Neural Dynamic Logic of Consciousness: The Knowledge Instinct

Abstract

This report discusses the evolution of consciousness driven by the knowledge instinct, a fundamental mechanism of the mind which determines its higher cognitive functions and neural dynamics. We discuss mathematical difficulties encountered in the past attempts at modeling the mind and relate them to logic. Neural modeling fields and dynamic logic mathematically describe these mechanisms and relate their neural dynamics to the knowledge instinct. Dynamic logic overcomes past mathematical difficulties encountered in modeling intelligence. Mathematical mechanisms of concepts, emotions, instincts, consciousness and unconscious are described and related to perception and cognition. The two main aspects of the knowledge instinct are differentiation and synthesis. Differentiation is driven by dynamic logic and proceeds from vague and unconscious states to more crisp and conscious states, from less knowledge to more knowledge at each hierarchical level of the mind. Synthesis is driven by a hierarchical organization of the mind; it strives to achieve unity and meaning of knowledge: every concept finds its deeper and more general meaning at a higher level. These mechanisms are in complex relationship of symbiosis and opposition, and lead to complex dynamics of evolution of consciousness and cultures. Mathematical modeling of this dynamics in a population leads to predictions for the evolution of consciousness, and cultures. Cultural predictive models can be compared to experimental data and used for improvement of human conditions. We discuss existing evidence and future research directions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 07, 2007
Accession Number
ADA472303

Entities

People

  • Leonid I. Perlovsky

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Artificial Intelligence
  • Brain
  • Cognition
  • Consciousness
  • Detection
  • Dynamics
  • Information Science
  • Intelligent Systems
  • Mathematical Logic
  • Mathematics
  • Neural Networks
  • Perception
  • Probability
  • Visual Cortex
  • Visual Perception

Readers

  • Educational Psychology
  • Neural Network Machine Learning.
  • Organizational Process Management (OPM).