EEG Frontal Theta-Beta Ratio and Frontal Midline Theta for the Assessment of Social Anxiety Disorder

2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)(2020)

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摘要
Social anxiety disorder (SAD) is believed to be characterized by aberrant patterns of electrocortical activity during resting state and during performing social task, particularly increased slow waves activity and decreased high wave activity. The main objective of this work is to confirm whether individuals with SAD contribute to the finding of spectral power between theta and beta ratio (THBR) activity. The second objective is to compare the individual differences between resting-state brain oscillations and recovery from social performing task for SAD and healthy control (HC) groups. From 10 healthy participants (5 SAD and 5 HC), resting-state EEG during (eyes open, eyes closed) and during recovery from social performing task (self-presentation) was recorded. Social Interaction Anxiety Scale (SIAS) for SAD was administered to determine the severity level of social anxiety in all participants. As a result, findings reported here suggests that increased THBR and FMT may reflect a reduced frontal cortical activity over subcortical oscillations. In accordance with several findings, THBR was found to correlate negatively with the self-reported score of SIAS in SAD group but correlate positively with HC group. As we hypothesized, SAD individuals showed less FMT comparing to the HC group which indicates that FMT is a neurophysiological correlate on anxiety state more than anxiety trait. These results are steady with previous studies and support the concept that slow wave/ fast wave and FMT may provide a useful tool in the study of affect and the neural mechanism of emotion regulation. Together, our findings interpreted to suggest that THBR and FMT are possible neurobiological markers for SAD and can differentiate between state and trait SAD during resting state and social stressors.
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关键词
Theta/beta ratio,cross-frequency coupling,neurofeedback,neurophysiological biomarkers,spectral power density,functional connectivity
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