PT  - JOURNAL ARTICLE
AU  - Rehan M. Khan
AU  - Chung-Hay Luk
AU  - Adeen Flinker
AU  - Amit Aggarwal
AU  - Hadas Lapid
AU  - Rafi Haddad
AU  - Noam Sobel
TI  - Predicting Odor Pleasantness from Odorant Structure: Pleasantness as a Reflection of the Physical World
AID  - 10.1523/JNEUROSCI.1158-07.2007
DP  - 2007 Sep 12
TA  - The Journal of Neuroscience
PG  - 10015--10023
VI  - 27
IP  - 37
4099  - http://www.jneurosci.org/content/27/37/10015.short
4100  - http://www.jneurosci.org/content/27/37/10015.full
SO  - J. Neurosci.2007 Sep 12; 27
AB  - Although it is agreed that physicochemical features of molecules determine their perceived odor, the rules governing this relationship remain unknown. A significant obstacle to such understanding is the high dimensionality of features describing both percepts and molecules. We applied a statistical method to reduce dimensionality in both odor percepts and physicochemical descriptors for a large set of molecules. We found that the primary axis of perception was odor pleasantness, and critically, that the primary axis of physicochemical properties reflected the primary axis of olfactory perception. This allowed us to predict the pleasantness of novel molecules by their physicochemical properties alone. Olfactory perception is strongly shaped by experience and learning. However, our findings suggest that olfactory pleasantness is also partially innate, corresponding to a natural axis of maximal discriminability among biologically relevant molecules.