Predicting Odor Pleasantness from Odorant Structure: Pleasantness as a Reflection of the Physical World

Abstract

Although it is agreed that physico-chemical 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 physico-chemical 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 physico-chemical properties reflected the primary axis of olfactory perception. This allowed us to predict the pleasantness of novel molecules by their physico-chemical 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 amongst biologically relevant molecules.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2009
Accession Number
ADA518390

Entities

People

  • Adeen Flinker
  • Amit Aggarwal
  • Chung-hay Luk
  • Hadas Lapid
  • Noam Sobel
  • Rafi Haddad
  • Rehan M. Khan

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Brain
  • Chemical Properties
  • Chemistry
  • Data Science
  • Data Sets
  • Databases
  • Dimensionality Reduction
  • Information Science
  • Intensity
  • Judgment
  • Magnetic Resonance
  • Organic Chemistry
  • Predictive Modeling
  • Psychology
  • Reaction Time
  • Test Sets
  • Two Dimensional

Readers

  • Nanocomposite Materials Science
  • Regression Analysis.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.