The study of the relapsed patients with major depressive disorder based on spectral dynamic causal modeling
10.3969/j.issn.1002-1671.2018.06.002
- VernacularTitle:基于谱动态因果模型对重度抑郁症复发的研究
- Author:
Jiaming LI
1
;
Baojuan LI
;
Kaizhong ZHENG
;
Liang LI
;
Peng DU
;
Baoyu YAN
Author Information
1. 西安电子科技大学生命科学技术学院
- Keywords:
major depressive disorder;
spectral dynamic causal modeling;
resting-state functional magnetic resonance imaging
- From:
Journal of Practical Radiology
2018;34(6):824-827
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the effects of abnormal effective connectivity within the default mode network (DMN)in relapsed patients with major depressive disorder.Methods Resting-state functional magnetic resonance imaging (rs-fMRI)data were collected from 21 patients of first-episode depression and 16 patients with relapsed depression,and 37 matched healthy controls.The effective connectivity within the DMN was investigated with spectral dynamic causal modeling (spDCM)method.Results spDCM analysis showed that the effective connections from left parietal cortex(LPC)to right parietal cortex(RPC)and medial frontal cortex(mPFC)were significantly decreased,while the connection from posterior cingulate cortex(PCC)to mPFC was increased in patients of first episode depression compared to healthy controls.Furthermore,the connectivity between mPFC and LPC were enhanced in patients with recurrent depression compared withhealthy control subjects,as well as PCC.Meanwhile,the connectivity between mPFC and PCC was enhanced in patients with relapse depression compared with patients of first episode depression.Conclusion Both first-episode and relapsed patients demonstrated abnormal effective connectivity of LPC,implicating that abnormal LPC connectivity may be associated with the neural substrates of depression.In contrast,the patients with relapsed depression showed aberrant connectivity with the mPFC,suggesting that abnormal effective connectivity of the mPFC may play an important role in the relapse of depression.
