Food flavor is the primary determinant of consumer acceptance. However， traditional research relies heavily on static chemical analysis and manual sensory evaluation， which fails to capture the dynamic and complex nature of human olfactory and gustatory perception. This complexity often obscures how specific flavor profiles are processed in real-world scenarios， making it difficult to bridge the gap between a product's chemical composition and the consumer's actual experience. This challenge is further compounded by the lack of standardized stimulus control， as environmental factors and inconsistent delivery timing often lead to variable physiological reception. Such a disconnect between physical stimuli and subjective perception severely constrains the accuracy of flavor prediction and the efficiency of product development. To address these systemic limitations， a transition toward more integrated and technologically advanced research methodologies is essential. This review introduced a novel framework that utilized advanced olfactory presentation technology for real-time， precise control over stimulus parameters. To quantify the sensory experience， the framework integrated multimodal measurement techniques， including the monitoring of brain activity via EEG and fMRI， alongside physiological indicators such as respiration and electrodermal activity. By placing cross-scale artificial intelligence at its core， this approach facilitated a systematic cycle of precise stimulation， quantitative measurement， AI-driven modeling， and closed-loop optimization. Within this paradigm， artificial intelligence decoded real-time physiological feedback to dynamically regulate the concentration and timing of stimuli. This enabled the establishment of clear mapping relationships between chemical molecules， neural responses， and subjective perception， effectively bridging the gap between material foundations and actual experience. The establishment of this paradigm provided flavor science with interpretable research tools and drives the food industry's transformation from experience-based approaches toward data-driven precision flavor design.