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

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.

You might also read

Related Articles

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

Sort by

Same author

Behavioral differences between humans and machines arise early in visual processing.

Journal of vision·2026

Same author

Bayesian Dynamical Modeling of Fixational Eye Movements.

Biological cybernetics·2025

Same author

Toward Dynamical Modeling of Infants' Looking Times.

Wiley interdisciplinary reviews. Cognitive science·2025

Same author

Distinctive pupil and microsaccade-rate signatures in self-recognition.

Journal of vision·2025

Same author

Estimating the contribution of early and late noise in vision from psychophysical data.

Journal of vision·2025

Same author

Plaid masking explained with input-dependent dendritic nonlinearities.

Scientific reports·2024

Search research articles

Related Experiment Video

Updated: Apr 18, 2026

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

Spatial statistics and attentional dynamics in scene viewing.

Ralf Engbert¹, Hans A Trukenbrod¹, Simon Barthelmé²

¹University of Potsdam, Germany Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.

Journal of Vision

|January 16, 2015

Summary

This study introduces a new dynamical model for visual attention that predicts human gaze patterns, including spatial clustering, by incorporating foveated saliency information and a leaky memory process for re-inspection.

Keywords:

attention eye movements modeling saccades scene perception spatial statistics

More Related Videos

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

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

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

Published on: July 5, 2015

Related Experiment Videos

Last Updated: Apr 18, 2026

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

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

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

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

Published on: July 5, 2015

Area of Science:

Computational Neuroscience
Cognitive Science
Visual Perception

Background:

Human visual acuity is concentrated at the center of gaze, making gaze selection a rapid decision-making process.
Existing saliency map models predict average human fixation points but miss individual scanpath structure.
Scanpaths exhibit statistical structure, including spatial clustering, beyond simple gaze position distributions.

Purpose of the Study:

To develop a dynamical model of saccadic selection that accurately predicts both gaze position distributions and spatial clustering in individual scanpaths.
To incorporate biologically-inspired mechanisms of foveated access to saliency information and leaky memory for region re-inspection.
To link neural dynamics of attention to observable behavioral gaze data through a theoretical framework.

Main Methods:

Development of a dynamical model of saccadic selection.
Incorporation of activation dynamics with spatially-limited (foveated) saliency access.
Inclusion of a leaky memory process for controlling target region re-inspection.

Main Results:

The model accurately predicts the distribution of gaze positions.
The model successfully predicts spatial clustering along individual scanpaths.
The framework provides a novel approach to modeling context-dependent decision-making in visual attention.

Conclusions:

The developed dynamical model offers a more comprehensive explanation of human visual behavior than traditional saliency maps.
Foveated access to saliency and leaky memory are crucial components for modeling detailed scanpath dynamics.
This work bridges neural dynamics of attention with behavioral gaze data, advancing our understanding of visual decision-making.