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Perspectives on Neuroscience
Published on: July 31, 2007
Sources of knowledge-causation begets entropy increase, time progression, and information flow
1University of Cincinnati, Cincinnati, OH, United States.
Frontiers in Cognition
|June 24, 2026
Summary
Causation drives information evolution, the basis for knowledge generation. Understanding this flow, measurable through Lyapunov exponents and information dimensions, is key to scientific inquiry.
Area of Science:
- Information theory
- Thermodynamics
- Philosophy of science
Background:
- Knowledge generation relies on information, distinct from belief.
- Causation, defined as property transfer (energy/momentum), has been debated.
- Time progression is linked to energy transfer and thermodynamic entropy.
Purpose of the Study:
- To define the underpinning of knowledge.
- To establish causation as the driver of information evolution.
- To link information flow to scientific inquiry and knowledge.
Main Methods:
- Information flow measurement using Lyapunov exponents and information dimensions.
- Analysis of causation as energy/momentum transfer.
- Characterization of time progression via heat transfer.
Main Results:
- Causation modifies thermodynamic entropy in all systems.
- Causation drives both time progression and information evolution.
- Observed information evolution during scientific inquiry forms the basis for knowledge.
Conclusions:
- Knowledge is fundamentally rooted in the information evolution driven by causation.
- Unobserved information dissipates over time and entropy, becoming inaccessible.
- This framework provides a unique definition for the generation of knowledge.
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