It is well known that Gaussian modelling of functional magnetic resonance imaging (fMRI) magnitude time‐course data, which are truly Rice distributed, constitutes an approximation, especially at low signal‐to‐noise ratios (SNRs). Based on this fact, previous work has argued that Rice‐based activation tests show superior performance over their Gaussian‐based counterparts at low SNRs and should be preferred in spite of the attendant additional computational and estimation burden. Here, we revisit these past studies and, after identifying and removing their underlying limiting assumptions and approximations, provide a more comprehensive comparison. Our experimental evaluations using Receiver Operating Characteristic (ROC) curve methodology show that tests derived using Ricean modelling are substantially superior over the Gaussian‐based activation tests only for SNRs below 0.6, that is, SNR values far lower than those encountered in fMRI as currently practiced.Copyright © 2013 John Wiley & Sons, Ltd.

中文翻译：

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Ricean在幅度fMRI分析中的高斯建模上增加了复杂性，而实际收益却微不足道。

众所周知，功能磁共振成像（fMRI）幅度时间过程数据的高斯建模（实际上是莱斯分布的）构成了一个近似值，尤其是在信噪比（SNR）低的情况下。基于这一事实，以前的工作认为，基于Rice的激活测试在低SNR的情况下显示出比基于Gaussian的激活测试更好的性能，尽管存在额外的计算和估计负担，还是应首选使用Rice的激活测试。在这里，我们将回顾这些过去的研究，并在确定并删除其潜在的局限性假设和近似值之后，提供更全面的比较。