4.6 Article

Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders

Journal

BRAIN STRUCTURE & FUNCTION
Volume 222, Issue 9, Pages 4051-4064

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s00429-017-1451-x

Keywords

Bipolar disorders; Major depressive disorder; Functional network connectivity; Gray matter density; Multimodal fusion; mCCA plus jICA

Funding

  1. National High-Tech Development Plan (863 plan) [2015AA020513]
  2. Strategic Priority Research Program of the Chinese Academy of Sciences [XDB02060005]
  3. 100 Talents Plan'' of the Chinese Academy of Sciences
  4. Chinese National Science Foundation [81471367]
  5. NIH via a COBRE Grant [P20GM103472, R01EB005846, 1R01EB006841]
  6. William K. Warren Foundation

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Bipolar disorder (BD) and major depressive disorder (MDD) share similar clinical characteristics that often obscure the diagnostic distinctions between their depressive conditions. Both functional and structural brain abnormalities have been reported in these two disorders. However, the direct link between altered functioning and structure in these two diseases is unknown. To elucidate this relationship, we conducted a multimodal fusion analysis on the functional network connectivity (FNC) and gray matter density from MRI data from 13 BD, 40 MDD, and 33 matched healthy controls (HC). A data-driven fusion method called mCCA+jICA was used to identify the co-altered FNC and gray matter components. Comparing to HC, BD exhibited reduced gray matter density in the parietal and occipital cortices, which correlated with attenuated functional connectivity within sensory and motor networks, as well as hyper-connectivity in regions that are putatively engaged in cognitive control. In addition, lower gray matter density was found in MDD in the amygdala and cerebellum. High accuracy in discriminating across groups was also achieved by trained classification models, implying that features extracted from the fusion analysis hold the potential to ultimately serve as diagnostic biomarkers for mood disorders.

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