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Neurosemantics, neurons and system theory.

Olaf Breidbach1

  • 1Ernst-Haeckel-Haus, Jena University, Berggasse 7, D-07745, Jena, Germany. Olaf.Breidbach@uni-jena.de

Theory in Biosciences = Theorie in Den Biowissenschaften
|December 19, 2007
PubMed
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Neuronal signal processing relies solely on internal system characteristics, not external observers. This self-referential operation, driven by local computations, forms the basis for neurosemantics.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cognitive Science

Background:

  • Traditional models of signal processing in neuronal systems often incorporate external observer perspectives.
  • This study challenges conventional approaches by emphasizing internal system dynamics.

Purpose of the Study:

  • To propose a framework for evaluating neuronal signal processing based exclusively on internal system characteristics.
  • To explore the concept of endogenous factors governing system configuration and computational performance.
  • To establish the foundation for neurosemantics through intrinsic system logic.

Main Methods:

  • Theoretical analysis of signal processing within neuronal networks.
  • Focus on local computation and emergent system behavior.

Related Experiment Videos

  • Examination of self-referential operations and intrinsic rules.

    • Main Results:

    • Signal processing is determined by internal system characteristics, excluding external control.
    • Endogenous factors dictate system configuration and computational performance.
    • Local computations generate emergent behaviors governed by intrinsic rules.

    Conclusions:

    • Neuronal signal processing should be understood through internal system dynamics.
    • Self-referential operations and intrinsic logic are fundamental to neural computation.
    • This internalist approach provides a basis for understanding neurosemantics.