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

Uncertainty: Overview00:59

Uncertainty: Overview

523
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
523
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

73.4K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
73.4K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

652
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
652
Random Error01:04

Random Error

830
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
830
Random and Systematic Errors01:20

Random and Systematic Errors

10.8K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
10.8K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

83
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
83

You might also read

Related Articles

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

Sort by
Same author

A Physics-Guided Neural Network Framework for Prediction and Control of Spring-Mass Running.

Bioinspiration & biomimetics·2026
Same author

Flow impairs multisensory tracking and increases active sensing in weakly electric fish.

The Journal of experimental biology·2026
Same author

Flow impairs multisensory tracking and increases active sensing in weakly electric fish.

The Journal of experimental biology·2025
Same author

On the analysis and control of a bipedal legged locomotion model via partial feedback linearization.

Bioinspiration & biomimetics·2024
Same author

Design and verification of a parallel elastic robotic leg.

Bioinspiration & biomimetics·2024
Same author

Stochastic stability analysis of legged locomotion using unscented transformation.

Bioinspiration & biomimetics·2023
Same journal

A bio-inspired, soft-bodied jumper.

Bioinspiration & biomimetics·2026
Same journal

Structural and Functional Characteristics of the Exoskeletal Architecture of the Cuttlebone.

Bioinspiration & biomimetics·2026
Same journal

Design, Kinematic Modeling and Aerodynamic Performance Evaluation of a Beetle-Inspired Folding Wing with High Folding Ratio.

Bioinspiration & biomimetics·2026
Same journal

Proprioceptive Feedback Control Improves Peristaltic Turning in Confined Environments.

Bioinspiration & biomimetics·2026
Same journal

Design of an Inchworm-Inspired Crawling Robot Based on Dielectric Elastomers.

Bioinspiration & biomimetics·2026
Same journal

Landing-Induced Viscoelastic Changes in an Anthropomimetic Foot Joint Structure are Modulated by Foot Structure and Posture.

Bioinspiration & biomimetics·2026
See all related articles

Related Experiment Video

Updated: Jun 7, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.3K

Predictive uncertainty in state-estimation drives active sensing.

Osman Kaan Karagoz1,2, Aysegul Kilic1, Emin Yusuf Aydin3

  • 1Electrical and Electronics Engineering, Middle East Technical University, 06800 Ankara, Turkey.

Bioinspiration & Biomimetics
|November 21, 2024
PubMed
Summary
This summary is machine-generated.

Weakly electric fish use active sensing movements, like whole-body oscillations, to improve environmental perception. This study reveals closed-loop control mechanisms are key to active sensing and state estimation in fish behavior.

Keywords:
active sensingsensorimotor controlstate estimationweakly electric fish

More Related Videos

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K
Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.7K

Related Experiment Videos

Last Updated: Jun 7, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.3K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K
Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.7K

Area of Science:

  • Neuroscience
  • Animal Behavior
  • Biophysics

Background:

  • Animals actively modify sensory signals for enhanced perception.
  • Mechanisms driving active sensing movements remain largely unknown.
  • Weakly electric fish, Eigenmannia virescens, exhibit refuge tracking behavior.

Purpose of the Study:

  • Investigate the role of active sensing movements in Eigenmannia virescens refuge tracking.
  • Elucidate the underlying mechanisms of stereotyped whole-body oscillations during sensory degradation.
  • Examine how active sensing impacts task performance in state estimation.

Main Methods:

  • Developed a closed-loop feedback control model for refuge tracking.
  • Simulated fish trajectories using the developed model.
  • Compared model predictions with actual fish behavior and existing models.

Main Results:

  • Active sensing movements in Eigenmannia virescens may minimize predictive uncertainty in state estimation.
  • The closed-loop model generated simulated trajectories statistically indistinguishable from real fish.
  • Open-loop and stochastic resonance models failed to replicate observed behavior.

Conclusions:

  • Closed-loop control is significant in active sensing behavior.
  • Active sensing dynamically modulates sensory information for improved perception.
  • Findings offer new insights into the neural and behavioral mechanisms of sensory processing.