Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients.
Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients.
复制标题
用于表征和区分 PTSD 患者的动态功能连接组学特征
DOI：
10.1002/hbm.22290
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发表时间：
2014-04
影响因子：
4.8
通讯作者：
Liu, Tianming
中科院分区：
文献类型：
--
作者：
Li, Xiang;Zhu, Dajiang;Jiang, Xi;Jin, Changfeng;Zhang, Xin;Guo, Lei;Zhang, Jing;Hu, Xiaoping;Li, Lingjiang;Liu, Tianming
功能性连接体最近被证明在表征大脑状况方面是强大的。然而，许多以前的研究假设的功能连接体的时间平稳性，而他们的时间动态很少探讨。在这里，基于从扩散张量成像（DTI）数据构建的结构连接体，功能连接体来自静息态fMRI（R-fMRI）数据，然后通过滑动时间窗方法在时间上划分为准稳定段。通过对44例创伤后应激障碍（PTSD）患者和51例健康对照者的大量时间上准稳定的功能性连接体片段进行整合和合并，利用有效的字典学习和稀疏编码算法，获得了共同的功能性连接体（CFC）模式。结果发现，有16个CFC模式是可重复的健康对照，有趣的是，两个额外的CFC模式与改变连接模式（称为签名功能连接体（SFC）在这里）主要存在于PTSD受试者。仅这两种SFC模式就可以成功区分80%的PTSD受试者和健康对照者，只有2%的假阳性。此外，在PTSD受试者的CFC模式的时间转换动力学与健康对照组有很大不同。这些结果已在单独的测试数据集中得到复制，表明动态功能连接组学签名可以有效地表征和区分PTSD患者。
Functional connectomes have been recently shown to be powerful in characterizing brain conditions. However, many previous studies assumed temporal stationarity of functional connectomes, while their temporal dynamics are rarely explored. Here, based on the structural connectomes constructed from diffusion tensor imaging (DTI) data, functional connectomes are derived from resting-state fMRI (R-fMRI) data and are then temporally divided into quasi-stable segments via a sliding time window approach. After integrating and pooling over a large number of those temporally quasi-stable functional connectome segments from 44 post-traumatic stress disorder (PTSD) patients and 51 healthy controls, common functional connectome (CFC) patterns are derived via effective dictionary learning and sparse coding algorithms. It is found that there are 16 CFC patterns that are reproducible across healthy controls, and interestingly, two additional CFC patterns with altered connectivity patterns (termed signature functional connectome (SFC) here) exist dominantly in PTSD subjects. These two SFC patterns alone can successfully differentiate 80% of PTSD subjects from healthy controls with only 2% false positive. Furthermore, the temporal transition dynamics of CFC patterns in PTSD subjects are substantially different from those in healthy controls. These results have been replicated in separate testing datasets, suggesting that dynamic functional connectomics signatures can effectively characterize and differentiate PTSD patients.
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影响因子：
2.8
作者：
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通讯作者：
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