A novel method for spatio-temporal pattern analysis of brain fMRI data
A novel method for spatio-temporal pattern analysis of brain fMRI data
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DOI：
10.1360/03yf0530
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发表时间：
2005-04
期刊：
影响因子：
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通讯作者：
Yadong Liu;Zongtan Zhou;D. Hu;Lirong Yan;Changlian Tan;Daxing Wu;S. Yao
中科院分区：
文献类型：
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作者：
Yadong Liu;Zongtan Zhou;D. Hu;Lirong Yan;Changlian Tan;Daxing Wu;S. Yao
提出了一种新的功能磁共振成像（fMRI）数据处理方法，该方法可以同时研究刺激信号动态响应的时空特征。首先利用多锥度谱估计方法估计每个体素的谱；对感兴趣频率线频率分量的显著性进行检测，以检测任务相关的皮层区域；然后对激活体素进行时间独立分量分析（temporal independent component analysis, tICA），获得刺激诱导的信号动态响应。该方法的优点是：不需要对脑血流动力学和任务相关区域的空间分布进行假设，克服了fMRI数据的tICA分析中经常出现的稳定性、可靠性和鲁棒性不足的问题。
A novel data processing procedure for fMRI was suggested in this paper, by which spatial and temporal characteristics of stimuli-induced signal dynamic responses can be investigated simultaneously. First the multitaper spectral estimation was utilized to estimate the spectrum of each voxel; the significance of the line frequency components at the interested frequency was tested to detect the task-related cortex areas; the temporal independent component analysis (tICA) was then applied to the activated voxels to obtain stimuli-induced signal dynamic responses. The advantages of this procedure are: few assumptions are needed for the cerebral hemodynamics and spatial distribution of task-related areas, problems which often appear in tICA analysis of fMRI data, such as the lack of stability, reliability and robustness, are overcome by the suggested method.