Sun Yat-sen University-Carnegie Mellon University (SYSU-CMU) Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China; Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Sun Yat-sen University-Carnegie Mellon University (SYSU-CMU) Joint Institute of Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China; Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA; School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, Guangdong, China; Sun Yat-sen University-Carnegie Mellon University (SYSU-CMU) Shunde International Joint Research Institute, Shunde, Guangdong, China.
Neuroscience. 2017 Dec 16;366:70-83. doi: 10.1016/j.neuroscience.2017.10.011. Epub 2017 Oct 14.
In this paper, by utilizing surface diffeomorphic deformations, we constructed and analyzed subcortical shape morphometric networks in 210 healthy control (HC) subjects and 175 subjects with Alzheimer's disease (AD), aiming to identify AD-induced abnormalities in the subcortical shape network. We quantitatively analyzed pertinent network attributes of the entire network and each node. Further to this, hierarchical analyses were performed; group comparisons were conducted at the structure level first and then the sub-region level. The bilateral amygdalae, hippocampi, as well as the thalamus were all divided into multiple functionally distinct sub-regions. From the structure level analysis, we found significant HC-vs-AD group differences in the average local efficiency and average global efficiency. In addition, the local nodal efficiencies between the right thalamus and all three of the right hippocampus, right amygdala, and left thalamus, as well as that between the left amygdala and left hippocampus, decreased significantly in AD. According to the sub-regional network analyses, we observed significant AD-induced local efficiency decreases between different sub-regions within the right hippocampus itself and between the subiculum of the right hippocampus and the sub-region of the right thalamus connecting to the temporal lobe, indicating a degradation of circuit between the hippocampus, thalamus, and temporal lobe. Statistical comparisons were performed using 40,000 non-parametric permutation tests, with false discovery rate correction employed for multiple comparison correction.
在本文中，我们利用表面变形，构建和分析了 210 名健康对照（HC）和 175 名阿尔茨海默病（AD）患者的皮质下形状形态网络，旨在识别 AD 引起的皮质下形状网络异常。我们对整个网络和每个节点的相关网络属性进行了定量分析。此外，还进行了层次分析；首先在结构水平上进行组间比较，然后在子区域水平上进行组间比较。双侧杏仁核、海马体以及丘脑均被分为多个具有不同功能的子区域。从结构水平分析，我们发现平均局部效率和平均全局效率在 HC 与 AD 组间存在显著差异。此外，右侧丘脑与右侧海马体、右侧杏仁核和左侧丘脑的右侧以及左侧杏仁核与左侧海马体的右侧之间的局部节点效率明显降低，这在 AD 患者中更为明显。根据子区域网络分析，我们观察到右侧海马体自身内以及右侧海马体的下托与连接颞叶的右侧丘脑子区域之间的不同子区域之间存在明显的 AD 诱导的局部效率降低，表明海马体、丘脑和颞叶之间的回路退化。采用 40000 次非参数置换检验进行统计比较，并采用错误发现率校正进行多重比较校正。
