Altered dynamic effective connectivity of the default mode network in type 2 diabetes

Kun Xu; Jun Wang; Guangyao Liu; Jiahao Yan; Miao Chang; Linzhen Jiang; Jing Zhang

doi:10.3389/fneur.2023.1324988

Altered dynamic effective connectivity of the default mode network in type 2 diabetes

Front Neurol. 2024 Jan 15:14:1324988. doi: 10.3389/fneur.2023.1324988. eCollection 2023.

Authors

Kun Xu^{1

2}, Jun Wang^{1

2}, Guangyao Liu^{2

3}, Jiahao Yan^{1

2}, Miao Chang^{1

2}, Linzhen Jiang^{1

2}, Jing Zhang^{2

3}

Affiliations

¹ Second Clinical School, Lanzhou University, Lanzhou, China.
² Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.
³ Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou University Second Hospital, Lanzhou, China.

Abstract

Introduction: Altered functional connectivity of resting-state functional magnetic resonance imaging (rs-fMRI) within default mode network (DMN) regions has been verified to be closely associated with cognitive decline in patients with Type 2 diabetes mellitus (T2DM), but most studies neglected the fluctuations of brain activities-the dynamic effective connectivity (DEC) within DMN of T2DM is still unknown.

Methods: For the current investigation, 40 healthy controls (HC) and 36 T2DM patients have been recruited as participants. To examine the variation of DEC between T2DM and HC, we utilized the methodologies of independent components analysis (ICA) and multivariate granger causality analysis (mGCA).

Results: We found altered DEC within DMN only show decrease in state 1. In addition, the causal information flow of diabetic patients major affected areas which are closely associated with food craving and metabolic regulation, and T2DM patients stayed longer in low activity level and exhibited decreased transition rate between states. Moreover, these changes related negatively with the MoCA scores and positively with HbA1C level.

Conclusion: Our study may offer a fresh perspective on brain dynamic activities to understand the mechanisms underlying T2DM-related cognitive deficits.

Keywords: default mode network; dynamic effective connectivity; independent components analysis; multivariate granger causality analysis; type 2 diabetes mellitus.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by National Natural Science Foundation of China (grant no. 81960309) and Science and Technology Project of Gansu Province (grant no. 21JR7RA438).