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

Growth Models with Integration: Problem Solving01:27

Growth Models with Integration: Problem Solving

In population modeling, integration provides a systematic way to determine accumulated quantities from known rates of change. One such application arises in ecology, where the total weight of a fish population in a body of water is referred to as its biomass. When the rate of growth of this biomass is known as a function of time, calculus can be used to determine the total biomass at a future date.Growth Rate and Biomass FunctionLet the growth rate of the fish population be represented by a...
Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
Cognitivism01:17

Cognitivism

Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
Previously dominated by behaviorism, which prioritized observable behaviors and largely ignored mental processes, psychology transformed in the 1950s. Cognitive psychologists argue that understanding how we think and process information is...
Causes of Social Behavior II: Cognitive Processes01:15

Causes of Social Behavior II: Cognitive Processes

Cognitive processes affect social behavior by guiding how individuals perceive, interpret, and respond to social stimuli. These mental processes enable individuals to assess others' behaviors, attribute causes to their actions, and form expectations based on past experiences.Causes of Behavior and Social JudgmentsIndividuals determine the causes of others' behaviors by distinguishing between personal traits and external circumstances. For example, if a friend frequently arrives late, an...

You might also read

Related Articles

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

Sort by
Same author

Biotechnical Multiscale Engineering of Scaffolds for Stem Cell and Organoid Research.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

Pragmatic information of aesthetic appraisal.

Cognitive neurodynamics·2025
Same author

Invariants for neural automata.

Cognitive neurodynamics·2024
Same author

Editorial: Predictive modeling of cognition and behavior on quantum principles.

Frontiers in psychology·2023
Same author

Particle filters for high-dimensional geoscience applications: A review.

Quarterly journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain)·2019
Same author

Metastable Resting State Brain Dynamics.

Frontiers in computational neuroscience·2019
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
Same journal

State estimation in spatiotemporal chaos via low-rank StatFEM.

Chaos (Woodbury, N.Y.)·2026
Same journal

Universal response functions in driven dissipative tunneling dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

A network-based approach to characterize the dynamics of the coupling field of thermoacoustic oscillators in annular geometry.

Chaos (Woodbury, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Jun 24, 2026

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

Inverse problems in dynamic cognitive modeling.

Peter beim Graben1, Roland Potthast

  • 1School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire, United Kingdom. p.r.beimgraben@reading.ac.uk

Chaos (Woodbury, N.Y.)
|April 2, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces dynamic cognitive modeling to determine synaptic weights and kernel functions for neural systems. A Tikhonov-Hebbian learning method is proposed to solve ill-posed inverse problems in cognitive computations.

More Related Videos

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance
13:20

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance

Published on: December 5, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

Related Experiment Videos

Last Updated: Jun 24, 2026

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance
13:20

Online Repetitive Transcranial Magnetic Stimulation of Dorsomedial and Dorsolateral Prefrontal Cortex in Cognition Decision Making, and Cognitive Dissonance

Published on: December 5, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

Area of Science:

  • Computational Neuroscience
  • Cognitive Science
  • Dynamical Systems Theory

Background:

  • Inverse problems in cognitive modeling involve determining parameters like synaptic weight matrices or kernel functions.
  • Existing methods face challenges, particularly with ill-posed kernel construction problems in neural/dynamic field models.

Purpose of the Study:

  • To introduce a novel framework for dynamic cognitive modeling.
  • To address the ill-posed nature of kernel construction in neural/dynamic field theories.
  • To propose and validate a regularization technique for solving these inverse problems.

Main Methods:

  • A three-tier, top-down dynamic cognitive modeling approach is presented.
  • Cognitive processes are modeled as algorithms operating on symbolic data structures.
  • Symbolic operations are mapped to vector space transformations, implemented in neurodynamical systems.

Main Results:

  • The Amari equation for neural/dynamic field theory is discussed as a specific case.
  • The kernel construction problem is identified as particularly ill-posed.
  • A Tikhonov-Hebbian learning method is proposed and demonstrated as a robust regularization technique.

Conclusions:

  • Dynamic cognitive modeling offers a structured approach to understanding cognitive processes.
  • The Tikhonov-Hebbian method effectively regularizes ill-posed inverse problems in cognitive computations.
  • This framework provides a robust method for parameter estimation in neurodynamical systems.