# Predicting computations necessary for the decoding of odor mixtures by the olfactory system

> **NIH NIH SC2** · NORTH CAROLINA AGRI & TECH ST UNIV · 2021 · $144,000

## Abstract

Our olfactory system processes complex odor mixtures, drawn from a very high
dimensional space of over 10,000 possible odorants, using a limited set of (~100-1000)
olfactory receptors. While a considerable amount of work has done to understand the
odors are encoded by the olfactory receptors, the inverse problem: “How does the
olfactory system obtain odor information from receptor response?” is unclear. This
project aims to identify the computations that are necessary for the decoding odor
information from receptor responses. We will develop decoding algorithms and
mechanistic neural network models for decoding odor information from receptor
responses. We will study the performance of these algorithms and mechanistic models
and compare their predictions to the structure of the olfactory system and available data
on the performance of organisms in olfactory behavioral tasks. Through such
comparisons, we will identify the specific computations that are necessary for decoding
of natural odors. This would be achieved through the following aims. Aim 1: Develop
algorithms for decoding odor information from receptor responses and compare their
performance to behavioral data. Aim 2: Develop biophysical neural network models the
olfactory system and compare it to odor decoding algorithm to predict role of olfactory circuits.

## Key facts

- **NIH application ID:** 10170060
- **Project number:** 1SC2GM140945-01
- **Recipient organization:** NORTH CAROLINA AGRI & TECH ST UNIV
- **Principal Investigator:** Vijay Singh
- **Activity code:** SC2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $144,000
- **Award type:** 1
- **Project period:** 2021-05-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10170060

## Citation

> US National Institutes of Health, RePORTER application 10170060, Predicting computations necessary for the decoding of odor mixtures by the olfactory system (1SC2GM140945-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10170060. Licensed CC0.

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