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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Graphs of Functions01:30

Graphs of Functions

Graphs of functions provide a visual representation of how output values change in response to varying inputs. Each point on the graph corresponds to an ordered pair, where the x-coordinate (independent variable) determines the horizontal position and the y-coordinate (dependent variable) determines the vertical position. Linear functions like y = x give a straight line, indicating a constant rate of change.Nonlinear functions display more complex behaviors. Even power functions generate...
Graphs of Two-Variable Functions01:27

Graphs of Two-Variable Functions

A weather map provides a practical example of a function of two variables. Across a wide region such as the United States, temperatures vary from one location to another. Each location can be identified by two geographic coordinates: longitude and latitude. Since a single temperature value is assigned to each coordinate pair, the situation can be represented mathematically as a function with two inputs and one output.In mathematical notation, longitude and latitude can be labeled as x and y,...
Introduction to Functional Groups02:08

Introduction to Functional Groups


Functional groups are group of atoms with specific chemical properties that occur within organic molecules and sometimes denoted as “R”. Functional groups are found along the carbon backbone of macromolecules can form chains or rings of carbon atoms. Functional groups can “functionalize” a compound by enabling it to adopt different physical and chemical properties.
Types of common functional groups
The table below summarizes some of the major functional groups in organic chemistry. (The...
Functional Groups02:45

Functional Groups

Functional groups are a group of atoms with characteristic properties, which when linked to the carbon skeleton of a molecule, alter the properties of that molecule. For example, the presence of certain functional groups on a molecule will make them hydrophilic, whereas others will make them hydrophobic. These functional groups are an indispensable part of organic chemistry and important components of biological molecules, such as carbohydrates, proteins, lipids, and nucleic acids. Each...

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Related Experiment Video

Updated: Jul 3, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Identification of functional information subgraphs in complex networks.

Luís M A Bettencourt1, Vadas Gintautas, Michael I Ham

  • 1T-7 and CNLS, Theoretical Division, MS B284 Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

Physical Review Letters
|July 23, 2008
PubMed
Summary

This study introduces an information-theoretic method to find functional groups in complex networks. The approach identifies key neuronal circuits by analyzing information flow and redundancy in brain activity.

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Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Related Experiment Videos

Last Updated: Jul 3, 2026

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
08:36

Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

  • Computational Neuroscience
  • Network Science
  • Information Theory

Background:

  • Complex networks, such as neuronal systems, exhibit emergent properties from the interactions of their components.
  • Understanding functional relationships within these networks is crucial for deciphering system behavior.

Purpose of the Study:

  • To develop a general information-theoretic framework for identifying functional subgraphs in complex networks.
  • To apply this framework to analyze neuronal circuits and understand information processing in the brain.

Main Methods:

  • Formulated a novel information-theoretic approach based on conditional mutual information, analogous to discrete calculus.
  • Developed optimization algorithms inspired by Taylor series expansions for identifying functional groups.
  • Applied the methodology to in vitro electrophysiological recordings of cortical neuronal networks.

Main Results:

  • Demonstrated that variable uncertainty can be decomposed into information quantities reflecting functional relationships.
  • Identified specific neuronal subgraphs responsible for explaining individual cell firing patterns.
  • Characterized these subgraphs based on their redundant or synergetic contributions to information processing.

Conclusions:

  • The developed information-theoretic method effectively identifies functional subgraphs in complex networks.
  • This approach allows for the reconstruction of neuronal circuits that explain target cell activity, highlighting redundant and synergetic interactions.