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Related Experiment Video

Updated: Dec 2, 2025

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

Leonardo S Barbosa1, William Marshall1,2, Sabrina Streipert1,3

  • 1Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53719, USA.

Scientific Reports
|November 3, 2020
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Summary
This summary is machine-generated.

We developed a novel information measure for intrinsic sender/receiver perspectives. This measure uniquely quantifies information based on causality, specificity, and intrinsicality, crucial for systems like neural networks.

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Area of Science:

  • Information theory
  • Communication systems
  • Network science

Background:

  • Existing information measures often rely on external channel knowledge.
  • A receiver or sender's intrinsic perspective is critical in many systems.
  • Understanding symbol information without channel access is a key challenge.

Purpose of the Study:

  • To introduce a novel information measure from an intrinsic perspective.
  • To define and satisfy causality, specificity, and intrinsicality properties.
  • To explore the implications of this measure for symbol-based systems.

Main Methods:

  • Developed a unique information measure based on three core properties.
  • Analyzed how symbol repertoire expansion and dilution affect information.
  • Demonstrated the measure's applicability to intrinsic system assessments.

Main Results:

  • The proposed information measure is unique and satisfies causality, specificity, and intrinsicality.
  • Intrinsic information increases with noise-free repertoire expansion.
  • Intrinsic information decreases with signal-free repertoire dilution.

Conclusions:

  • The new information measure provides a receiver/sender intrinsic viewpoint.
  • Optimal balance between expansion and dilution is vital for intrinsic assessments.
  • This framework is relevant for understanding systems like neural networks.