| 赵杰
，欧阳周玲
，丁雪桐
，乔吉日木图.认知障碍的进展对脑功能连接梯度的影响[J].神经损伤功能重建,2022,17(1):23-27 |
| 认知障碍的进展对脑功能连接梯度的影响 |
| Impact of Progression of Cognitive Impairment on Functional Brain Connectivity Gradient |
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| DOI： |
| 中文关键词: 功能磁共振成像 阿尔兹海默症 功能连接 连接梯度 |
| 英文关键词: functional magnetic resonance imaging Alzheimer's disease functional connectivity connectivity gradient |
| 基金项目: |
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| 摘要点击次数: 3224 |
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| 中文摘要: |
| 目的：探究认知障碍的进展对连接梯度是否存在影响，以及认知障碍的进展导致的各脑区梯度变化
差异。方法：收集正常对照40例（NC组）、早期轻度认知障碍（MCI）患者42例（EMCI组）、晚期MCI患者39
例（LMCI组）和阿尔兹海默病（AD）患者40例（AD组）的静息态fMRI数据。采用非线性分解的方法将各受
试组的功能连接数据计算连接体梯度，比较不同阶段被试组间的梯度差异。结果：认知障碍的进展会导致
连接梯度的连接模式中变化的脑网络增多，梯度分数也明显下降，其中第一梯度变化最明显的在EMCI阶 段，第二梯度变化最明显的在AD阶段，并且第一梯度解释了梯度变化中最大的差异。结论：认知障碍的进
展对连接梯度存在影响，相比于离散网络的研究方法，连接梯度保留了各子网络间的连接，反映了全脑的宏
观连接模式。 |
| 英文摘要: |
| To investigate whether progression of cognitive impairment has an effect on
connectivity gradients, and to examine the differences in gradient changes across brain regions due to the
progression of cognitive impairment. Methods: The resting-state fMRI data from 40 normal controls (NC
group), 42 patients with early mild cognitive impairment (MCI) (EMCI group), 39 patients with late MCI
(LMCI group), and 40 patients with Alzheimer's disease (AD) (AD group) were collected. A nonlinear
decomposition method was used to calculate the linker gradient from the functional connectivity data of each
subject group and to compare the differences in gradients between subject groups at different stages. Results:
Progression of cognitive impairment leads to an increase in the number of brain networks that change in the
connectivity pattern of the connectivity gradient and a significant decrease in gradient scores, with the most
significant change in the first gradient occurring during the EMCI stage and the most significant change in the
second gradient occurring during the AD stage, and with the first gradient explaining the largest difference in
gradient change. Conclusion: The progression of cognitive impairment impacts the connectivity gradient.
Compared to the discrete network approach, the connectivity gradient preserves the connections among the
subnetworks and responds to the macroscopic connectivity patterns of the whole brain. |
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