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• Clinical Article •
Functional connectivity within the default mode network can predict the sleep disturbance scores of the patients with depression
QIN Jiaolong  LI Hongxuan  WU Ye  NI Huangjing 

Cite this article as: QIN J L, LI H X, WU Y, et al. Functional connectivity within the default mode network can predict the sleep disturbance scores of the patients with depression[J]. Chin J Magn Reson Imaging, 2024, 15(7): 51-57. DOI:10.12015/issn.1674-8034.2024.07.009.


[Abstract] Objective To explore whether the functional connectivity (FC) of the default mode network (DMN) can predict the sleep disturbance scores of the patients with major depressive disorder (MDD).Materials and Methods The resting functional magnetic resonance imaging data of 326 patients with MDD from the REST-meta-MDD project were included after undergoing rigorous selection based on the experimental criteria. The entire brain was defined into 256 regions based on the Power template, followed by separate extraction of the FC of the intra- and inter- DMN. Connectome-based predictive modeling was employed to regress individual sleep disturbance score using both types of FC feature, and the experimental findings would be subsequently validated on an external independent validation dataset.Results The predictive model based on the intra-FC of the DMN demonstrated significant prediction capability for sleep disturbance scores in individuals with depression, not only in the discovery dataset (r=0.244, P<0.001), but also in the external validation dataset (r=0.345, P=0.046). However, models based on the inter-FC of the DMN exhibited limited prediction ability and can only predict the scores in the discovery dataset (r=0.238, P<0.001), failing to generalize to the external validation dataset (r=0.256, P=0.143).Conclusions The intra-FC of DMN demonstrates predictive capability for the sleep disturbance scores in patients with MDD in some extent.
[Keywords] depression；sleep disturbance；default mode network；resting-state functional magnetic resonance imaging；magnetic resonance imaging

QIN Jiaolong1, 2*   LI Hongxuan1, 2   WU Ye1, 2   NI Huangjing3*  

1 Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210014, China

2 Jiangsu Key Lab of Image and Video Understanding for Social Security, School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210014, China

3 School of Computer Science, School of Software, School of Cyberspace Security, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Corresponding author: NI H J, E-mail: nihuangjing@njupt.edu.cn QIN J L, E-mail: jiaolongq@njust.edu.cn

Conflicts of interest   None.

Received  2024-01-19
Accepted  2024-06-06
DOI: 10.12015/issn.1674-8034.2024.07.009
Cite this article as: QIN J L, LI H X, WU Y, et al. Functional connectivity within the default mode network can predict the sleep disturbance scores of the patients with depression[J]. Chin J Magn Reson Imaging, 2024, 15(7): 51-57. DOI:10.12015/issn.1674-8034.2024.07.009.

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