Long Zhiying, Wang Zhi, Zhang Jing, Zhao Xiaojie, Yao Li
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
School of Information Science & Technology, Beijing Normal University, Beijing, China.
BMC Med Imaging. 2019 Jan 17;19(1):6. doi: 10.1186/s12880-018-0300-6.
Although independent component analysis (ICA) has been widely applied to functional magnetic resonance imaging (fMRI) data to reveal spatially independent brain networks, the order indetermination of ICA leads to the problem of target component selection. The temporally constrained independent component analysis (TCICA) is capable of automatically extracting the desired spatially independent components by adding the temporal prior information of the task to the mixing matrix for fMRI data analysis. However, the TCICA method can only extract a single component that tends to be a mix of multiple task-related components when there exist several independent components related to one task.
In this study, we proposed a TCICA with threshold (TCICA-Thres) method that performed TCICA outside the threshold and performed FastICA inside the threshold to automatically extract all the target components related to one task. The proposed approach was tested using simulated fMRI data and was applied to a real fMRI experiment using 13 subjects. Additionally, the performance of TCICA-Thres was compared with that of FastICA and TCICA.
The results from the simulation and the fMRI data demonstrated that TCICA-Thres better extracted the task-related components than TCICA. Moreover, TCICA-Thres outperformed FastICA in robustness to noise, spatial detection power and computational time.
The proposed TCICA-Thres solves the limitations of TCICA and extends the application of TCICA in fMRI data analysis.
尽管独立成分分析（ICA）已广泛应用于功能磁共振成像（fMRI）数据以揭示空间独立的脑网络，但ICA的顺序不确定性导致了目标成分选择的问题。时间约束独立成分分析（TCICA）能够通过将任务的时间先验信息添加到用于fMRI数据分析的混合矩阵中，自动提取所需的空间独立成分。然而，当存在与一个任务相关的多个独立成分时，TCICA方法只能提取一个往往是多个任务相关成分混合的成分。
在本研究中，我们提出了一种带阈值的TCICA（TCICA-Thres）方法，该方法在阈值外执行TCICA，在阈值内执行FastICA，以自动提取与一个任务相关的所有目标成分。使用模拟fMRI数据对所提出的方法进行了测试，并将其应用于一项使用13名受试者的真实fMRI实验。此外，将TCICA-Thres的性能与FastICA和TCICA的性能进行了比较。
模拟和fMRI数据的结果表明，TCICA-Thres比TCICA能更好地提取任务相关成分。此外，TCICA-Thres在噪声鲁棒性、空间检测能力和计算时间方面优于FastICA。
所提出的TCICA-Thres解决了TCICA的局限性，并扩展了TCICA在fMRI数据分析中的应用。
