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Cortical Functional Activity in Patients with Generalized Anxiety Disorder

Overview
Journal BMC Psychiatry
Publisher Biomed Central
Specialty Psychiatry
Date 2016 Jul 9
PMID 27388467
Citations 14
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Abstract

Background: The neurological correlates of Generalised Anxiety Disorder (GAD) are not well known, however there is evidence of cortical dysregulation in patients with GAD. The aim of the study was to examine cortical functional activity in different cerebral regions in patients with GAD using electroencephalogram (EEG) nonlinear analysis to evaluate its contribution of anxiety severity.

Methods: The cohorts consisted of 64 patients diagnosed with GAD as classified by the Structured Clinical Interview for the Diagnostic and Statistical Manual of the American Psychiatric Association-IV-TR. Anxiety severity was assessed using the Hamilton Rating Scale for Anxiety (HAMA) severity score, with 7 ≤ scores ≤ 17 indicating mild anxiety as A group (n = 31) and 18 and above indicating moderate-severe anxiety as B group (n = 33). Participants with clinical levels of depression symptoms were excluded. A healthy control group comprising 30 participants was matched for age and gender. Closed eyes EEGs were conducted, and between-group differences on non-linear parameter Correlation Dimension (D2) were analyzed. The association of D2 value with HAMA scores was analyzed using multiple linear stepwise regression.

Results: Compared with the control group, D2 values were increased in anxiety groups (P < .05). For those with mild anxiety, this difference occurred in the left prefrontal regions (P < .05). For those with moderate-severe anxiety, significantly greater D2 values were observed in all of the cerebral regions, especially in the left cerebral regions and right temporal lobe (P < .01). When compared with those with mild anxiety, D2 values were significantly greater for those with moderate-severe anxiety in the right temporal lobe and all left cerebral regions except for left occipital lobe (P < .05). A positive correlation was observed between D2 values and moderate-severe anxiety HAMA scores.

Conclusions: The increased D2 values were found in the majority of cerebral regions in GAD patients, especially in the left cerebral regions and the right temporal lobe. The increased GAD severity positively correlates to the D2 values in a larger number of cerebral regions. This analysis method can potentially be used as a complementary tool to examine dysfunctional cortical activity in GAD.

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References
1.
Hosseinifard B, Moradi M, Rostami R . Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal. Comput Methods Programs Biomed. 2012; 109(3):339-45. DOI: 10.1016/j.cmpb.2012.10.008. View

2.
SKINNER J, Carpeggiani C, Landisman C, Fulton K . Correlation dimension of heartbeat intervals is reduced in conscious pigs by myocardial ischemia. Circ Res. 1991; 68(4):966-76. DOI: 10.1161/01.res.68.4.966. View

3.
Sumich A, Harris A, Flynn G, Whitford T, Tunstall N, Kumari V . Event-related potential correlates of depression, insight and negative symptoms in males with recent-onset psychosis. Clin Neurophysiol. 2006; 117(8):1715-27. DOI: 10.1016/j.clinph.2006.04.017. View

4.
Jeong J, Chae J, Kim S, Han S . Nonlinear dynamic analysis of the EEG in patients with Alzheimer's disease and vascular dementia. J Clin Neurophysiol. 2001; 18(1):58-67. DOI: 10.1097/00004691-200101000-00010. View

5.
Stam C, van Woerkom T, Pritchard W . Use of non-linear EEG measures to characterize EEG changes during mental activity. Electroencephalogr Clin Neurophysiol. 1996; 99(3):214-24. DOI: 10.1016/0013-4694(96)95638-2. View