# Biophysical models of human olfactory intensity perception

> **NIH NIH F32** · MONELL CHEMICAL SENSES CENTER · 2022 · $67,174

## Abstract

PROJECT SUMMARY/ABSTRACT
We can measure the brightness of a color and the loudness of a sound because we have related these
perceptual properties to physical properties. This has not been done for olfaction. Knowing the basic unit of
intensity is essential to understand other aspects of a sense. For instance, just as color shifts with brightness,
the smell of an odor is relative to its intensity. In fact, most naturally occurring odors are not one molecule, but
mixtures of many molecules at different intensities. At the olfactory receptor level, we know that one odorant
may inhibit another leading to a change in each other’s strength. Knowing how and what interactions take
place in an odor mixture has clinical relevance. If we understand interactions in odor mixtures, we could
suppress unappetizing odorants in medicines that lead to lack of compliance as well as increase palatable
odorants in individuals with partial loss (e.g. elderly). Furthermore, knowing mixture intensity will supplement
fields trying to accurately measure odors (environmental regulation) or recreate them (food science). In this
proposal, I will collect high-quality, public data sets linking molecular structure to perceived intensity and build
open-access tools to provide practical, accessible predictions to advance the scientific field.

## Key facts

- **NIH application ID:** 10465391
- **Project number:** 1F32DC020380-01
- **Recipient organization:** MONELL CHEMICAL SENSES CENTER
- **Principal Investigator:** Robert Pellegrino
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $67,174
- **Award type:** 1
- **Project period:** 2022-03-15 → 2024-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10465391

## Citation

> US National Institutes of Health, RePORTER application 10465391, Biophysical models of human olfactory intensity perception (1F32DC020380-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10465391. Licensed CC0.

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