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Standard Entropy Change for a Reaction03:00

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Dynamic Cross-Entropy.

Dorian Aur1, Fidel Vila-Rodriguez1

  • 1Non-Invasive Neurostimulation Therapies Lab, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.

Journal of Neuroscience Methods
|December 17, 2016
PubMed
Summary
This summary is machine-generated.

We developed Dynamic Cross-Entropy (DCE), a new method to measure complexity in multidimensional time series like EEG signals. DCE can identify transitions to chaos, offering insights into nonlinear brain activity.

Keywords:
Brain synchronyChaosComplexityEntropyNonlinear dynamicsNonlinear resonance

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Area of Science:

  • Neuroscience
  • Nonlinear Dynamics
  • Signal Processing

Background:

  • Traditional time series complexity measures are limited to one dimension.
  • Many real-world systems, including brain activity, are multidimensional.

Purpose of the Study:

  • Introduce Dynamic Cross-Entropy (DCE) as a novel multidimensional complexity measure.
  • Quantify the regularity of electroencephalogram (EEG) signals in specific frequency bands.
  • Test DCE's ability to detect transitions to chaos using logistic equations.

Main Methods:

  • Developed Dynamic Cross-Entropy (DCE), a multidimensional complexity measure.
  • Applied sliding window DCE analysis to EEG data and logistic equations.
  • Utilized sample entropy for DCE calculation, comparing it to Shannon entropy.

Main Results:

  • DCE analysis revealed period-doubling bifurcations leading to chaos in logistic equations.
  • Observed similar chaotic transitions in EEG signals during electroconvulsive therapy (ECT) induced seizures.
  • DCE values showed phase transitions from regular to irregular states, indicating potential chaos in the brain.
  • DCE based on sample entropy demonstrated robustness against EEG artifacts.

Conclusions:

  • DCE is a novel technique for analyzing multidimensional time series complexity.
  • The method can identify transitions to chaos in biological signals like EEG.
  • DCE offers new avenues for understanding nonlinear brain activity and neurological conditions.