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Commentary Open Access
Volume 5 | Issue 1 | DOI: https://doi.org/10.46439/Neuroscience.5.027

A comprehensive metric for consciousness strength: Integrating real-time responsiveness and long-term learning based on the HLbC model

  • 1Ishinomaki Senshu University, 1 Shinmito, Minami-sakai, Ishinomaki-shi, Miyagi-ken, 986-8580, Japan
  • 2Fukuoka University, 1-19 Nanakuma, Jonan-ku, Fukuoka-shi,814-0180, Japan
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Corresponding Author

Shin-ichi Inage, s.inage.pu@isenshu-u.ac.jp

Received Date: December 30, 2024

Accepted Date: May 16, 2025

Abstract

This paper presents a novel framework for measuring consciousness strength based on the Human Language-based Consciousness (HLbC) model. While Integrated Information Theory (IIT) quantifies consciousness via integrated information, the HLbC model views consciousness as a post-hoc process, emphasizing language and probabilistic decision-making. By modeling this decision process, a pseudo-Schrödinger equation emerges where the Kullback-Leibler distance replaces spatial coordinates. We propose two metrics for "consciousness strength": one focusing on real-time response and information processing, and another using Bayesian statistics to assess learning and adaptation over time. These metrics offer a comprehensive view of consciousness, integrating both immediate responses and long-term learning. Our findings contribute to advancing quantitative measures of consciousness, with potential applications in fields like artificial intelligence.

Keywords

Consciousness strength, Bayesian learning, Real-time evaluation, Information entropy, HLbC model

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