DTU Informatics, Technical University of Denmark, Kongens Lyngby, Denmark.
Neuroimage. 2012 Apr 15;60(3):1807-18. doi: 10.1016/j.neuroimage.2012.01.096. Epub 2012 Jan 28.
We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising procedure is performed within a data-driven split-half evaluation framework. ii) We introduce manifold navigation for exploration of a nonlinear data manifold, and illustrate how pre-image estimation can be used to generate brain maps in the continuum between experimentally defined brain states/classes. We base these illustrations on two fMRI BOLD data sets - one from a simple finger tapping experiment and the other from an experiment on object recognition in the ventral temporal lobe.
我们研究了核主成分分析（PCA）和神经影像学中称为逆问题的预图像估计的应用：i）我们探索核 PCA 和预图像估计作为图像去噪的一种手段，作为图像处理管道的一部分。在数据驱动的分半评估框架内评估去噪过程。ii）我们引入流形导航来探索非线性数据流形，并说明预图像估计如何用于在实验定义的脑状态/类之间的连续体中生成脑图。我们基于两个 fMRI BOLD 数据集来进行这些说明 - 一个来自简单的手指敲击实验，另一个来自腹侧颞叶的物体识别实验。
