Lefèvre Julien, Obozinski Guillaume, Baillet Sylvain
Cognitive Neuroscience and Brain Imaging Laboratory, CNRS UPR640-LENA, Université Pierre et Marie CURIE-Paris6, Paris, F-75013, France.
Inf Process Med Imaging. 2007;20:470-81. doi: 10.1007/978-3-540-73273-0_39.
We report on mathematical methods for the exploration of spatiotemporal dynamics of Magneto- and Electro-Encephalography (MEG / EEG) surface data and/or of the corresponding brain activity at the cortical level, with high temporal resolution. In this regard, we describe how the framework and numerical computation of the optical flow--a classical tool for motion analysis in computer vision--can be extended to non-flat 2-dimensional surfaces such as the scalp and the cortical mantle. We prove the concept and mathematical well-posedness of such an extension through regularizing constraints on the estimated velocity field, and discuss the quantitative evaluation of the optical flow. The method is illustrated by simulations and analysis of brain image sequences from a ball-catching paradigm.
我们报告了用于探索脑磁图和脑电图（MEG/EEG）表面数据以及皮质水平相应脑活动的时空动态的数学方法，具有高时间分辨率。在这方面，我们描述了光流的框架和数值计算——计算机视觉中用于运动分析的经典工具——如何扩展到非平面的二维表面，如头皮和皮质幔。我们通过对估计速度场的正则化约束证明了这种扩展的概念和数学适定性，并讨论了光流的定量评估。通过对抓球范式的脑图像序列进行模拟和分析来说明该方法。
