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执行控制网络功能连接对阿尔茨海默病重复经颅磁刺激治疗效果的影响研究。

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

机构信息

Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.

出版信息

J Alzheimers Dis. 2024;99(4):1349-1359. doi: 10.3233/JAD-231449.

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.

摘要

背景

阿尔茨海默病(AD)是一种以大脑网络功能障碍为特征的神经退行性疾病。很少有研究探讨执行控制网络(ECN)与其他大脑区域之间的功能连接是否可以预测重复经颅磁刺激(rTMS)的治疗效果。

目的

本研究旨在检验 ECN 网络内的功能连接(FC)与 rTMS 疗效之间的关系。

方法

我们招募了 AD 患者进行 rTMS 治疗。我们使用基线期 fMRI 数据建立了 ECN,并对整个大脑的 ECN 功能连接进行了分析。同时,采用支持向量回归(SVR)方法,利用 ECN 的连接属性作为预测标记,预测 rTMS 后认知评分。

结果

患者的平均年龄为 66.86±8.44 岁,男性 8 人,女性 13 人。大多数认知测量都有显著改善。我们使用基线期患者的 ECN 连接和大脑区域功能作为 SVR 模型训练和拟合的特征。SVR 模型可以在 rTMS 治疗后,对 AD 患者蒙特利尔认知评估评分的变化进行显著预测。对模型预测贡献最大的大脑区域(权重前 10%)位于内侧颞叶、中颞叶、额叶、顶叶和枕叶。

结论

ECN 与顶枕叶功能之间的拮抗作用越强,对认知改善的预测效果越好;ECN 与额颞叶功能之间的协同作用越强,对认知改善的预测效果越好。

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