collected multimodal data in a controlled lab setting using standard taste testing kits with nine healthy subjects. From collected data, I analyze and evaluate both data-driven deep learning approaches and eXplainable Artificial Intelligence (XAI) with causal machine learning to better understand the intricate relationship and interplays between tastes, cognition, and behaviors. I believe this research investigation will reveal promising results in EEG taste decoding while XAI gives meaningful insights about discriminative EEG among tastes.