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Olfaction

Olfaction

The sense of smell is achieved through the activities of the olfactory system. It starts when an airborne odorant enters the nasal cavity and reaches olfactory epithelium (OE). The OE is protected by a thin layer of mucus, which also serves the purpose of dissolving more complex compounds into simpler chemical odorants. The size of the OE and the density of sensory neurons varies among species; in humans, the OE is only about 9-10 cm2.
The olfactory receptors are embedded in the cilia of the...

Physiology of Smell and Olfactory Pathway

Physiology of Smell and Olfactory Pathway

Humans detect odors with the help of specialized cells located in the upper part of the nasal cavity, called olfactory receptor neurons (ORNs). ORNs possess hair-like structures called cilia, which are receptive to sensations from the inhaled air. When an odorant molecule binds to a specific receptor on the cell of the cilia, it leads to a series of events that ultimately cause the ORN to send electrical signals to the olfactory bulb in the brain through the olfactory nerves.
The olfactory...

Olfactory Receptors: Location and Structure

Olfactory Receptors: Location and Structure

The process of olfaction, also known as the sense of smell, is a sophisticated chemical response system. The specialized sensory neurons that facilitate this process, known as olfactory receptor neurons, are situated in an upper segment of the nasal cavity, known as the olfactory epithelium. Olfactory sensory neurons are bipolar, with their dendrites extending from the epithelium's apex into the mucus that lines the nasal cavity. Airborne molecules, when inhaled, traverse the olfactory...

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Related Experiment Video

Updated: Jul 31, 2025

Imaging Odor-Evoked Activities in the Mouse Olfactory Bulb using Optical Reflectance and Autofluorescence Signals

Imaging Odor-Evoked Activities in the Mouse Olfactory Bulb using Optical Reflectance and Autofluorescence Signals

Published on: October 31, 2011

Metabolic activity organizes olfactory representations.

Wesley W Qian^1,2, Jennifer N Wei², Benjamin Sanchez-Lengeling²

¹Osmo, Cambridge, United States.

|May 2, 2023

Summary

This summary is machine-generated.

Researchers discovered a computable molecular representation for odors, called the principal odor map (POM). This map predicts olfactory responses across species and reveals how metabolic processes shape our sense of smell.

Keywords:

D. melanogaster computational biology human machine learning metabolome mouse neuroscience olfaction psychophysics systems biology

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Area of Science:

Olfactory neuroscience
Computational biology
Cheminformatics

Background:

Sensory systems like hearing and vision are tuned to natural environmental statistics.
The natural statistics of odors and how olfactory systems utilize them remain less understood.
Previous models for human odor perception exist but lack broad applicability.

Purpose of the Study:

To determine the natural statistics of odors.
To find a computable molecular representation for odor perception.
To investigate how olfactory systems, across diverse organisms, exploit these statistics.

Main Methods:

Dissection of an accurate machine learning model for human odor perception.
Development of a computable odor representation at the molecular level (principal odor map [POM]).
Analysis of odorant co-occurrence, metabolic relationships, and metabolic reaction pathways within the POM framework.

Main Results:

A principal odor map (POM) was identified, accurately predicting odor-evoked responses across various terrestrial organisms.
Compounds with similar POM representations tend to co-occur in substances and are metabolically related.
Metabolic reaction sequences exhibit smooth trajectories in the POM, even with significant molecular structure changes.

Conclusions:

The principal odor map (POM) provides a universal molecular representation for odor perception.
Natural statistics of metabolism appear to significantly influence the brain's olfactory representations.
This work parallels how visual systems evolved around the statistics of light and shapes.