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. 2020 Aug 15;41(12):3295-3304.
doi: 10.1002/hbm.25017. Epub 2020 May 13.

Resting state functional network switching rate is differently altered in bipolar disorder and major depressive disorder

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Resting state functional network switching rate is differently altered in bipolar disorder and major depressive disorder

Shaoqiang Han et al. Hum Brain Mapp. .

Abstract

The clinical misdiagnosis ratio of bipolar disorder (BD) patients to major depressive disorder (MDD) patients is high. Recent findings hypothesize that the ability to flexibly recruit functional neural networks is differently altered in BD and MDD patients. This study aimed to explore distinct aberrance of network flexibility during dynamic networks configuration in BD and MDD patients. Resting state functional magnetic resonance imaging of 40 BD patients, 61 MDD patients, and 61 matched healthy controls were recruited. Dynamic functional connectivity matrices for each subject were constructed with a sliding window method. Then, network switching rate of each node was calculated and compared among the three groups. BD and MDD patients shared decreased network switching rate of regions including left precuneus, bilateral parahippocampal gyrus, and bilateral dorsal medial prefrontal cortex. Apart from these regions, MDD patients presented specially decreased network switching rate in the bilateral anterior insula, left amygdala, and left striatum. Taken together, BD and MDD patients shared decreased network switching rate of key hubs in default mode network and MDD patients presented specially decreased switching rate in salience network and striatum. We found shared and distinct aberrance of network flexibility which revealed altered adaptive functions during dynamic networks configuration of BD and MDD.

Keywords: bipolar disorder; dynamic networks configuration; fMRI; major depressive disorder; multilayer network method; network switching rate.

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Conflict of interest statement

All authors declared no conflict of interest.

Figures

FIGURE 1
FIGURE 1
(a) Flow chart of analysis steps. The original images were preprocessed. The mean values of 246 atlas were extracted to build dynamic functional matrix for each subject. Then, an iterative and ordinal Louvain algorithm was used to track dynamic network modulation over time. Finally, network switching rate was calculated and compared among three groups with ANOVA. (b) An overview of network switching rate. The windows meant the sliding windows in dynamic functional connectivity. The red and blue nodes represented nodes in two different modularity partitions. There were two switching events in this figure (adapted from Mangor et al.)
FIGURE 2
FIGURE 2
Shared decreased network switching rate of BD and MDD patients. L.dMPFC, left dorsal medial prefrontal cortex; L.Pcun, left precuneus
FIGURE 3
FIGURE 3
Specially decreased networking rate in MDD patients. L.lAmy, left lateral amygdale; R.STG, right superior temporal gyrus; R.PHG, right parahippocampal gyrus
FIGURE 4
FIGURE 4
Regions presenting lower network switching rate in MDD patients compared with BD patient. L.Fug, fusiform gyrus; L.rPhG, left rostral parahippocampal gyrus; L.EC, left entorhinal cortex; L.dAIC, left dorsal anterior insula cortex; L.mAmy, left medial amygdale; L.Hip, left hippocampus; L.str, left stritum; R.cAIC, right caudoventral anterior insula cortex

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