Resting‐State Functional Connectivity and Brain Network Abnormalities in Depressive Patients with Suicidal Ideation

Vincent Chin Hung Chen, Yu Syuan Chou, Yuan Hsiung Tsai, Yin Cheng Huang, Roger S. McIntyre, Jun Cheng Weng*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

16 Scopus citations

Abstract

Our study aimed to investigate whether changes in brain function measured with functional magnetic resonance imaging (fMRI) can be detected among individuals with depressive disorders and suicidal ideation. The association between depression severity and brain images is also discussed. Our study recruited 111 participants in three groups: 35 depressive patients with suicidal ideation (SI), 32 depressive patients without suicidal ideation (NS), and 44 healthy controls (HCs). All participants were scanned using 3T MRI to obtain resting-state functional images, and functional connectivity (FC), amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and graph theoretical analysis (GTA) were performed. We found functional activity differences, such as the hippocampus and thalamus, in the SI group compared with the NS group. We also concluded lower activity in the thalamus and cuneus regions were related to suicidal ideation. We also found several functional connectivity of the brain areas, such as hippocampus, cuneus, and frontal regions, in the SI group correlated with Hamilton Depression Rating Scale (HAM-D) and Hospital Anxiety and Depression Scale (HADS). A graph theoretical analysis (GTA) and network-based statistical (NBS) analysis revealed different topological organization and slightly better local segregation of the brain network in healthy participants compared with those in depressive patients with suicidal ideation. We suggest that brain functional connectivity may be affected in depressive patients with suicidal ideation.

Original languageEnglish
Pages (from-to)234-244
Number of pages11
JournalBrain Topography
Volume34
Issue number2
DOIs
StatePublished - 03 2021

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

Keywords

  • Graph theoretical analysis
  • Network‐based statistical analysis
  • Resting‐state functional connectivity
  • Suicidal ideation

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