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

Difference from Background: Limit of Detection

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 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.

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...

You might also read

Related Articles

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

Sort by

Same author

Partial gastrectomy for simple ulcer; a review of the end-results of 132 cases, with a criticism of the Polya operation.

The British journal of surgery·2010

Same author

A cross-sectional study of psychological morbidity in patients with acne, psoriasis and atopic dermatitis in specialist dermatology and general practices.

Journal of the European Academy of Dermatology and Venereology : JEADV·2008

Same author

Mondor's disease of the breast: sonographic and mammographic findings.

AJR. American journal of roentgenology·2001

Same author

Allergic contact dermatitis due to benzalkonium chloride in plaster of Paris.

The Australasian journal of dermatology·2001

Same author

Society of Breast Imaging residency and fellowship training curriculum.

Radiologic clinics of North America·2000

Same author

Transducer model produces facilitation from opposite-sign flanks.

Vision research·1999

Search research articles

Related Experiment Video

Updated: Jul 14, 2026

Cross-Modal Multivariate Pattern Analysis

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

Visual detection of spatial contrast patterns: evaluation of five simple models.

¹NASA Ames Research Center, Moffett Field, CA 94035, USA. abwatson@mail.arc.nasa.gov

|September 20, 2002

Summary

The Gabor Channels model best fits spatial vision data from twelve labs. Simpler models also performed well, suggesting a potential standard observer for spatial vision research.

Keywords:

NASA Center ARC NASA Discipline Space Human Factors

More Related Videos

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

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

Published on: January 23, 2017

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Published on: May 2, 2019

Related Experiment Videos

Last Updated: Jul 14, 2026

Cross-Modal Multivariate Pattern Analysis

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

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

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

Published on: January 23, 2017

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Published on: May 2, 2019

Area of Science:

Visual perception
Computational neuroscience
Psychophysics

Background:

The ModelFest Phase One dataset comprises luminance contrast thresholds for 43 spatial patterns.
Data were gathered by 12 laboratories to create a shared resource for spatial vision model testing.

Purpose of the Study:

To evaluate the performance of five different models in fitting the ModelFest dataset.
To assess the potential for a standard observer in spatial vision.

Main Methods:

Fitting five distinct models (Peak Contrast, Contrast Energy, Generalized Energy, Gabor Channels, Discrete Cosine Transform) to the ModelFest data.
Analyzing the goodness-of-fit for each model.

Main Results:

The Gabor Channels model demonstrated the best fit to the experimental data.
Simpler models, excluding Peak Contrast, also yielded strong fits.
Identified regularities in individual observer data.

Conclusions:

The Gabor Channels model is a strong candidate for explaining spatial vision.
Simpler models offer valuable insights into visual processing.
The data support the development of a standard observer for spatial vision.