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

You might also read

Related Articles

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

Sort by
Same author

A model-based approach to study ant energetics from trajectory data.

PNAS nexus·2026
Same author

Hydrodynamic entanglement in the abyss: Morphological adaptations of groups of <i>Euplectella aspergillum</i>.

PNAS nexus·2026
Same author

Evaluating OCR performance for assistive technology: effects of walking speed, camera placement, and camera type.

Disability and rehabilitation. Assistive technology·2026
Same author

Visual influence networks in walking crowds.

Journal of the Royal Society, Interface·2026
Same author

ROPE: a novel method for real-time phase estimation of complex biological rhythms.

Journal of the Royal Society, Interface·2026
Same author

Dynamic stabilization of a mechanical oscillator in the absence of any stable feature.

Nature communications·2026

Related Experiment Video

Updated: Apr 21, 2026

Using Touch-evoked Response and Locomotion Assays to Assess Muscle Performance and Function in Zebrafish
09:40

Using Touch-evoked Response and Locomotion Assays to Assess Muscle Performance and Function in Zebrafish

Published on: October 31, 2016

14.5K

Data-driven stochastic modelling of zebrafish locomotion.

Adam Zienkiewicz1, David A W Barton1, Maurizio Porfiri2

  • 1Department of Engineering Mathematics, University of Bristol, Bristol, UK.

Journal of Mathematical Biology
|November 1, 2014
PubMed
Summary

This study models zebrafish (Danio rerio) locomotion using data-driven stochastic differential equations. The framework captures individual fish movement, including dynamic speed regulation and responses to external constraints.

Keywords:
Computational biologyFish locomotionOrnstein–UhlenbeckStochastic modelsZebrafish

More Related Videos

Automated High-throughput Behavioral Analyses in Zebrafish Larvae
09:28

Automated High-throughput Behavioral Analyses in Zebrafish Larvae

Published on: July 4, 2013

17.3K
Zebrafish In Situ Spinal Cord Preparation for Electrophysiological Recordings from Spinal Sensory and Motor Neurons
08:24

Zebrafish In Situ Spinal Cord Preparation for Electrophysiological Recordings from Spinal Sensory and Motor Neurons

Published on: April 18, 2017

11.1K

Related Experiment Videos

Last Updated: Apr 21, 2026

Using Touch-evoked Response and Locomotion Assays to Assess Muscle Performance and Function in Zebrafish
09:40

Using Touch-evoked Response and Locomotion Assays to Assess Muscle Performance and Function in Zebrafish

Published on: October 31, 2016

14.5K
Automated High-throughput Behavioral Analyses in Zebrafish Larvae
09:28

Automated High-throughput Behavioral Analyses in Zebrafish Larvae

Published on: July 4, 2013

17.3K
Zebrafish In Situ Spinal Cord Preparation for Electrophysiological Recordings from Spinal Sensory and Motor Neurons
08:24

Zebrafish In Situ Spinal Cord Preparation for Electrophysiological Recordings from Spinal Sensory and Motor Neurons

Published on: April 18, 2017

11.1K

Area of Science:

  • * Computational Biology
  • * Animal Behavior
  • * Biophysics

Background:

  • * Understanding fish locomotion is crucial for ecological and behavioral studies.
  • * Previous models often lack detailed, data-driven representations of individual fish movement dynamics.
  • * Zebrafish (Danio rerio) are a key model organism for studying collective and individual behaviors.

Purpose of the Study:

  • * To develop a data-driven mathematical framework for modeling zebrafish locomotion.
  • * To incorporate dynamic speed regulation and responses to external constraints into fish movement models.
  • * To provide a quantitative tool for analyzing individual fish behavior in controlled environments.

Main Methods:

  • * Utilized automated visual tracking to capture individual zebrafish movement data.
  • * Developed a model using stochastic differential equations to represent fish as self-propelled particles.
  • * Calibrated model parameters using salient metrics derived from experimental data, including speed and angular speed.

Main Results:

  • * Successfully reproduced key characteristics of individual zebrafish locomotion.
  • * Integrated experimentally-derived processes for dynamic speed regulation into the model.
  • * Accounted for fish responses to external constraints within the mathematical framework.

Conclusions:

  • * The developed data-driven framework offers a robust method for simulating fish movement.
  • * This approach facilitates quantitative investigation of individual behavior under various experimental conditions.
  • * The model provides insights into the fundamental dynamics governing zebrafish locomotion.