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Cybernetic model of psychophysiological pathways: I. Control functions
1Neuroscience Institute, Division of Research, New York Chiropractic College, Glen Head 11545.
Journal of Manipulative and Physiological Therapeutics
|April 1, 1989
Summary
The nervous system processes information by converting numerous electrophysiological signals into higher-order signals. This "superization" allows for nuanced control but can lead to dysfunction if not all signal details are refined.
Area of Science:
- Neuroscience
- Information Theory
- Computational Neuroscience
Background:
- Electrophysiological signals are crucial for neural communication but lack specificity.
- The nervous system must interpret complex signal arrays to derive meaningful information.
Purpose of the Study:
- To examine the
- superization
- process by which the nervous system transforms raw signals into actionable information.
- To elucidate the mechanisms of information recognition and control within neural networks.
Main Methods:
- Analysis of signal processing within neuronal networks.
- Conceptual modeling of hierarchical information extraction.
- Examination of the transition from signal-based to information-based control.
Main Results:
- Information recognition is achieved through a hierarchical "superization" process, moving from lower-order signals to superior-order signals.
- Neuronal networks utilize logical circuits, representing source models, for signal recognition.
- The nervous system transitions from signal-based control to information-based control, enabling more refined supervision.
Conclusions:
- The superization process is fundamental to how the nervous system extracts and utilizes information.
- While enabling sophisticated control, this process can lead to psychophysiological dysfunction if information refinement is incomplete.