A Transfer entropy-based methodology to analyze information flow under eyes-open and eyes-closed conditions with a clinical perspective-Reference-Cited by-同舟云学术

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A Transfer entropy-based methodology to analyze information flow under eyes-open and eyes-closed conditions with a clinical perspective

Published:2023-09 Issue: Volume:86 Page:105181
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Restrepo Juan F.^ORCID,Mateos Diego M.^ORCID,López Juan M. Díaz^ORCID

Funder

Agencia Nacional de Promoción Científica y Tecnológica

Universidad Nacional de Entre Ríos

Agencia Nacional de Promocion de la Investigacion el Desarrollo Tecnologico y la Innovacion

Consejo Nacional de Investigaciones Científicas y Técnicas

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference39 articles.

1. Neurosciences;Purves,2019

2. EEG differences between eyes-closed and eyes-open resting conditions;Barry;Clin. Neurophysiol.,2007

3. The difference of brain functional connectivity between eyes-closed and eyes-open using graph theoretical analysis;Tan;Comput. Math. Methods Med.,2013

4. Eye closure causes widespread low-frequency power increase and focal gamma attenuation in the human electrocorticogram;Geller;Clin. Neurophysiol.,2014

5. Exploring the alpha desynchronization hypothesis in resting state networks with intracranial electroencephalography and wiring cost estimates;Gómez-Ramírez;Sci. Rep.,2017

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1. Vagus nerve stimulation modulating the directed brain network of patients with drug-resistant epilepsy;Biomedical Signal Processing and Control;2024-09

2. Revisiting the Characterization of Resting Brain Dynamics with the Permutation Jensen–Shannon Distance;Entropy;2024-05-20

3. Permutation entropy analysis of EEG signals for distinguishing eyes-open and eyes-closed brain states: Comparison of different approaches;Chaos: An Interdisciplinary Journal of Nonlinear Science;2024-04-01

4. Information Geometry Theoretic Measures for Characterizing Neural Information Processing from Simulated EEG Signals;Entropy;2024-02-28

5. Information Geometry Approach to Analyzing Simulated EEG Signals of Alzheimer's Disease Patients and Healthy Control Subjects;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

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