2. Predictive Hedonics

Understanding, prediction, and modulation of the peripheral chemosensory reception and coding mechanisms to enable healthy food choices and development of next-generation human-machine interfaces and intelligent chemosensor systems with human-like performance.

What determines our sensory judgment of food? Will it become possible to predict whether the consumer likes or dislikes a food product simply from the ingredients used and the process conditions applied? To answer this question, the scientists of the Leibniz-LSB@TUM study the biomolecular mechanisms underlying human chemosensory perception, which is primarily defined by our chemical senses of smell and taste as well as by trigeminal stimulation. Their research will help us to understand how the sensory effector systems in food interact with the peripheral chemoreceptors in the mouth and nose and by means of which coding mechanisms chemosensory stimulation is translated into neuronal activity patterns. Based on their insights and by recruiting high-performance analytical techniques, the scientists aim to deduce how the hedonic evaluation of food products can be predicted from the molecular signature of their ingredients. The results will help to optimize food production and processing conditions targeting the development of more healthy and tasty food products. The scientists also want to develop intelligent human machine interfaces for microsystems technology and high-performance sensors. Such technologies will allow engineers to give technical systems like robots the ability to recognize complex odors with human-like performance.

  • Elucidating and modulating the principles underlying the translation of the combinatorial chemosensory effector systems of food into human perception and developing strategies driving a behavioral change in food choice.
  • Understanding and predicting the role of single nucleotide polymorphisms and epigenetics in human chemosensory perception , development of food preferences, and decision making.
  • New knowledge creation for natural next-generation flavor modifying systems.
  • Automated monitoring of chemosensory effector systems and prediction of human sensory perception.
  • Development of high-performance chemosensory arrays and advanced human-machine interfaces.