Olfactory Perception

Olfactory perception research aims to understand how humans perceive and process smells, bridging the gap between molecular structure and subjective experience. Current efforts focus on developing machine learning models, including deep learning architectures like graph convolutional networks and generative neural networks, to predict olfactory perception from molecular structures and even to generate novel fragrance molecules based on desired sensory profiles. These advancements hold significant promise for applications in fragrance design, cultural heritage studies (analyzing olfactory scenes in art), and a deeper understanding of the neural mechanisms underlying olfaction.