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

  • Hao He
  • , Jing Sui*
  • , Yuhui Du
  • , Qingbao Yu
  • , Dongdong Lin
  • , Wayne C. Drevets
  • , Jonathan B. Savitz
  • , Jian Yang
  • , Teresa A. Victor
  • , Vince D. Calhoun
  • *此作品的通讯作者
  • The Mind Research Network
  • University of New Mexico
  • CAS - Institute of Automation
  • Chinese Academy of Sciences
  • School of Computer and Information Technology
  • Shanxi University
  • Johnson & Johnson
  • Laureate Institute for Brain Research
  • Beijing Institute of Technology
  • Yale University

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

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.

源语言英语
页(从-至)4051-4064
页数14
期刊Brain Structure and Function
卷222
期9
DOI
出版状态已出版 - 1 12月 2017
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