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

Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

2.7K
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
2.7K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.5K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.5K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

335
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
335
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

2.7K
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.
2.7K
Uniform Depth Channel Flow01:27

Uniform Depth Channel Flow

890
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant...
890
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

870
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
870

You might also read

Related Articles

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

Sort by
Same author

Hierarchical coding of binary images.

IEEE transactions on pattern analysis and machine intelligence·2011
Same author

Combining sensory information: mandatory fusion within, but not between, senses.

Science (New York, N.Y.)·2002
Same author

How vertical disparities assist judgements of distance.

Vision research·2001
Same author

Ideal cue combination for localizing texture-defined edges.

Journal of the Optical Society of America. A, Optics, image science, and vision·2001
Same author

Interaction of visual prior constraints.

Vision research·2001
Same author

Interaction between the perceived shape of two objects.

Vision research·2000
Same journal

Phase retrieval with prior information.

Journal of the Optical Society of America. A, Optics and image science·2008
Same journal

Clinical microscopy of the cornea utilizing optical sectioning and a high-numerical-aperture objective.

Journal of the Optical Society of America. A, Optics and image science·1993
Same journal

Eye-tracking laser Doppler velocimeter stabilized in two dimensions: principle, design, and construction.

Journal of the Optical Society of America. A, Optics and image science·1993
Same journal

Effects of aging in retinal image quality.

Journal of the Optical Society of America. A, Optics and image science·1993
Same journal

Axial eye-length measurement by wavelength-shift interferometry.

Journal of the Optical Society of America. A, Optics and image science·1993
Same journal

Fractal analysis of steady-state-flicker visual evoked potentials: feasibility.

Journal of the Optical Society of America. A, Optics and image science·1993
See all related articles

Related Experiment Video

Updated: May 6, 2026

Examining Local Network Processing using Multi-contact Laminar Electrode Recording
13:40

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

12.2K

Parallel model of the kinetic depth effect using local computations.

M S Landy

    Journal of the Optical Society of America. A, Optics and Image Science
    |May 1, 1987
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel computational model for the kinetic depth effect using multidot stimuli. The model employs a cooperative-competitive network for iterative depth cue processing, enhancing 3D perception.

    More Related Videos

    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

    16.3K
    Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
    09:49

    Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

    Published on: April 16, 2014

    24.7K

    Related Experiment Videos

    Last Updated: May 6, 2026

    Examining Local Network Processing using Multi-contact Laminar Electrode Recording
    13:40

    Examining Local Network Processing using Multi-contact Laminar Electrode Recording

    Published on: September 8, 2011

    12.2K
    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

    16.3K
    Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
    09:49

    Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

    Published on: April 16, 2014

    24.7K

    Area of Science:

    • Computational neuroscience
    • Computer vision
    • Perception psychology

    Background:

    • The kinetic depth effect (KDE) is crucial for perceiving 3D structure from motion.
    • Existing models often struggle with complex multidot stimuli and integrating multiple depth cues.

    Purpose of the Study:

    • To propose a new computational model for the kinetic depth effect (KDE).
    • To simulate KDE using multidot stimuli within a cooperative-competitive network.

    Main Methods:

    • Developed a relaxation labeling process for iterative computation of depth cues.
    • Incorporated local rigidity constraints, akin to the Ullman incremental-rigidity scheme.
    • Simulated the model with changing-dot-position cues and additional depth cues.

    Main Results:

    • The model successfully computes depth from motion in multidot displays.
    • Demonstrated the integration of local rigidity and changing-dot-position cues.
    • Showcased the model's flexibility with combined depth cues.

    Conclusions:

    • The proposed cooperative-competitive network model offers a robust framework for understanding the kinetic depth effect.
    • The model's reliance on local iterative computation and rigidity constraints provides insights into biological visual processing.
    • Future work can explore further integration of diverse depth cues within this framework.