Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Gestalt Principles of Perception

Gestalt Principles of Perception

Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...

Visual System

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

Perceptual Constancy

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...

Depth Perception and Spatial Vision

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.

Collisions in Multiple Dimensions: Problem Solving

Collisions in Multiple Dimensions: Problem Solving

In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...

You might also read

Related Articles

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

Sort by

Same authorSame Topic

Distracted by Previous Experience: Integrating Selection History, Current Task Demands and Saliency in an Algorithmic Model.

Computational brain & behavior·2026

Same author

Emotional modulation of statistical learning in visual search.

Frontiers in cognition·2026

Same author

Stage-specific priming of pop-out effects in the target-feature memory encoding and retrieval.

Acta psychologica·2026

Same author

Duration reproduction under memory pressure: Modeling the roles of visual memory set size in duration encoding and reproduction.

Cognition·2026

Same author

Distinct hippocampus codes for contextual cueing: learning contexts and their predictive associations with targets in visual search.

NeuroImage·2025

Same author

Effort expectation and strategic cue use in visual search.

Cognitive, affective & behavioral neuroscience·2025

Search research articles

Related Experiment Video

Updated: Jun 22, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

Selecting and ignoring salient objects within and across dimensions in visual search.

Anna Schubö¹, Hermann J Müller

¹Department of Psychology, Ludwig Maximilian University Munich, Leopoldstrasse 13, D-80802 Munich, Germany. anna.schuboe@lmu.de

|June 9, 2009

Summary

Visual attention selects information based on salience or goals. This study shows top-down control strongly influences salience-based selection, filtering irrelevant information more effectively when based on dimensions rather than specific features.

More Related Videos

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

Related Experiment Videos

Last Updated: Jun 22, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

Area of Science:

Cognitive Neuroscience
Visual Perception
Attention Studies

Background:

Visual attention utilizes salience and behavioral goals for information selection.
The role of top-down control in modulating salience-based selection remains debated.
Understanding visual selection mechanisms is crucial for cognitive science.

Purpose of the Study:

To investigate if the visual system filters salient but irrelevant information.
To determine the influence of visual system organization on attentional selection.
To compare the effects of dimension-based versus feature-based search on ERPs.

Main Methods:

Utilized event-related brain potentials (ERPs) to compare object processing under different task relevance conditions.
Employed dimension-based search (Experiment 1) and feature-based search (Experiment 2) paradigms.
Monitored observer responses to target and non-target singletons defined by specific visual dimensions.

Main Results:

Dimension-based search showed enhanced posterior N2 and P3 for targets, with no significant ERPs for irrelevant non-targets.
N2pc results indicated task-modulated attentional allocation in dimension-based search.
Feature-based search revealed ERP enhancements for irrelevant non-targets in N2, N2pc, and P3 ranges.

Conclusions:

Top-down control exerts a strong influence on singleton selection, particularly when operating on visual dimensions.
The visual system demonstrates more effective filtering of salient, irrelevant information when selection is dimension-based.
Findings suggest attentional selection mechanisms differ significantly between dimension-based and feature-based processing.