MRC Cyclotron Unit, Hammersmith Hospital, London W12 OHS, United Kingdom.
Hum Brain Mapp. 1994;1(3):210-20. doi: 10.1002/hbm.460010306.
Current approaches to detecting significantly activated regions of cerebral tissue use statistical parametric maps, which are thresholded to render the probability of one or more activated regions of one voxel, or larger, suitably small (e. g., 0.05). We present an approximate analysis giving the probability that one or more activated regions of a specified volume, or larger, could have occurred by chance. These results mean that detecting significant activations no longer depends on a fixed (and high) threshold, but can be effected at any (lower) threshold, in terms of the spatial extent of the activated region. The substantial improvement in sensitivity that ensues is illustrated using a power analysis and a simulated phantom activation study. © 1994 Wiley-Liss, Inc.
当前检测大脑组织显著激活区域的方法使用统计参数映射,这些映射通过阈值处理,使一个或多个体素或更大的激活区域的概率变得足够小(例如,0.05)。我们提出了一种近似分析,给出了一个或多个指定体积或更大的激活区域偶然发生的概率。这些结果意味着检测显著激活不再依赖于固定(且较高)的阈值,而是可以根据激活区域的空间范围在任何(较低)阈值下进行。使用幂分析和模拟幻影激活研究说明了随之而来的灵敏度的显著提高。©1994 年 Wiley-Liss, Inc.