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

Clearance Models: Compartment Models01:25

Clearance Models: Compartment Models

165
Clearance measures drug elimination from the central compartment, including plasma and highly perfused organs like kidneys and liver. Its calculation varies depending on pharmacokinetic models and administration routes. The one-compartment model, for instance, portrays the pharmacokinetics of polar drugs such as aminoglycoside antibiotics administered intravenously and readily excreted in urine. In this case, clearance is influenced by the terminal rate constant (λz) and the total volume...
165
Three-Compartment Open Model01:06

Three-Compartment Open Model

566
The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
566
Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

294
Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
294
Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

122
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
122
Rational Expressions01:28

Rational Expressions

60
Rational expressions are algebraic fractions in which both the numerator and the denominator are polynomials. These expressions follow the arithmetic rules of numerical fractions but require extra care due to the presence of variables. A fundamental part of working with rational expressions is identifying values that make the expression undefined, typically those that result in division by zero or undefined radicals.Determining the DomainThe domain of a rational expression includes all real...
60
Modeling and Similitude01:12

Modeling and Similitude

394
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...
394

You might also read

Related Articles

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

Sort by
Same author

On Common Factors in Visual Illusions: A Review.

Neuropsychologia·2026
Same author

Sequential neural dynamics underlie unconscious integration and conscious perception of visual stimuli.

PLoS biology·2026
Same author

Silver bullets and sensory horizons.

The Behavioral and brain sciences·2026
Same author

Examining the relationship between ssVEP and psychophysical measures of contrast sensitivity, grating acuity, and orientation discrimination.

iScience·2026
Same author

When stripes in clothes deceive: Cross-cultural examination of perceptual and belief discrepancies about horizontal stripes in clothes.

PloS one·2026
Same author

Finding the forest in the trees: Using machine learning and online cognitive and perceptual measures to predict adult autism diagnosis.

Translational psychiatry·2026

Related Experiment Video

Updated: Oct 29, 2025

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding
09:14

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Published on: August 22, 2016

12.7K

Shrinking Bouma's window: How to model crowding in dense displays.

Alban Bornet1, Adrien Doerig1,2, Michael H Herzog1

  • 1Laboratory of Psychophysics, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Plos Computational Biology
|July 6, 2021
PubMed
Summary

Visual crowding, where target perception worsens with flankers, challenges traditional models. New research shows grouping stages, not just proximity, explain crowding in dense displays, improving visual perception models.

More Related Videos

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

620
Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

9.0K

Related Experiment Videos

Last Updated: Oct 29, 2025

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding
09:14

Improving 2D and 3D Skin In Vitro Models Using Macromolecular Crowding

Published on: August 22, 2016

12.7K
Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

620
Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
05:58

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking

Published on: August 29, 2018

9.0K

Area of Science:

  • Visual perception
  • Computational neuroscience
  • Human vision

Background:

  • Visual crowding impairs target recognition due to surrounding elements.
  • Traditional models, like Bouma's law, suggest interference based on proximity.
  • Sparse display studies may yield inaccurate conclusions about human visual processing.

Purpose of the Study:

  • To test computational models explaining visual crowding in dense displays.
  • To determine if feedforward pooling or grouping stages better explain human performance.
  • To refine existing models of visual crowding.

Main Methods:

  • Utilized a genetic algorithm to generate dense visual displays.
  • Selected displays based on model outputs rather than human performance.
  • Compared feedforward pooling models against models with a dedicated grouping stage.

Main Results:

  • Feedforward pooling models failed to replicate human crowding behavior.
  • Models incorporating a grouping stage successfully explained the observed results.
  • Nearest neighbors, not all elements within a set distance, were found to be critical.

Conclusions:

  • Traditional feedforward models are insufficient for explaining visual crowding.
  • A dedicated grouping stage is crucial for accurate modeling of visual crowding.
  • Integrating grouping mechanisms enhances computational models of human vision.