Paper Info
Title
Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke.
Abstract
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.
Year
DOI
Venue
2016
10.1155/2016/2582478
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Field
DocType
Volume
Brain mapping,Thalamus,Neuroscience,Sample entropy,Artificial intelligence,Electroencephalography,Disease,Brain ischemia,Case-control study,Internal medicine,Cardiology,Psychology,Stroke,Machine learning
Journal
2016
ISSN
Citations 
PageRank 
1748-670X
1
0.36
References 
Authors
7
8
Name
Order
Citations
PageRank
Shuang Liu13622.95
Jie Guo210.36
Jiayuan Meng3162884.35
Zhijun Wang410.36
Yang Yao510.36
Jiajia Yang6167.51
Hongzhi Qi74920.61
Dong Ming810551.47