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Quantifying consciousness through intrinsic probability density function

delete2025-08-06
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OA
AI
N
Norden E. Huang
W
Wei-Shuai Yuan
A
Albert C. Yang
T
Terry B.J. Kuo
W
Wen-Xi Tang
H
Helen Kang
M
Max Leopold Wagner
W
Wei‐Kuang Liang *
DOI:10.1016/j.biopsycho.2025.109101delete
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Abstract

Abstract

En 中文
• Introduces iPDF to quantify consciousness via EEG. • Uses empirical mode decomposition to generate scale-dependent probability density functions • Distinguishes conscious from unconscious states by iPDF. • Identifies neural interactions or modulations via super-Gaussian vs. Gaussian EEG profiles. • Achieves 81 % accuracy in dementia classification.
Keywords:
Intrinsic Probability Density Function
IPDF
Consciousness
Conscious states
Sleep
Neural interactions
Neural modulations
Intercortical communications
Emperical Mode Decomposition
EMD
Dementia
Cognitive states
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Biological Psychology cover
Biological Psychology
IF:
2.9
Papers:
407
Citations:
1.0W

Organization

N
national yang-ming chiao tung university
Scholars:
121
Papers: 65
Citations: 0
H
Harvard University
Scholars:
26.5W
Papers: 22.0W
Citations: 28.7W
N
National Central University
Scholars:
1.0W
Papers: 8.6K
Citations: 6.4K
S
shandong university
Scholars:
9.5W
Papers: 6.4W
Citations: 94
F
First Institute of Oceanography
Scholars:
347
Papers: 148
Citations: 1.9K
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