Extracting task-related activation components from optical topography measurement using independent components analysis
Extracting task-related activation components from optical topography measurement using independent components analysis
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DOI：
10.1117/1.2981829
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发表时间：
2008-09-01
影响因子：
3.5
通讯作者：
Tanaka, Naoki
中科院分区：
文献类型：
--
作者：
Katura, Takusige;Sato, Hiroki;Tanaka, Naoki
光学地形图（OT）的信号测量在实验中，使用激活任务的某些脑功能包含神经元激活诱导的血氧变化，也生理变化。我们使用独立分量分析来分离信号并提取与大脑激活相关的分量，而不使用任何血流动力学模型。分析过程分为三个阶段：首先，OT信号被分离成独立的成分（IC），通过使用时间延迟去相关算法;第二，任务相关的IC（TR-IC）被从分离的IC的基础上，他们的平均试验间的互相关选择;第三，TR-IC被分类为TR激活相关的IC（TR-AIC）和TR噪声IC（TR-AIC）的k-means聚类。我们将此分析程序应用于从单手手指敲击任务的实验中获得的OT信号。在TR-AIC的平均波形中，在每个任务开始后的几秒钟和结束后的几秒钟内可以看到小的过冲，并且TR-NIC的平均波形具有N形图案。(C)2008年，由光学仪器工程师协会（Society of Photo-Optical Instrumentation Engineers）主办。[DOI 10.1117/1.2981829]
Optical topography (OT) signals measured during an experiment that used activation tasks for certain brain functions contain neuronal-activation induced blood oxygenation changes and also physiological changes. We used independent component analysis to separate the signals and extracted components related to brain activation without using any hemodynamic models. The analysis procedure had three stages: first, OT signals were separated into independent components (ICs) by using a time-delayed decorrelation algorithm; second, task-related ICs (TR-ICs) were selected from the separated ICs based on their mean intertrial cross-correlations; and third, the TR-ICs were categorized by k-means clustering into TR activation-related ICs (TR-AICs) and TR noise ICs (TR-NICs). We applied this analysis procedure to the OT signals obtained from experiments using one-handed finger-tapping tasks. In the averaged waveform of the TR-AICs, a small overshoot can be seen for a few seconds after the onset of each task and a few seconds after it ends, and the averaged waveforms of the TR-NICs have an N-shaped pattern. (C) 2008 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.2981829]