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Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke
Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional con...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923597/ https://www.ncbi.nlm.nih.gov/pubmed/27403202 http://dx.doi.org/10.1155/2016/2582478 |
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author | Liu, Shuang Guo, Jie Meng, Jiayuan Wang, Zhijun Yao, Yang Yang, Jiajia Qi, Hongzhi Ming, Dong |
author_facet | Liu, Shuang Guo, Jie Meng, Jiayuan Wang, Zhijun Yao, Yang Yang, Jiajia Qi, Hongzhi Ming, Dong |
author_sort | Liu, Shuang |
collection | PubMed |
description | Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional connectivity in patients with acute thalamic ischemic stroke and healthy subjects. Electroencephalography (EEG) in resting condition with eyes closed was recorded for 12 stroke patients and 11 healthy subjects as control group. Lempel-Ziv complexity (LZC), Sample Entropy (SampEn), and brain network using partial directed coherence (PDC) were calculated for feature extraction. Results showed that patients had increased mean LZC and SampEn than the controls, which implied the stroke group has higher EEG complexity. For the brain network, the stroke group displayed a trend of weaker cortical connectivity, which suggests a functional impairment of information transmission in cortical connections in stroke patients. These findings suggest that nonlinear analysis and brain network could provide essential information for better understanding the brain dysfunction in the stroke and assisting monitoring or prognostication of stroke evolution. |
format | Online Article Text |
id | pubmed-4923597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-49235972016-07-11 Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke Liu, Shuang Guo, Jie Meng, Jiayuan Wang, Zhijun Yao, Yang Yang, Jiajia Qi, Hongzhi Ming, Dong Comput Math Methods Med Research Article Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional connectivity in patients with acute thalamic ischemic stroke and healthy subjects. Electroencephalography (EEG) in resting condition with eyes closed was recorded for 12 stroke patients and 11 healthy subjects as control group. Lempel-Ziv complexity (LZC), Sample Entropy (SampEn), and brain network using partial directed coherence (PDC) were calculated for feature extraction. Results showed that patients had increased mean LZC and SampEn than the controls, which implied the stroke group has higher EEG complexity. For the brain network, the stroke group displayed a trend of weaker cortical connectivity, which suggests a functional impairment of information transmission in cortical connections in stroke patients. These findings suggest that nonlinear analysis and brain network could provide essential information for better understanding the brain dysfunction in the stroke and assisting monitoring or prognostication of stroke evolution. Hindawi Publishing Corporation 2016 2016-06-14 /pmc/articles/PMC4923597/ /pubmed/27403202 http://dx.doi.org/10.1155/2016/2582478 Text en Copyright © 2016 Shuang Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Shuang Guo, Jie Meng, Jiayuan Wang, Zhijun Yao, Yang Yang, Jiajia Qi, Hongzhi Ming, Dong Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke |
title | Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke |
title_full | Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke |
title_fullStr | Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke |
title_full_unstemmed | Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke |
title_short | Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke |
title_sort | abnormal eeg complexity and functional connectivity of brain in patients with acute thalamic ischemic stroke |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923597/ https://www.ncbi.nlm.nih.gov/pubmed/27403202 http://dx.doi.org/10.1155/2016/2582478 |
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