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

Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

8.6K
The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
8.6K

You might also read

Related Articles

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

Sort by
Same author

Laminar architecture of visual and auditory responses in the supplementary eye field of macaques.

Cerebral cortex (New York, N.Y. : 1991)·2026
Same author

Acute stress modulates early visual perception and decision-making speed in bees.

The Journal of experimental biology·2026
Same author

Temporal consistency of judgement biases in bumblebees.

Biology letters·2026
Same author

Testing Bottom-up Cuing Effects on Target Detection and Discrimination in Bumblebees.

Journal of insect behavior·2026
Same author

Multiple mechanisms of response suppression to self-induced sensation during pursuit eye movements.

Royal Society open science·2025
Same author

Prior cueing affects the saccadic response to targets in the praying mantis Sphodromantis lineola.

The Journal of experimental biology·2025

Related Experiment Video

Updated: Feb 28, 2026

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
08:13

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

Published on: December 25, 2017

8.7K

Invisible noise obscures visible signal in insect motion detection.

Ghaith Tarawneh1, Vivek Nityananda2, Ronny Rosner2

  • 1Institute of Neuroscience, Henry Wellcome Building for Neuroecology, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom. ghaith.tarawneh@ncl.ac.uk.

Scientific Reports
|June 16, 2017
PubMed
Summary

The motion energy model predicts motion detection differently in insects and mammals due to early visual processing variations. Insects can experience impaired motion detection from "invisible" noise, a phenomenon confirmed in praying mantises.

More Related Videos

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.8K
Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches
07:23

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Published on: August 4, 2014

23.9K

Related Experiment Videos

Last Updated: Feb 28, 2026

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
08:13

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

Published on: December 25, 2017

8.7K
Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.8K
Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches
07:23

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Published on: August 4, 2014

23.9K

Area of Science:

  • Neuroscience
  • Animal Behavior
  • Visual Processing

Background:

  • The motion energy model is widely accepted for explaining motion detection across diverse animal species.
  • Early visual processing differs significantly between mammals and insects.
  • These differences lead to divergent predictions from the motion energy model.

Purpose of the Study:

  • To investigate how variations in early visual processing impact motion detection predictions in mammals versus insects.
  • To test the model's prediction of motion detection impairment by "invisible" noise in insects.

Main Methods:

  • Comparative analysis of the motion energy model's predictions for insect and mammal visual systems.
  • Experimental validation using the optomotor response in praying mantises (Sphodromantis lineola).
  • Examination of spatial filtering characteristics (lowpass vs. bandpass) in early visual processing.

Main Results:

  • Insects exhibit spatially lowpass early filtering, predicting motion detection impairment by spatially filtered "invisible" noise.
  • This prediction was experimentally confirmed in praying mantises.
  • Mammals possess spatially bandpass early filtering, where such "invisible" noise effects are not observed, preserving the validity of linear systems techniques.

Conclusions:

  • Differences in early visual filtering fundamentally alter motion detection model predictions between insects and mammals.
  • "Invisible" noise can impair motion detection in insects, a counter-intuitive effect stemming from their visual system's properties.
  • Masking by invisible noise may be a generalizable phenomenon in neural circuits with specific nonlinearities.