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

Modeling and Similitude

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

Impression Management Techniques I: Managing Appearances

Impression Management Techniques I: Managing Appearances

Appearance is a multidimensional aspect of self-presentation that encompasses observable attributes such as clothing, grooming, speech, and nonverbal behavior. These elements are often strategically managed to align with socially constructed expectations in different settings. For instance, individuals tailor their appearance during job interviews, social gatherings, or athletic events to meet the perceived norms of those environments.Contextual Adaptation and Social SignalsThe research...

Modeling in Therapy

Modeling in Therapy

Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

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.

Steps in the Modeling Process

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...

You might also read

Related Articles

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

Sort by

Same author

Effects of color-enhancing filters on color salience in normal trichromats.

Vision research·2026

Same author

Effects of color-enhancing filters on color salience in normal trichromats.

bioRxiv : the preprint server for biology·2025

Same author

Warm/cool judgments as a function of hue, value, and chroma.

Journal of the Optical Society of America. A, Optics, image science, and vision·2025

Same author

Directed attention influences optimality of top-down and bottom-up multi-modal perceptual integration.

Scientific reports·2025

Same author

An equivalent illuminant analysis of lightness constancy with physical objects and in virtual reality.

Behavior research methods·2025

Same author

Dissecting Bayes: Using influence measures to test normative use of probability density information derived from a sample.

PLoS computational biology·2024

Same journal

Planning, Coordination, and Communication: The Posterior Parietal Cortex in Eye-Hand Control.

Annual review of vision science·2026

Same journal

Multiphoton Excitation in Retinal Imaging and Functional Measurements.

Annual review of vision science·2026

Same journal

Visual Perception of Intuitive Physics and Its Computational Foundations.

Annual review of vision science·2026

Same journal

Diversity and Feature Selectivity of Primate Retinal Ganglion Cells.

Annual review of vision science·2026

Same journal

Predictive Foveal Processing in Active Vision.

Annual review of vision science·2026

Same journal

The Legacy of Perley G. Nutting Jr.: The Past and the Present of Chromatic Discrimination.

Annual review of vision science·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 21, 2025

Visualizing Visual Adaptation

Visualizing Visual Adaptation

Published on: April 24, 2017

Measuring and Modeling Visual Appearance.

Laurence T Maloney¹, Kenneth Knoblauch^2,3

¹Department of Psychology, New York University, New York, New York 10003, USA;

Annual Review of Vision Science

|May 19, 2020

Summary

This summary is machine-generated.

This study introduces two models for suprathreshold visual judgments, maximum likelihood difference scaling and conjoint measurement. These models help understand visual perception beyond simple discrimination tasks.

Keywords:

MLCM MLDS diagnostics maximum likelihood conjoint measurement maximum likelihood difference scaling proximity scaling suprathreshold

More Related Videos

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

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

Related Experiment Videos

Last Updated: Dec 21, 2025

Visualizing Visual Adaptation

Visualizing Visual Adaptation

Published on: April 24, 2017

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

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

Area of Science:

Visual perception
Psychophysics
Computational neuroscience

Background:

Extensive research exists on models for visual discrimination tasks.
Non-threshold visual judgments, like magnitude estimation, are crucial for understanding appearance.
These judgments bridge the gap between threshold detection and subjective visual experience.

Purpose of the Study:

To present and discuss two models for suprathreshold visual judgments.
To highlight the utility of these models in visual perception research.
To review recent applications of these psychophysical techniques.

Main Methods:

Description of maximum likelihood difference scaling.
Explanation of maximum likelihood conjoint measurement.
Review of literature employing these scaling methods.

Main Results:

These models provide a quantitative framework for analyzing suprathreshold visual judgments.
They allow for the separation of different sources of perceptual variation.
Recent studies demonstrate their effectiveness in diverse visual domains.

Conclusions:

Maximum likelihood difference scaling and conjoint measurement are valuable tools for studying visual perception.
These methods advance our understanding of how the visual system processes stimulus magnitudes.
Further research can leverage these techniques to explore complex visual phenomena.