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Review of EEG, ERP, and Brain Connectivity Estimators as Predictive Biomarkers of Social Anxiety Disorder

机译:eEG,ERP和脑连接估计的审查作为社会焦虑症的预测生物标志物

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Social anxiety disorder (SAD) is characterised by a fear of negative evaluation, negative self-belief and extreme avoidance of social situations. These recurrent symptoms are thought to maintain the severity and substantial impairment in social and cognitive thoughts. SAD is associated with a disruption in neuronal networks implicated in emotional regulation, perceptual stimulus functions, and emotion processing, suggesting a network system to delineate the electrocortical endophenotypes of SAD. This paper seeks to provide a comprehensive review of the most frequently studied electroencephalographic (EEG) spectral coupling, event-related potential (ERP), visual-event potential (VEP), and other connectivity estimators in social anxiety during rest, anticipation, stimulus processing, and recovery states. A search on Web of Science provided 97 studies that document electrocortical biomarkers and relevant constructs pertaining to individuals with SAD. This study aims to identify SAD neuronal biomarkers and provide insight into the differences in these biomarkers based on EEG, ERPs, VEP, and brain connectivity networks in SAD patients and healthy controls (HC). Furthermore, we proposed recommendations to improve methods of delineating the electrocortical endophenotypes of SAD, e.g., a fusion of EEG with other modalities such as functional magnetic resonance imaging (fMRI) and magnetoencephalograms (MEG), to realise better effectiveness than EEG alone, in order to ultimately evolve the treatment selection process, and to review the possibility of using electrocortical measures in the early diagnosis and endophenotype examination of SAD.
机译:社交焦虑症(悲伤)的特点是担心消极评估,消极的自信和极端避免社交场合。这些复发症状被认为保持社会和认知思想中的严重程度和大量损害。悲伤与神经网络中的破坏相关,涉及情绪调节,感知刺激功能和情感加工,建议一个网络系统描绘悲伤的蠕动内肌型。本文旨在提供对最常见的脑电图(EEG)光谱耦合,事件相关潜力(ERP),视觉事件潜力(VEP)以及社交焦虑的其他连通性估算,以及在休息期间的其他连通性估算,提供全面的审查和恢复国家。搜索科学网提供97个研究,其中记录了与悲伤的个人有关的有关的相关构建体。本研究旨在识别悲伤的神经元生物标志物,并在悲伤患者和健康对照(HC)中,对基于EEG,ERP,VEP和脑连接网络的这些生物标志物的差异提供洞察。此外,我们提出了提高划清伤病的电沉噬素型的方法的建议,例如,eeg的融合与诸如功能磁共振成像(FMRI)和磁性脑图(MEG)的其他方式,以实现比eeg更好的效果,按顺序实现更好的效果最终进化治疗选择过程,并审查在悲伤的早期诊断和内胚型检查中使用电蚀刻的可能性。

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