AUTHOR=Al-Ezzi Abdulhakim , Kamel Nidal , Faye Ibrahima , Gunaseli Esther TITLE=Review of EEG, ERP, and Brain Connectivity Estimators as Predictive Biomarkers of Social Anxiety Disorder JOURNAL=Frontiers in Psychology VOLUME=11 YEAR=2020 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2020.00730 DOI=10.3389/fpsyg.2020.00730 ISSN=1664-1078 ABSTRACT=

Social anxiety disorder (SAD) is characterized 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 realize 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.