Triple Network Model-Based Analysis on Abnormal Core Brain Functional Network Dynamics in Different Stage of Amnestic Mild Cognitive Impairment

Article type: Research Article

Authors: Li, Chenxi^{a; 2} | Li, Youjun^{b; c; d; 2} | Wu, Jianqian^e | Wu, Min^b | Peng, Fang^{a; *} | Chao, Qiuling^{e; *} | Alzheimer’s Disease Neuroimaging Initiative¹

Affiliations: [a] Department of Military Medical Psychology, Air Force Medical University, Xi’an, Shaanxi, China | [b] The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, P. R. China | [c] National Engineering Research Center for Healthcare Devices, Guangzhou, Guangdong, P.R. China | [d] The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi’an, Shaanxi, P. R. China | [e] School of Public Policy and Adiminstration, Xi’an Jiaotong University, Xi’an, Shaanxi, P. R. China

Correspondence: [*] Correspondence to: Peng Fang, Department of Military Medical Psychology, Air Force Medical University, Xi’an, Shaanxi,710032, P.R. China. E-mail: fangpeng@fmmu.edu.cn and Qiuling Chao, School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, P. R. China. E-mail: cql@xjtu.edu.cn.

Note: [1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (https://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: https://adni.loni.usc.edu/wpcontent/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Note: [2] These authors contributed equally to this work.

Abstract: Background:Amnestic mild cognitive impairment (aMCI) is considered to be a transitional stage between Alzheimer’s disease (AD) and normal cognitive state because it has the same clinical symptoms as AD but with lower severity. Studies have confirmed that patients with aMCI are more likely to develop to AD. Although studies on resting state functional connectivity have revealed the abnormal organization of brain networks, the dynamic changes of the functional connectivity across the scans have been ignored. Objective:Dynamic functional connectivity is a novel method to reveal the temporal variation of brain networks. This paper aimed to investigate the dynamic characteristics of brain functional connectivity in the early and late phases of aMCI. Methods:Based on the “triple network” model, we used the sliding time window approach to construct dynamical functional networks and then analyzed the dynamic characteristics of the functional connectivity across the entire scan. Results:The results showed that patients with aMCI had longer dwell times in weaker network connection than in the strong network. The transitions between different states become more frequent, and the stability of the patient’s brain core network deteriorates. This study also found the correlation between the altered dynamic properties of the core functional networks and the patient’s clinical Mini-Mental State Examination assessment scale sores. Conclusion:This study revealed that the characteristics of dynamic functional networks constructed by the core cognitive networks varied in distinct ways at different stages of aMCI, which could provide a new idea for exploring the neuro-mechanisms of neurological disorders.

Keywords: Amnestic mild cognitive impairment, dynamic functional connectivity network, temporal variability, triple network

DOI: 10.3233/JAD-220282

Journal: Journal of Alzheimer's Disease, vol. 89, no. 2, pp. 519-533, 2022