Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Olfaction01:25

Olfaction

44.2K
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...
44.2K
Olfactory Receptors: Location and Structure01:03

Olfactory Receptors: Location and Structure

9.1K
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...
9.1K
Physiology of Smell and Olfactory Pathway01:20

Physiology of Smell and Olfactory Pathway

8.2K
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...
8.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Hidden Spirals Reveal the Neurocomputational Mechanisms of Traveling Waves in Human Memory.

bioRxiv : the preprint server for biology·2026
Same author

Multi-stable oscillations in cortical networks with two classes of inhibition.

PLoS computational biology·2026
Same author

Male and female mice scent mark during social communication regardless of sexual motivation or partner identity.

Cell reports·2026
Same author

Planar, spiral, and concentric traveling waves distinguish behavioral states in human memory.

Nature communications·2026
Same author

Maximum entropy model reveals frequent brain state switching in a multiversal brain function analysis in early psychoses.

bioRxiv : the preprint server for biology·2026
Same author

A discrete-time continuous-space neural model for shell patterns in mollusks.

Journal of theoretical biology·2025

Related Experiment Video

Updated: Jun 13, 2025

Author Spotlight: Understanding Processing of Olfactory and Spatial Information by Brain with Real-Time Behavioral Analysis
06:21

Author Spotlight: Understanding Processing of Olfactory and Spatial Information by Brain with Real-Time Behavioral Analysis

Published on: September 20, 2024

732

Simple olfactory navigation in air and water.

Bowei Ouyang1, Aaron C True2, John P Crimaldi2

  • 1Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, United States of America.

Journal of Theoretical Biology
|September 11, 2024
PubMed
Summary
This summary is machine-generated.

Two algorithms effectively locate odor sources by analyzing concentration differences and flow direction. Success rates exceed 90%, with optimized parameters sometimes leading to more exploratory paths.

Keywords:
Animal navigationComputational modelingKlinotaxisOlfactionTropotaxis

More Related Videos

Functional Evaluation of Olfactory Pathways in Living Xenopus Tadpoles
07:33

Functional Evaluation of Olfactory Pathways in Living Xenopus Tadpoles

Published on: December 11, 2018

6.8K
Visually Mediated Odor Tracking During Flight in Drosophila
08:50

Visually Mediated Odor Tracking During Flight in Drosophila

Published on: January 26, 2009

9.9K

Related Experiment Videos

Last Updated: Jun 13, 2025

Author Spotlight: Understanding Processing of Olfactory and Spatial Information by Brain with Real-Time Behavioral Analysis
06:21

Author Spotlight: Understanding Processing of Olfactory and Spatial Information by Brain with Real-Time Behavioral Analysis

Published on: September 20, 2024

732
Functional Evaluation of Olfactory Pathways in Living Xenopus Tadpoles
07:33

Functional Evaluation of Olfactory Pathways in Living Xenopus Tadpoles

Published on: December 11, 2018

6.8K
Visually Mediated Odor Tracking During Flight in Drosophila
08:50

Visually Mediated Odor Tracking During Flight in Drosophila

Published on: January 26, 2009

9.9K

Area of Science:

  • Computational Biology and Cheminformatics
  • Robotics and Autonomous Systems
  • Environmental Science and Engineering

Background:

  • Accurate odor source localization is crucial for applications ranging from environmental monitoring to search and rescue.
  • Existing methods often struggle with complex flow dynamics and varying odor landscapes.
  • Developing robust algorithms for odor-guided navigation remains a significant challenge.

Purpose of the Study:

  • To evaluate the efficacy of two novel algorithms for odor source localization.
  • To compare algorithm performance across diverse odor landscapes, including air and water plumes.
  • To identify optimal algorithm parameters for maximizing success rates and minimizing path lengths.

Main Methods:

  • Tested a bilateral ('stereo sampling') algorithm and a 'casting' algorithm using simulated odor plumes.
  • Employed image data from air plumes (three regimes) and water plumes as test environments.
  • Agents initiated at random locations and orientations, navigating until odor source detection or failure.

Main Results:

  • Achieved consistent success rates exceeding 90% in odor source localization.
  • Path lengths were approximately twice the initial distance in air and four times in water.
  • Optimizing for success often resulted in more exploratory search pathways.

Conclusions:

  • Both algorithms demonstrate high success rates for odor source localization in varied environments.
  • Odor direction information is vital for navigation in water and beneficial for air plumes.
  • Algorithm parameter tuning impacts both navigation efficiency and search strategy.