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

Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...
Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position with respect to time...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the drone...
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
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

Receptive-field sizes during remapping and uniform transsaccadic updating across the visual space.

bioRxiv : the preprint server for biology·2026
Same author

Desmoplastic Small Round Cell Tumor of the Ovary: A Case Report With Atypical Morphologic Features and Literature Review.

International journal of surgical pathology·2026
Same author

Development of a PCR-Cas12a-LFD visual detection system for highly sensitive and specific detection of Ralstonia sp., Phytophthora sp., Alternaria sp., and Pseudomonas sp. in tobacco.

Pest management science·2026
Same author

Primary epithelioid angiomatous nodule of the vocal cord: A case report and literature review.

Experimental and therapeutic medicine·2025
Same author

A retrospective and comprehensive analysis of excess life-years lost, mortality risk, and cause of death among severe mental illness in China.

BMC medicine·2025
Same author

In Situ Cross-Linked Chitosan/Hyaluronic Acid Hydrogel for Removing Kidney Stone Fragments after Lithotripsy Surgery.

ACS applied bio materials·2025

Related Experiment Video

Updated: Jun 20, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Pulfrich phenomena are coded effectively by a joint motion-disparity process.

Ning Qian1, Ralph D Freeman

  • 1Department of Neuroscience, Columbia University, New York, NY, USA. nq6@columbia.edu

Journal of Vision
|September 18, 2009
PubMed
Summary
This summary is machine-generated.

Pulfrich phenomena, depth illusions from interocular time delay, are best explained by joint neural coding of motion and disparity. This unified model accounts for observed S-shaped disparity functions and direction-depth effects.

More Related Videos

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Related Experiment Videos

Last Updated: Jun 20, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Area of Science:

  • Neuroscience
  • Computational Vision
  • Perceptual Psychology

Background:

  • Pulfrich phenomena are depth illusions caused by interocular time delays.
  • Previous research proposed joint coding of motion and disparity by neurons.
  • Recent models challenge joint coding, focusing on S-shaped disparity functions.

Purpose of the Study:

  • To address fundamental problems in recent models of Pulfrich phenomena.
  • To compare joint and separate neural coding schemes for motion and disparity.
  • To determine the most plausible neural basis for Pulfrich effects.

Main Methods:

  • Critically evaluated recent models regarding causality and physiological plausibility.
  • Developed and compared computational models of joint and separate coding.
  • Assessed model performance against experimental data, including S-shaped disparity functions and direction-depth contingency.

Main Results:

  • Identified fundamental issues with recent models of Pulfrich phenomena.
  • Demonstrated that joint coding, not separate coding, can explain S-shaped disparity functions.
  • Showed that unidirectional motion selectivity within joint coding is necessary for direction-depth contingency.

Conclusions:

  • Joint encoding of unidirectional motion and disparity provides a unified explanation for Pulfrich phenomena.
  • Separate coding models fail to account for key experimental observations.
  • The findings support a neural basis where motion and disparity are processed together.