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

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...
Depth Perception and Spatial Vision01:15

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.

You might also read

Related Articles

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

Sort by
Same author

Activation of the hypothalamic-pituitary adrenal axis in response to a verbal fluency task and associations with task performance.

PloS one·2020
Same author

Evaluation of the socially evaluated cold-pressor group test (SECPT-G) in the general population.

PeerJ·2019
Same author

Top-down influence on bottom-up process: the familiarity effect modulates texture segmentation.

Vision research·2013
Same author

Spatial competition on the master-saliency map.

Frontiers in psychology·2013
Same author

Electrophysiological correlates of target eccentricity in texture segmentation.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology·2011
Same author

Texture segmentation: do the processing units on the saliency map increase with eccentricity?

Vision research·2010
Same journal

Comment on 'angle illusion on a picture's surface' by Hammad et al. (2008).

Spatial vision·2009
Same journal

Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

Spatial vision·2009
Same journal

Inhibition related impairments of coherent motion perception in the attention-induced motion blindness paradigm.

Spatial vision·2009
Same journal

Recognition units in reading: backward masking experiments.

Spatial vision·2009
Same journal

Spatial-temporal modeling of interactive image interpretation.

Spatial vision·2009
Same journal

Faster graphical models for point-pattern matching.

Spatial vision·2009
See all related articles

Related Experiment Video

Updated: Jun 19, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
03:31

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

Published on: December 15, 2023

Spatial distance between target and irrelevant patch modulates detection in a texture segmentation task.

Ursula Schade1, Cristina Meinecke

  • 1Institute of Psychology, University of Erlangen-Nürnberg, Kochstrasse 4, 91054 Erlangen, Germany. Ursula.Schade@psy.phil.uni-erlangen.de

Spatial Vision
|November 7, 2009
PubMed
Summary
This summary is machine-generated.

A distracting patch impaired target detection only at close distances. Detection performance improved with distance up to a critical point, suggesting interactions in visual processing.

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Related Experiment Videos

Last Updated: Jun 19, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
03:31

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

Published on: December 15, 2023

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Area of Science:

  • Visual perception
  • Cognitive psychology
  • Neuroscience

Background:

  • Texture segmentation relies on detecting target patches within visual scenes.
  • Task-irrelevant stimuli can influence performance in visual detection tasks.
  • Spatial relationships between stimuli are crucial for understanding visual processing.

Purpose of the Study:

  • To investigate how a task-irrelevant patch in a backward mask affects target detection performance.
  • To examine the influence of spatial distance between the target and the irrelevant patch.
  • To explore the interaction between visual signals as a function of their separation.

Main Methods:

  • Three texture segmentation experiments were conducted.
  • Participants detected a target patch under varying conditions of a backward mask.
  • The spatial distance between the target and a task-irrelevant patch was systematically manipulated.

Main Results:

  • Target detection was impaired by the irrelevant patch only at small spatial distances.
  • Detection performance increased linearly with increasing distance up to a critical threshold.
  • Beyond this critical distance, further increases in separation did not improve performance.

Conclusions:

  • Visual signals interact based on spatial proximity, impacting detection.
  • A critical distance exists, potentially related to receptive field sizes in visual cortex.
  • Findings support the biased competition account of visual attention and perception.