EEG Network in Low-Beta as Biomarkers for Distinguishing PTSD, Panic, and Other Anxiety Disorders
Poster No:
685
Submission Type:
Abstract Submission
Authors:
Minhee Kim1, Deung-Hyun Kang2, Soo-Hee Choi1
Institutions:
1Department of Psychiatry, Seoul National University Hospital, Seoul, Korea, Republic of, 2Department of Psychiatry, SMG-SNU BoramaeMedical Center Seoul, Seoul, Korea, Republic of
First Author:
Co-Author(s):
Deung-Hyun Kang
Department of Psychiatry, SMG-SNU BoramaeMedical Center Seoul
Seoul, Korea, Republic of
Department of Psychiatry, SMG-SNU BoramaeMedical Center Seoul
Seoul, Korea, Republic of
Introduction:
Anxiety disorder is one of the highest rates of comorbidity in patients with posttraumatic stress disorder (PTSD) (Brady et al., 2000). And these disorders are similar in having anxiety related symptoms. PTSD patients with anxiety disorder showed decreased psychosocial function than the PTSD only patients (Ginzburg et al., 2010). Thus, for its proper diagnosis and treatment, it is important to discover what is different and same between PTSD and anxiety disorders. EEG connectivity network could reflect individuals' mental states and has beneficial to employing in clinical settings (Choi et al., 2021). In previous studies, disrupted brain network was discovered in PTSD (Shim et al., 2017). However, there's only few studies about brain network on anxiety disorder except social anxiety. Hence, in the present study, we aimed to investigate whether the brain network from resting-state EEG could distinguish PTSD, panic disorder, and other anxiety disorders on which frequency band.
Methods:
Patients with PTSD (N=30), panic disorder (N=32), and other anxiety disorders (N=30) were recruited. Resting-state EEGs were recorded for 20 minutes with eyes closed. The data were pre-processed as following: band-pass filtering at 0.1-50Hz, average referencing, artifact rejection by visual inspection and ICA. Phase-locking values (PLVs) were calculated between each pair of channels and averaged for each frequency band (delta: 0.5-4Hz; theta: 4-8Hz; alpha: 8-12Hz; low-beta: 12-22Hz; high-beta: 22-30Hz; gamma: 30-50Hz). For further graph theoretical analysis, connectivity matrices were constructed using PLV values. In network analysis, global network indices including strength (STR), path length (PL), clustering coefficient (CC), and efficiency (EFF) were evaluated and averaged across participants for each disorder group. We conducted one-way ANOVAs to find significant group differences with each global network index as dependent variable, and post-hoc t-tests on significant network indices.
Results:
The one-way ANOVA revealed that there was a significant difference in patient groups on low-beta band for all network indices: STR (F(2, 89)=3.05, p<.05), PL ( F(2, 89)=.52, p<.05), CC (F(2, 89)=.008, p<.05), and EFF (F(2, 89)=2.97, p=.057) with trend level. Thus, in further t-tests, we analyzed group differences for these four network indices on low-beta band. Post-hoc t-tests between PTSD and anxiety disorder groups showed that the anxiety disorder was greater than the PTSD for the STR (t(58)=2.34, p=.02), CC (t(58)=2.28, p=.03), and EFF (t(58)=2.30, p=.03), and the PTSD was greater for the PL (t(58)=2.35, p=.02). Likewise, the same t-tests between panic and anxiety disorder groups showed that the anxiety disorder was greater than the panic disorder for the STR (t(60)=2.11, p=.04), CC (t(60)=2.14, p=.04), and EFF (t(60)=2.02, p=.048), and the panic disorder was greater for the PL (t(60)=2.51, p=.02). And there was no significant difference between for any network index between the PTSD and panic disorder groups.
·results of strength(STR) and path length(PL) between patient groups
·results of clustering coefficient(CC) and path efficiency(EFF) between patient groups
Conclusions:
In this resting-state EEG study, we revealed that the brain network STR, CC, and EFF on low-beta band were greater, and PL was lesser on the patients with other anxiety disorders than the patients with PTSD and panic disorder. Given that the larger values of STR, CC, and EFF, and the lower value of PL reflect relative effective brain functional network, these results imply that in the other anxiety disorders their brain functional connectivity might be relatively closer to normal, compared to PTSD or panic disorder. In the previous study, patients with PTSD showed the lesser STR, CC, and EFF, and the greater PL on delta, theta, and low-beta band than control (Shim et al., 2017). And in the present study, we only found significant differences between patient groups on the low-beta band. This means that the brain network indices on the low-beta band could be biomarkers for discriminating the other anxiety disorders from the PTSD and panic disorder.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Keywords:
Anxiety
Electroencephaolography (EEG)
Other - PTSD; anxiety disorder; panic disorder; resting-state; connectivity; phase-locking value; network
1|2Indicates the priority used for review
Provide references using author date format
Choi, K. M., Kim, J. Y., Kim, Y. W., Han, J. W., Im, C. H., & Lee, S. H. (2021), 'Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG', Scientific reports, 11(1), 22007.
Ginzburg, K., Ein-Dor, T., & Solomon, Z. (2010), 'Comorbidity of posttraumatic stress disorder, anxiety and depression: a 20-year longitudinal study of war veterans', Journal of affective disorders, 123(1-3), 249-257.
Shim, M., Im, C. H., & Lee, S. H. (2017), 'Disrupted cortical brain network in post-traumatic stress disorder patients: a resting-state electroencephalographic study', Translational psychiatry, 7(9), e1231-e1231.