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

Statistical Significance01:50

Statistical Significance

21.3K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
21.3K
Probability in Statistics01:14

Probability in Statistics

23.3K
Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...
23.3K
Introduction to Statistics01:17

Introduction to Statistics

63.4K
The science of statistics involves collecting, analyzing, interpreting, and presenting data. The method of collecting, organizing, and summarizing data is called descriptive statistics. The systematic method of drawing inferences from the sample data and predicting unknown characteristics of a population is called inferential statistics.
In statistics, the collection of individuals or objects under study is called population. The idea of sampling is to select a portion of the larger population...
63.4K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

16.5K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
16.5K
Identifying Statistically Significant Differences: The F-Test01:14

Identifying Statistically Significant Differences: The F-Test

3.7K
The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...
3.7K
Introduction to Nonparametric Statistics01:28

Introduction to Nonparametric Statistics

1.4K
Nonparametric statistics offer a powerful alternative to traditional parametric methods, useful when assumptions about the population distribution cannot be made. Unlike parametric tests, which require data to follow a specific distribution with well-defined parameters (such as the mean and standard deviation), nonparametric tests do not require such constraints. This makes them particularly valuable when dealing with small sample sizes, skewed data, or ordinal and categorical variables.
One of...
1.4K

You might also read

Related Articles

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

Sort by
Same author

Combined conceptual and perceptual control of visual attention in search for real-world objects.

Attention, perception & psychophysics·2025
Same author

Signal suppression makes search less effortful.

Cognitive, affective & behavioral neuroscience·2025
Same author

Assessing the effectiveness of spatial PCA on SVM-based decoding of EEG data.

NeuroImage·2024
Same author

Using multivariate pattern analysis to increase effect sizes for event-related potential analyses.

Psychophysiology·2024
Same author

Using Multivariate Pattern Analysis to Increase Effect Sizes for Event-Related Potential Analyses.

bioRxiv : the preprint server for biology·2023
Same author

The Distractor Positivity Component and the Inhibition of Distracting Stimuli.

Journal of cognitive neuroscience·2023
Same journal

Human thermal sensitivity drifts at extreme temperatures.

Journal of experimental psychology. Human perception and performance·2026
Same journal

Dynamic competition between selective attention and spatial prediction during visual search.

Journal of experimental psychology. Human perception and performance·2026
Same journal

Encapsulation of the visual perception of social events from semantic priming.

Journal of experimental psychology. Human perception and performance·2026
Same journal

Biasmapping: Idiosyncratic covert search in the vicinity of fixation.

Journal of experimental psychology. Human perception and performance·2026
Same journal

What are you still waiting for? Fricative recognition shows encapsulated processing and is partially predicted by secondary cue reliance.

Journal of experimental psychology. Human perception and performance·2026
Same journal

Eye movements reveal that drivers can predict the location of hazards in dynamic road scenes but gaze and awareness are dissociable.

Journal of experimental psychology. Human perception and performance·2026
See all related articles

Related Experiment Video

Updated: Jan 28, 2026

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

8.2K

Feature-based statistical regularities of distractors modulate attentional capture.

Brad T Stilwell1, Brett Bahle1, Shaun P Vecera1

  • 1Department of Psychological and Brain Sciences, University of Iowa.

Journal of Experimental Psychology. Human Perception and Performance
|February 26, 2019
PubMed
Summary
This summary is machine-generated.

Learning to ignore distracting visual information improves search efficiency. This study shows that the visual system can learn to reduce attentional capture by both location and feature regularities of distractors.

More Related Videos

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

9.5K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.3K

Related Experiment Videos

Last Updated: Jan 28, 2026

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

8.2K
Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
09:37

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

9.5K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.3K

Area of Science:

  • Cognitive Psychology
  • Visual Perception
  • Neuroscience

Background:

  • Efficient visual search requires suppressing salient, distracting information.
  • Environmental regularities, such as frequent distractor locations, can reduce attentional capture.
  • Previous research demonstrated location-based regularities reduce attentional capture.

Purpose of the Study:

  • To investigate whether feature-based regularities, similar to location-based ones, can also reduce attentional capture.
  • To determine if the visual attentional system utilizes feature regularities to minimize distraction.
  • To explore the interplay between location and feature information in attentional capture.

Main Methods:

  • Four experiments were conducted using visual search tasks.
  • Participants searched for a shape singleton target among homogeneous color distractors.
  • Task-irrelevant color singleton distractors were presented, with varying frequencies and locations.

Main Results:

  • Replicated previous findings: frequent distractor locations captured attention less.
  • Demonstrated that frequently presented distractor colors also attenuated attentional capture.
  • Observed reliable attentional capture reduction based on color feature regularities, even with strong location cues.

Conclusions:

  • Attentional capture is reduced by both location-based and feature-based regularities.
  • The visual attentional system is adaptable and utilizes environmental regularities to enhance search efficiency.
  • Findings suggest a flexible mechanism for attentional control in response to predictable distractor characteristics.