Poline J B, Worsley K J, Holmes A P, Frackowiak R S, Friston K J
Wellcome Department of Cognitive Neurology, Hammersmith Hospital, London, England.
J Comput Assist Tomogr. 1995 Sep-Oct;19(5):788-96. doi: 10.1097/00004728-199509000-00017.
The smoothness parameter that characterises the spatial dependence of pixel values in functional brain images is usually estimated empirically from the data. Since this parameter is essential for the assessment of significant changes in brain activity, it is important to know (a) the variance of its estimator and (b) how this variability affects the results of the ensuing statistical analysis.
In this article, we derive an approximate expression for the variance of the smoothness estimator and investigate the effects of this variability on assessing the significance of cerebral activation in statistical parametric maps using a verbal fluency PET activation experiment.
Our results suggest that, for p values around 0.05, the variability in the p value (due to smoothness estimation) is approximately 20%.
The effect of the assessment of the spatial dependency of the data is far from being negligible, and this suggests a more comprehensive methodology for functional imaging than the one used so far. This work provides a simple tool for taking into account this effect.
用于表征功能性脑图像中像素值空间依赖性的平滑度参数通常是根据数据凭经验估计的。由于该参数对于评估脑活动的显著变化至关重要，因此了解以下两点很重要：（a）其估计量的方差；（b）这种变异性如何影响后续统计分析的结果。
在本文中，我们推导了平滑度估计量方差的近似表达式，并使用言语流畅性PET激活实验研究了这种变异性对评估统计参数图中脑激活显著性的影响。
我们的结果表明，对于p值约为0.05的情况，p值的变异性（由于平滑度估计）约为20%。
数据空间依赖性评估的影响远非微不足道，这表明功能性成像需要一种比目前使用的方法更全面的方法。这项工作提供了一个考虑这种影响的简单工具。
