Backfrieder W, Baumgartner R, Sámal M, Moser E, Bergmann H
Department of Biomedical Engineering and Physics, University of Vienna, Austria.
Phys Med Biol. 1996 Aug;41(8):1425-38. doi: 10.1088/0031-9155/41/8/011.
In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.
在功能磁共振成像（fMRI）中，使用标准临床磁共振设备测量与刺激的神经脑活动相关的脑血流动力学变化。必须通过仔细的图像分析来检测fMRI数据中的微小强度变化，并将其与非神经效应区分开来。基于多变量统计，我们描述了一种算法，该算法涉及对最重要的主成分进行斜旋转，以估计整个图像矩阵上刺激的神经活动的时间和空间分布。该算法利用了强烈的局部信号变化。设计了一个数学模型来生成模拟数据，以评估该方法。在模拟实验中，证明了该方法量化微小强度变化的潜力，特别是在处理包含多个信号变化源的数据集时。对在视觉和运动刺激实验中收集的体内fMRI数据进行了分析，结果显示激活的皮质区域在知名神经中枢内的位置正确，并且准确提取了激活时间曲线。所建议的方法无需广泛的先验知识和用户交互即可对体内脑活动进行准确的绝对量化。
