Nonadditive Information Theory for the Analysis of Brain Rhythms

Abstract

In this paper, we introduce Nonadditive Information Theory through the axiomatic formulation of Tsallis entropy. We show that systems with transitions from high dimensionality to few degrees of freedom are better described by nonadditive formalism. Such a biological system is the brain and brain rhythms is its macroscopic dynamic trace. We will show with simulations that Tsallis entropy is a powerful information measure, and we present results of brain dynamics analyzed using EEG recordings from a brain injury model.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA410192

Entities

People

  • A. Bezerianos
  • N. Thakor
  • Susanna T.Y. Tong
  • Yupeng Zhu

Organizations

  • Johns Hopkins University

Tags

DTIC Thesaurus Topics

  • Biomedical Engineering
  • Brain Injuries
  • Cardiac Arrest
  • Distribution Functions
  • Engineering
  • Gaussian Distributions
  • Information Theory
  • Mechanics
  • Military Research
  • Random Variables
  • Recovery
  • Standards
  • Statistical Mechanics
  • Stochastic Processes
  • Systems Biology

Readers

  • Computational Fluid Dynamics (CFD)
  • Mathematical Modeling and Probability Theory.
  • Neurotrauma and Rehabilitation Medicine.