Electroconvulsive therapy enhances degree centrality in the orbitofrontal cortex in depressive rumination.

Depressive rumination has been implicated in the onset, duration, and treatment response of refractory depression. Electroconvulsive therapy (ECT) is remarkably effective in treatment of refractory depression by modulating the functional coordination between brain hubs. However, the mechanisms by which ECT regulates depressive rumination remain unsolved. We investigated degree centrality (DC) in 32 pre- and post-ECT depression patients as well as 38 matched healthy controls. An identified brain region was defined as the seed to calculate functional connectivity (FC) in whole brains. Rumination was measured by the Ruminative Response Scale (RRS) and its relationships with identified DC and FC alterations were examined. We found a significant negative correlation between DC of the right orbitofrontal cortex (rOFC) before ECT and brooding level before and after treatment. Moreover, rOFC DC increased after ECT. DC of the left superior temporal gyrus (lSTG) was positively correlated with reflective level before intervention, while lSTG DC decreased after ECT. Patients showed elevated FC in the rOFC with default mode network. No significant association was found between decreased RRS scores and changes in DC and FC. Our findings suggest that functional changes in rOFC and lSTG may be associated with the beneficial effects of ECT on depressive rumination.

Altered brain entropy and functional connectivity patterns in generalized anxiety disorder patients.

BACKGROUND: Generalized anxiety disorder (GAD) is a highly prevalent disease characterized by chronic, pervasive, and intrusive worry. Previous resting-state functional MRI (fMRI) studies on GAD have mainly focused on conventional static linear features. Entropy analysis of resting-state functional magnetic resonance imaging (rs-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. However, the nonlinear dynamic complexity of brain signals has been rarely explored in GAD. METHODS: We measured the approximate entropy (ApEn) and sample entropy (SampEn) of the resting-state fMRI data from 38 GAD patients and 37 matched healthy controls (HCs). The brain regions with significantly different ApEn and SampEn values between the two groups were extracted. Using these brain regions as seed points, we also investigated whether there are differences in whole brain resting-state function connectivity (RSFC) pattern between GADs and HCs. Correlation analysis was subsequently conducted to investigate the association between brain entropy, RSFC and the severity of anxiety symptoms. A linear support vector machine (SVM) was used to assess the discriminative power of BEN and RSFC features among GAD patients and HCs. RESULTS: Compared to the HCs, patients with GAD showed increased levels of ApEn in the right angular cortex (AG) and increased levels of SampEn in the right middle occipital gyrus (MOG) as well as the right inferior occipital gyrus (IOG). Contrarily, compared to the HCs, patients with GAD showed decreased RSFC between the right AG and the right inferior parietal gyrus (IPG). The SVM-based classification model achieved 85.33 % accuracy (sensitivity: 89.19 %; specificity: 81.58 %; and area under the receiver operating characteristic curve: 0.9018). The ApEn of the right AG and the SVM-based decision value was positively correlated with the Hamilton Anxiety Scale (HAMA). LIMITATIONS: This study used cross-sectional data and sample size was small. CONCLUSION: Patients with GAD showed increased level of nonlinear dynamical complexity of ApEn in the right AG and decreased linear features of RSFC in the right IPG. Combining the linear and nonlinear features of brain signals may be used to effectively diagnose psychiatric disorders.