Literature DB >> 21362744

Resting-state functional connectivity in treatment-resistant depression.

Su Lui1, Qizhu Wu, Lihua Qiu, Xun Yang, Weihong Kuang, Raymond C K Chan, Xiaoqi Huang, Graham J Kemp, Andrea Mechelli, Qiyong Gong.   

Abstract

OBJECTIVE: The authors used resting-state functional connectivity MRI to evaluate brain networks in patients with refractory and nonrefractory major depressive disorder.
METHOD: In a cross-sectional study, 28 patients with refractory major depression, 32 patients with nonrefractory major depression, and 48 healthy comparison subjects underwent scanning using a gradient-echo echo-planar imaging sequence on a 3-T MR system. Thirteen regions of interest that have been identified in the literature as relevant to mood regulation were selected as seed areas. A reference time series was extracted for each seed and used for voxel-wise correlation analysis with the rest of the brain. Voxel-based comparisons of z-value maps among the three groups were performed using one-way analysis of variance followed by post hoc t tests with age and duration of illness as covariates of no interest.
RESULTS: Relative to healthy comparison subjects, both patient groups showed significantly reduced connectivity in prefrontal-limbic-thalamic areas bilaterally. However, the nonrefractory group showed a more distributed decrease in connectivity than the refractory group, especially in the anterior cingulate cortex and in the amygdala, hippocampus, and insula bilaterally; in contrast, the refractory group showed disrupted functional connectivity mainly in prefrontal areas and in thalamus areas bilaterally.
CONCLUSIONS: Refractory depression is associated with disrupted functional connectivity mainly in thalamo-cortical circuits, while nonrefractory depression is associated with more distributed decreased connectivity in the limbic-striatal-pallidal-thalamic circuit. These results suggest that nonrefractory and refractory depression are characterized by distinct functional deficits in distributed brain networks.

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Year:  2011        PMID: 21362744     DOI: 10.1176/appi.ajp.2010.10101419

Source DB:  PubMed          Journal:  Am J Psychiatry        ISSN: 0002-953X            Impact factor:   18.112


  116 in total

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