A Study on the Effect of Executive Control Network Functional Connection on the Therapeutic Efficacy of Repetitive Transcranial Magnetic Stimulation in Alzheimer’s Disease

Article type: Research Article

Authors: Geng, Zhi^{a; b; c; 1} | Wu, Yue^{b; c; f; 1} | Liu, Jiaqiu^{a; b; c} | Zhan, Yuqian^{a; b; c} | Yan, Yibing^{a; b; c} | Yang, Chaoyi^{a; b; c} | Pang, Xuerui^{a; b; c} | Ji, Yi^{a; b; c} | Gao, Manman^{a; b; c} | Zhou, Shanshan^{a; b; c} | Wei, Ling^{a; b; c} | Hu, Panpan^{a; b; c; d; e} | Wu, Xingqi^{a; b; c; *} | Tian, Yanghua^{a; b; c; f; *} | Wang, Kai^{a; b; c; d; e; *}

Affiliations: [a] Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China | [b] Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China | [c] Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China | [d] Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China | [e] Anhui Provincial Institute of Translational Medicine, Anhui Medical University, Hefei, China | [f] Department of Sleep Psychology, The Second Hospital of Anhui Medical University, Anhui Medical University, Hefei, China

Correspondence: [*] Correspondence to: Xingqi Wu, Yanghua Tian, and Kai Wang, Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China. Emails: wuxingqi09@163.com (X. Wu), ayfytyh@126.com (Y. Tian), wangkai1964@126.com (K. Wang).

Note: [1] These authors contributed equally to this work.

Abstract: Background:Alzheimer’s disease (AD) is a neurodegenerative disease characterized by brain network dysfunction. Few studies have investigated whether the functional connections between executive control networks (ECN) and other brain regions can predict the therapeutic effect of repetitive transcranial magnetic stimulation (rTMS). Objective:The purpose of this study is to examine the relationship between the functional connectivity (FC) within ECN networks and the efficacy of rTMS. Methods:We recruited AD patients for rTMS treatment. We established an ECN using baseline period fMRI data and conducted an analysis of the ECN’s FC throughout the brain. Concurrently, the support vector regression (SVR) method was employed to project post-rTMS cognitive scores, utilizing the connectional attributes of the ECN as predictive markers. Results:The average age of the patients was 66.86±8.44 years, with 8 males and 13 females. Significant improvement on most cognitive measures. We use ECN connectivity and brain region functions in baseline patients as features for SVR model training and fitting. The SVR model could demonstrate significant predictability for changes in Montreal Cognitive Assessment scores among AD patients after rTMS treatment. The brain regions that contributed most to the prediction of the model (the top 10% of weights) were located in the medial temporal lobe, middle temporal gyrus, frontal lobe, parietal lobe and occipital lobe. Conclusions:The stronger the antagonism between ECN and parieto-occipital lobe function, the better the prediction of cognitive improvement; the stronger the synergy between ECN and fronto-temporal lobe function, the better the prediction of cognitive improvement.

Keywords: Alzheimer’s disease, executive control network, functional connectivity, repetitive transcranial magnetic stimulation, support vector regression

DOI: 10.3233/JAD-231449

Journal: Journal of Alzheimer's Disease, vol. 99, no. 4, pp. 1349-1359, 2024