# The Peripheral Representation of Odor Space

> **NIH NIH U19** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2020 · $739,684

## Abstract

Summary (Project 1: The peripheral representation of odor space)
Progress towards an understanding of olfactory coding has been hampered by long-standing hurdles created by
the nature of the stimulus and the complexity of the underlying sensory biology. At the same time, a description
of olfactory coding in mammals would provide a unique window into how multidimensional stimuli are
represented by the mammalian brain. Olfactory systems use large families of odorant receptors to detect a vast
number of chemical stimuli. An important challenge that must be overcome to better understand olfaction is to
establish a comprehensive description of what features of olfactory stimuli are represented by the system. Doing
so requires that we overcome previously insurmountable technical challenges in identifying the stimulus
specificity of a large number of receptors to a large number of odorants, and that we generate a theoretical
framework for quantifying and exploring the multidimensional “space” of odors and receptors. Here, we propose
an interdisciplinary effort to comprehensively characterize the odorant response properties of a large number of
odorant receptors in vivo, and to use this information to explicitly and rigorously test novel models of odor coding.
This project exploits the one-to-one correspondence between odorant receptors and glomeruli in the olfactory
bulb of mice. Aim 1 will characterize the sensitivities of a large number of receptors (glomeruli) in awake, intact
animals using functional imaging. Aim 2 will map these glomerular responses to specific receptors using
emerging spatial transcriptomics methods. Aim 3 will use a powerful genomics-based assay to identify the
highest affinity receptors for a large set of individual odors. Aim 4 will test a novel theoretical framework for
understanding how odor features are represented. This large-scale in vivo multidisciplinary approach will provide
long-sought data and analytical tools to rigorously explore potential models of odor coding.

## Key facts

- **NIH application ID:** 10001611
- **Project number:** 5U19NS112953-02
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Thomas Bozza
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $739,684
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10001611

## Citation

> US National Institutes of Health, RePORTER application 10001611, The Peripheral Representation of Odor Space (5U19NS112953-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10001611. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*