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

Membrane Fluidity01:26

Membrane Fluidity

15.8K
Membrane fluidity is explained by the fluid mosaic model of the cell membrane, which describes the plasma membrane structure as a mosaic of components—including phospholipids, cholesterol, proteins, and carbohydrates—that gives the membrane a fluid character.
Mosaic nature of the membrane
The mosaic characteristic of the membrane helps the plasma membrane remain fluid. The integral proteins and lipids exist as separate but loosely-attached molecules in the membrane. The membrane is...
15.8K
Membrane Fluidity01:23

Membrane Fluidity

174.6K
Cell membranes are composed of phospholipids, proteins, and carbohydrates loosely attached to one another through chemical interactions. Molecules are generally able to move about in the plane of the membrane, giving the membrane its flexible nature called fluidity. Two other features of the membrane contribute to membrane fluidity: the chemical structure of the phospholipids and the presence of cholesterol in the membrane.
174.6K
State Space Representation01:27

State Space Representation

590
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
590
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

220
The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all...
220
Control Volume and System Representations01:16

Control Volume and System Representations

1.6K
Two key frameworks are employed to analyze mass, energy, and momentum transfer: the control volume approach and the system approach. These frameworks offer different perspectives, depending on whether the focus is on a specific region in space (control volume approach) or a defined mass of fluid (system approach).
The control volume approach considers a stationary region in space through which fluid flows. This region is bounded by a control surface.  For instance, in the case of water...
1.6K
Cognitive Dissonance01:38

Cognitive Dissonance

37.5K
Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
37.5K

You might also read

Related Articles

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

Sort by
Same author

Efficacy and effectiveness of robot-assisted therapy for autism spectrum disorder: From lab to reality.

Science robotics·2025
Same author

EEL-GA: An Evolutionary Clustering Framework for Energy-Efficient 3D Wireless Sensor Networks in Smart Forestry.

Sensors (Basel, Switzerland)·2025
Same author

A latent diffusion approach to visual attribution in medical imaging.

Scientific reports·2025
Same author

Visual attribution using Adversarial Latent Transformations.

Computers in biology and medicine·2023
Same author

Pediatrics in Artificial Intelligence Era: A Systematic Review on Challenges, Opportunities, and Explainability.

Indian pediatrics·2023
Same author

Machine Learning in Pediatrics: Evaluating Challenges, Opportunities, and Explainability.

Indian pediatrics·2023
Same journal

Ruliological Resilience: Pattern Restoration and Robustness in Wolfram Patterns. A Basis for Regeneration, Not Just in Cone Shells?

Bio Systems·2026
Same journal

The Quantum-to-Classical Transducer: A Thermodynamic and Quantum Mechanical Framework for the Emergence of Bioenergetics.

Bio Systems·2026
Same journal

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same journal

Partial-label metric ceilings for evaluating gene regulatory networks inferred from single-cell foundation models.

Bio Systems·2026
Same journal

The impedance mismatch theory: A non-equilibrium thermodynamic framework for a shared energetic stress pathway in neurodegeneration.

Bio Systems·2026
Same journal

Immune signal-status misclassification: A theoretical framework for biological status assignment and failed status resolution.

Bio Systems·2026
See all related articles

Related Experiment Video

Updated: Feb 6, 2026

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.8K

Representational fluidity in embodied (artificial) cognition.

David Windridge1, Serge Thill2

  • 1Department of Computer Science, School of Science and Technology, Middlesex University, The Burroughs, London NW4 4B, UK; Centre for Vision Speech and Signal Processing, University of Surrey, Guildford, GU2 7XH, UK.

Bio Systems
|August 10, 2018
PubMed
Summary
This summary is machine-generated.

Embodied cognition requires more than body-as-interface. For human-like intelligence, artificial agents need to update their representational frameworks, grounding symbols through sensorimotor experiences for true cognitive capabilities.

Keywords:
ComputationalismEmbodied cognitionRepresentational frameworksRepresentational updating

More Related Videos

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
08:31

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

Published on: July 31, 2016

14.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.1K

Related Experiment Videos

Last Updated: Feb 6, 2026

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

13.8K
Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
08:31

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome

Published on: July 31, 2016

14.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.1K

Area of Science:

  • Cognitive Science
  • Artificial Intelligence
  • Philosophy of Mind

Background:

  • Theories of embodied cognition debate the body's role in cognition.
  • Some views see the body as a mere input/output interface for computational processes.
  • This paper challenges the notion of the body as solely an interface.

Purpose of the Study:

  • To demonstrate that the body's role in cognition extends beyond a simple interface.
  • To explore the requirements for artificial agents to achieve human-level cognition.
  • To introduce the concept of "representational fluidity" as crucial for cognition.

Main Methods:

  • Analysis of necessary properties for artificial agents capable of updating representational frameworks.
  • Examination of how updates must be falsifiable and beneficial to the agent.
  • Proposal of a mechanism involving bottom-up abstraction and top-down hypothesis testing.

Main Results:

  • Cognitive agents require mechanisms for updating their representational frameworks, not just reasoning.
  • Representational updates are achieved through progressive symbolic abstraction of sensorimotor connections.
  • Top-down hypothesis testing guides representational shifts beneficially.

Conclusions:

  • Human cognition necessitates a dynamic, updating representational system grounded in sensorimotor experience.
  • Fully embodied learners with a priori perception-action linkages are essential for grounding symbolic representations.
  • Findings have implications for understanding human cognition and designing advanced AI.