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

Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.1K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.1K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

185
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
185
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

652
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
652
Partial Fractions01:28

Partial Fractions

73
A partial fraction is a component of a rational expression represented as the sum of simpler fractions. When a rational function is expressed as a ratio of two polynomials, it can often be decomposed into a sum of fractions whose denominators are simpler polynomials, typically linear or irreducible quadratic factors. This process is called partial fraction decomposition, and it is used to simplify complex expressions for integration, solving equations, or analysis.Partial fraction decomposition...
73
Fast Fourier Transform01:10

Fast Fourier Transform

657
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
657
Fisher's Exact Test01:08

Fisher's Exact Test

995
Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
995

You might also read

Related Articles

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

Sort by
Same author

Koopman mode decomposition of thermodynamic dissipation in nonlinear Langevin dynamics.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

A Japan-origin motivational framework for diversive and specific curiosity: development of the English version of the Japanese Epistemic Curiosity scale.

Frontiers in psychology·2026
Same author

Atypical Tactile Expressions Using Japanese Ideophones in Adults With Autism Spectrum Disorders.

Journal of autism and developmental disorders·2026
Same author

Single-cell resolution functional networks during unconsciousness are segregated into spatially intermixed modules.

Cell reports·2026
Same author

Quantifying State-Dependent Control Properties of Brain Dynamics from Perturbation Responses.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2025
Same author

Qualia structures collapse for geometric shapes, but not faces, when spatial attention is withdrawn.

Neuroscience of consciousness·2025

Related Experiment Video

Updated: Nov 27, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.4K

Efficient Algorithms for Searching the Minimum Information Partition in Integrated Information Theory.

Jun Kitazono1,2, Ryota Kanai1, Masafumi Oizumi1,3

  • 1Araya, Inc., Toranomon 15 Mori Building, 2-8-10 Toranomon, Minato-ku, Tokyo 105-0001, Japan.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

Integrated Information Theory (IIT) quantifies consciousness via integrated information (Φ). A new algorithm efficiently finds the Minimum Information Partition (MIP) for large systems, even with non-submodular Φ measures.

Keywords:
Queyranne’s algorithmconsciousnessintegrated informationintegrated information theoryminimum information partitionsubmodularity

More Related Videos

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.5K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.5K

Related Experiment Videos

Last Updated: Nov 27, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.4K
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.5K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.5K

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Information Theory

Background:

  • Information integration is crucial for brain functions like cognition and consciousness.
  • Integrated Information Theory (IIT) links consciousness level to integrated information (Φ).
  • Calculating Φ requires finding the Minimum Information Partition (MIP), which is computationally intensive.

Purpose of the Study:

  • To evaluate an optimization algorithm for finding the MIP with non-submodular Φ measures.
  • To determine the practical applicability of the algorithm for real neural data.
  • To assess the accuracy of the algorithm in identifying the MIP for large systems.

Main Methods:

  • Empirical evaluation of an optimization algorithm on simulated and real neural data.
  • Testing the algorithm's performance with non-submodular measures of Φ.
  • Assessing the accuracy of MIP identification by the algorithm.

Main Results:

  • The algorithm accurately identifies the MIP even for non-submodular Φ measures.
  • The method successfully measures Φ in large systems within practical time constraints.
  • Computational challenges in applying IIT to neural data are significantly reduced.

Conclusions:

  • The developed algorithm enables efficient Φ measurement in complex systems.
  • This approach facilitates the application of IIT to large-scale neural data.
  • The findings support the use of this algorithm for advancing consciousness research.