Same salience, different consequences: Disturbed inter-network connectivity during a social oddball paradigm in major depressive disorder

Graph theoretical analysis and independent component analysis of diabetic optic neuropathy: A resting-state functional magnetic resonance imaging study

AIMS

This study aimed to investigate the resting-state functional connectivity and topologic characteristics of brain networks in patients with diabetic optic neuropathy (DON).

METHODS

Resting-state functional magnetic resonance imaging scans were performed on 23 patients and 41 healthy control (HC) subjects. We used independent component analysis and graph theoretical analysis to determine the topologic characteristics of the brain and as well as functional network connectivity (FNC) and topologic properties of brain networks.

RESULTS

Compared with HCs, patients with DON showed altered global characteristics. At the nodal level, the DON group had fewer nodal degrees in the thalamus and insula, and a greater number in the right rolandic operculum, right postcentral gyrus, and right superior temporal gyrus. In the internetwork comparison, DON patients showed significantly increased FNC between the left frontoparietal network (FPN-L) and ventral attention network (VAN). Additionally, in the intranetwork comparison, connectivity between the left medial superior frontal gyrus (MSFG) of the default network (DMN) and left putamen of auditory network was decreased in the DON group.

CONCLUSION

DON patients altered node properties and connectivity in the DMN, auditory network, FPN-L, and VAN. These results provide evidence of the involvement of specific brain networks in the pathophysiology of DON.

Disrupted default mode network and executive control network are associated with depression severity on structural network

OBJECTIVE

Major depressive disorder (MDD) is a psychiatric disorder with a relatively limited response to treatment. It is necessary to better understand the neuroanatomical mechanisms of structural networks.

METHODS

The current study recruited 181 first-onset, untreated adult MDD patients: slight MDD (SD, N = 23), moderate MDD (MD, N = 77), Heavy MDD (HD, N = 81) groups; along with a healthy control group (HC, N = 81) with matched general clinical data. FreeSurfer was used to preprocess T1 images for gray matter volume (GMV), and the default mode network (DMN) and the execution control network (ECN) were analyzed by structural covariance network (SCN).

RESULTS

Present study found that the GMV of brain regions reduced with the severity of the disease. Specifically, the GMV of the left anterior cingulate gyrus (ACC.L) is negatively correlated with MDD severity. In addition, the SCN connectivity of the whole-brain network increases with the increase of severity in MDD. ACC.L is a key brain region with increased connectivity between the left orbitofrontal in DMN and between the right orbitofrontal in ECN, which leads to damage to the balance of neural circuits.

CONCLUSIONS

Patients with smaller GMV of ACC.L are more likely to develop severe MDD, and as a key region in both networks which have distinct structural network models in DMN and ECN. MDD patients with different severity have different neuroimaging changes in DMN and ECN.