Prolonged disease course leads to impaired brain function in anxiety disorder: a resting state EEG study

Author:

Mou Shaoqi1,Yan Shiyu1,Shen Shanhong2,Shuai Yibin2,Li Gang3,Shen Zhongxia2,Ping Shen2

Affiliation:

1. Wenzhou Medical University,Wenzhou

2. Huzhou Third Municipal Hospital, the Affiliated Hospital of Huzhou University

3. Zhejiang Normal University

Abstract

Abstract Objective Anxiety disorder (AD) is a common disabling disease. The prolonged disease course may lead to impaired cognitive performance, brain function, and a bad prognosis. Few studies have examined the effect of disease course on brain function by electroencephalogram (EEG).Methods Resting-state EEG analysis was performed in 34 AD patients. The 34 patients with AD were divided into two groups according to the duration of their illness: anxious state (AS) and generalized anxiety disorder (GAD). Then, EEG features, including univariate power spectral density (PSD), fuzzy entropy (FE), and multivariable functional connectivity (FC), were extracted and compared between AS and GAD. These features were evaluated by three previously validated machine learning methods to test the accuracy of classification in AS and GAD.Results Significant decreased PSD and FE in GAD were detected compared with AS, especially in the alpha 2 band. In addition, FC analysis indicated that GAD patients’ connection between the left and right hemispheres decreased. Based on machine learning, AS and GAD are classified on a six-month criterion with the highest classification accuracy of up to 0.99 ± 0.0015.Conclusion The brain function of patients is more severely impaired in AD patients with longer illness duration. Resting-state EEG demonstrated to be a promising examination in the classification in GAD and AS using machine learning methods with better classification accuracy.

Publisher

Research Square Platform LLC

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