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

9.0K
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...
9.0K
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

7.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
7.1K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

8.7K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
8.7K
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

161
Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...
161
Significance Testing: Overview01:04

Significance Testing: Overview

10.2K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
10.2K
Unusual Results01:16

Unusual Results

3.0K
Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
Maximum unusual value =...
3.0K

You might also read

Related Articles

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

Sort by
Same author

Truth over falsehood: Experimental evidence on what persuades and spreads.

Journal of personality and social psychology·2025
Same author

Did he or didn't he? Mixed evidence for the continued influence of retracted misinformation on person impressions.

PloS one·2025
Same author

Validating a forced-choice method for eliciting quality-of-reasoning judgments.

Behavior research methods·2023
Same author

Evaluating the effectiveness of different perceptual training methods in a difficult visual discrimination task with ultrasound images.

Cognitive research: principles and implications·2023
Same author

The workload capacity of semantic search in convergent thinking.

Journal of experimental psychology. General·2021
Same author

Explainable models for forecasting the emergence of political instability.

PloS one·2021
Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026
Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026
Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026
Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026
Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026
Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026
See all related articles

Related Experiment Video

Updated: May 3, 2026

A Method for Investigating Change Blindness in Pigeons Columba Livia
06:14

A Method for Investigating Change Blindness in Pigeons Columba Livia

Published on: September 7, 2018

6.0K

Detecting unidentified changes.

Piers D L Howe1, Margaret E Webb1

  • 1School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia.

Plos One
|January 24, 2014
PubMed
Summary
This summary is machine-generated.

Visual change detection can occur without identifying or localizing the change. Observers may detect alterations by monitoring global scene properties, even in natural images.

More Related Videos

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
05:17

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

Published on: October 10, 2025

559
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

8.3K

Related Experiment Videos

Last Updated: May 3, 2026

A Method for Investigating Change Blindness in Pigeons Columba Livia
06:14

A Method for Investigating Change Blindness in Pigeons Columba Livia

Published on: September 7, 2018

6.0K
Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
05:17

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

Published on: October 10, 2025

559
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

8.3K

Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Visual Perception

Background:

  • Visual awareness theories suggest awareness extends beyond attended objects to include global scene properties like luminance and spatial frequencies.
  • Detecting changes in global properties might enable change detection without specific identification or localization of the altered object.
  • Previous studies on natural images yielded inconclusive results regarding change detection independent of identification or localization.

Purpose of the Study:

  • To investigate whether visual change detection can occur without the ability to identify or localize the change.
  • To provide further evidence for change detection independent of object identification and localization in natural images.
  • To explore the role of monitoring global scene properties in visual change detection.

Main Methods:

  • Utilized a novel analysis technique to examine visual change detection in natural images.
  • Presented participants with visual stimuli and assessed their ability to detect, identify, and localize changes.
  • Compared detection performance with identification and localization accuracy.

Main Results:

  • Demonstrated that changes in natural images can be reliably detected without concurrent identification or localization.
  • Results suggest that observers can detect alterations by monitoring global visual scene properties.
  • The novel analysis technique provided additional evidence supporting change detection independent of specific object-level awareness.

Conclusions:

  • Change detection in visual stimuli can occur without necessarily enabling the identification or localization of the specific change.
  • Monitoring global scene properties is a likely mechanism for detecting changes without detailed object awareness.
  • This finding has implications for understanding the scope of visual awareness and information processing.