Automated Stimulus Delivery for Taste-Based Neuroimaging in Sensory and Consumer Neuroscience

In consumer neuroscience, taste-based studies are typically constrained by manual stimulus delivery, which establishes movement artifacts and timing inconsistencies that ultimately impede data quality. These limitations are primarily relevant in research where physiological markers and sensory responses should be recorded with high accuracy. In this paper, we reveal a methodological finding: a feeding system developed to deliver taste stimuli in a regulated, automated, and hands-free manner. The system is incorporated with functional near-infrared spectroscopy (fNIRS), electrodermal activity (EDA), and electromyography (EMG) recordings. Aimed at improving integration between neurophysiological recording and stimulus presentation, the feeding system is designed to work seamlessly with PsychoPy and Transistor-Transistor-Logic (TTL) trigger systems. Preliminary validation of the system is in progress in a study that compares sensory and physiological responses to plant-based meat and chicken meat (puree) under different priming conditions. This method attempts to minimize signal noise, strengthen ecological validity, and reinforce more naturalistic paradigms in taste-based neuromarketing, sensory research, and consumer neuroscience.