Disorganized functional architecture of amygdala subregional networks in obsessive-compulsive disorder.
Lingxiao CaoHailong LiJing LiuJiaxin JiangBin LiXue LiSuming ZhangYingxue GaoKaili LiangXinyue HuWeijie BaoHui QiuLu LuLianqing ZhangXinyu HuQi-Yong GongXiaoqi HuangPublished in: Communications biology (2022)
A precise understanding of amygdala-centered subtle networks may help refine neurocircuitry models of obsessive-compulsive disorder (OCD). We applied connectivity-based parcellation methodology to segment the amygdala based on resting-state fMRI data of 92 medication-free OCD patients without comorbidity and 90 matched healthy controls (HC). The amygdala was parcellated into two subregions corresponding to basolateral amygdala (BLA) and centromedial amygdala (CMA). Amygdala subregional functional connectivity (FC) maps were generated and group differences were evaluated with diagnosis-by-subregion flexible factorial ANOVA. We found significant diagnosis × subregion FC interactions in insula, supplementary motor area (SMA), midcingulate cortex (MCC), superior temporal gyrus (STG) and postcentral gyrus (PCG). In HC, the BLA demonstrated stronger connectivity with above regions compared to CMA, whereas in OCD, the connectivity pattern reversed to stronger CMA connectivity comparing to BLA. Relative to HC, OCD patients exhibited hypoconnectivity between left BLA and left insula, and hyperconnectivity between right CMA and SMA, MCC, insula, STG, and PCG. Moreover, OCD patients showed reduced volume of left BLA and right CMA compared to HC. Our findings characterized disorganized functional architecture of amygdala subregional networks in accordance with structural defects, providing direct evidence regarding the specific role of amygdala subregions in the neurocircuitry models of OCD.
Keyphrases
- functional connectivity
- resting state
- obsessive compulsive disorder
- deep brain stimulation
- end stage renal disease
- ejection fraction
- newly diagnosed
- klebsiella pneumoniae
- prognostic factors
- healthcare
- escherichia coli
- multidrug resistant
- electronic health record
- patient reported outcomes
- adverse drug
- patient reported
- deep learning