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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.
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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.
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Related Experiment Video

Updated: Dec 21, 2025

Testing for Odor Discrimination and Habituation in Mice

Testing for Odor Discrimination and Habituation in Mice

Published on: May 5, 2015

Habituation as a neural algorithm for online odor discrimination.

Yang Shen¹, Sanjoy Dasgupta², Saket Navlakha³

¹Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724.

Proceedings of the National Academy of Sciences of the United States of America

|May 21, 2020

Summary

This summary is machine-generated.

Habituation, a simple memory, filters redundant sensory information by suppressing neural activity. This process enhances odor discrimination and the detection of novel stimuli in complex environments.

Keywords:

background subtraction habituation odor discrimination systems neuroscience unsupervised algorithm

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Published on: March 22, 2018

Area of Science:

Neuroscience
Computational Biology
Sensory Systems

Background:

Habituation is a fundamental form of learning involving reduced response to repeated, non-threatening stimuli.
This neural process is crucial for focusing attention on salient environmental cues.

Purpose of the Study:

To derive a computational algorithm for habituation based on known neural circuits.
To investigate how this algorithm impacts sensory information processing, specifically in olfaction.

Main Methods:

Utilized the fruit fly olfactory system as a model.
Developed and analyzed a mathematical algorithm for habituation.
Conducted empirical validation of the algorithm's predictions.

Main Results:

The derived algorithm effectively filters redundant sensory input.
Demonstrated improved discrimination between similar odors against background noise.
Showcased enhanced detection of novel odor components within mixtures.

Conclusions:

An algorithmic framework for biological habituation provides insights into sensory perception.
Habituation mechanisms can optimize information processing in neural systems.
This approach may extend to understanding habituation in more complex neural architectures.