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The impact of insomnia on brain networks topology in depressed patients: A resting-state fMRI study.
Chen, Lei; Zhang, Zhu-Qing; Li, Zhao-Xue; Qu, Miao; Liao, Dan; Guo, Zhi-Peng; Li, De-Chun; Liu, Chun-Hong.
Afiliação
  • Chen L; Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China.
  • Zhang ZQ; Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266003, China.
  • Li ZX; Department of Neurological Rehabilitation, Xuzhou Rehabilitation Hospital, Xuzhou 221010, China.
  • Qu M; Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China.
  • Liao D; Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China.
  • Guo ZP; Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China.
  • Li DC; Department of Radiology, Xuzhou Central Hospital, Xuzhou 221009, China. Electronic address: 18952171358@189.cn.
  • Liu CH; Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing 100010, China. Electronic address: liuchunhong@bjzhongyi.com.
Brain Res ; 1844: 149169, 2024 Aug 22.
Article em En | MEDLINE | ID: mdl-39179194
ABSTRACT

OBJECTIVE:

Depression and insomnia frequently co-occur, but the neural mechanisms between patients with varying degrees of these conditions are not fully understood. The specific topological features and connectivity patterns of this co-morbidity have not been extensively studied. This study aimed to investigate the topological characteristics of topological characteristics and functional connectivity of brain networks in depressed patients with insomnia.

METHODS:

Resting-state functional magnetic resonance imaging data from 32 depressed patients with a high level of insomnia (D-HI), 35 depressed patients with a low level of insomnia (D-LI), and 81 healthy controls (HC) were used to investigate alterations in brain topological organization functional networks. Nodal and global properties were analyzed using graph-theoretic techniques, and network-based statistical analysis was employed to identify changes in brain network functional connectivity.

RESULTS:

Compared to the HC group, both the D-HI and D-LI groups showed an increase in the global efficiency (Eglob) values, local efficiency (Eloc) was decreased in the D-HI group, and Lambda and shortest path length (Lp) values were decreased in the D-LI group. At the nodal level, the right parietal nodal clustering coefficient (NCp) values were reduced in D-HI and D-LI groups compared to those in HC. The functional connectivity of brain networks in patients with D-HI mainly involves default mode network (DMN)-cingulo-opercular network (CON), DMN-visual network (VN), DMN-sensorimotor network (SMN), and DMN-cerebellar network (CN), while that in patients with D-LI mainly involves SMN-CON, SMN-SMN, SMN-VN, and SMN-CN. The values of the connection between the midinsula and postoccipital gyrus was negatively correlated with scores for early awakening in D-HI.

CONCLUSION:

These findings may contribute to our understanding of the underlying neuropsychological mechanisms in depressed patients with insomnia.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Brain Res Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Brain Res Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China