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Article

Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study

1
Centre for Intelligent Signal and Imaging Research (CISIR), Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia
2
Psychiatry Discipline Sub Unit, Universiti Kuala Lumpur Royal College of Medicine Perak, Ipoh 30450, Malaysia
*
Author to whom correspondence should be addressed.
Academic Editors: Gianluca Esposito and Andrea Bizzego
Sensors 2021, 21(12), 4098; https://doi.org/10.3390/s21124098
Received: 24 February 2021 / Revised: 7 April 2021 / Accepted: 9 April 2021 / Published: 15 June 2021
(This article belongs to the Special Issue Brain Signals Acquisition and Processing)
Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1–3 Hz), theta (4–8 Hz), alpha (8–12 Hz), low beta (13–21 Hz), and high beta (22–30 Hz). Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta (p = 0.009) and alpha (p = 0.001) bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, HC exhibited higher resting-state connectivity at the mPFC, providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = −0.689, p = 0.001. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication. View Full-Text
Keywords: effective connectivity network; partial directed coherence (PDC); social anxiety disorder (SAD); default mode network (DMN); electrophysiological biomarkers (EEG); resting state network (RSN); Granger causality (GC) effective connectivity network; partial directed coherence (PDC); social anxiety disorder (SAD); default mode network (DMN); electrophysiological biomarkers (EEG); resting state network (RSN); Granger causality (GC)
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MDPI and ACS Style

Al-Ezzi, A.; Kamel, N.; Faye, I.; Gunaseli, E. Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study. Sensors 2021, 21, 4098. https://doi.org/10.3390/s21124098

AMA Style

Al-Ezzi A, Kamel N, Faye I, Gunaseli E. Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study. Sensors. 2021; 21(12):4098. https://doi.org/10.3390/s21124098

Chicago/Turabian Style

Al-Ezzi, Abdulhakim, Nidal Kamel, Ibrahima Faye, and Esther Gunaseli. 2021. "Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study" Sensors 21, no. 12: 4098. https://doi.org/10.3390/s21124098

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