标题： 评估重复测试fMRI研究中的激活或非激活确定性 显示英文标题

标题： Assessing Certainty of Activation or Inactivation in Test-Retest fMRI Studies

摘要： 功能性磁共振成像（fMRI）被广泛用于研究人脑中的激活情况。在大多数情况下，数据通常用于构建与特定范式相对应的激活图。然而，结果可能非常具有变异性，因此量化研究中确定激活和非激活的确定性非常重要。本文提出了一种基于模型的方法，用于从多次重复相同实验范式所获得的数据中估计确定性。具体来说，从数据分析的统计值$p$被明确建模为其潜在分布的混合；因此，与目前使用的现有方法不同，在估计过程中无需主观阈值设定。控制混合模型的参数可以通过最大似然原理轻松获得。此外，这些估计值还可以用于最佳识别体素特定的激活区域及其对应的确定性度量。该方法应用于一项涉及单一受试者在两个月内多次执行运动范式的实验研究。校准方法性能的模拟实验结果令人鼓舞。同时，该方法在确定激活区域及其对应确定性方面也表现出较强的鲁棒性。 显示英文摘要

摘要： Functional Magnetic Resonance Imaging~(fMRI) is widely used to study activation in the human brain. In most cases, data are commonly used to construct activation maps corresponding to a given paradigm. Results can be very variable, hence quantifying certainty of identified activation and inactivation over studies is important. This paper provides a model-based approach to certainty estimation from data acquired over several replicates of the same experimental paradigm. Specifically, the $p$-values derived from the statistical analysis of the data are explicitly modeled as a mixture of their underlying distributions; thus, unlike methodology currently in use, there is no subjective thresholding required in the estimation process. The parameters governing the mixture model are easily obtained by the principle of maximum likelihood. Further, the estimates can also be used to optimally identify voxel-specific activation regions along with their corresponding certainty measures. The methodology is applied to a study involving a motor paradigm performed on a single subject several times over a period of two months. Simulation experiments used to calibrate performance of the method are promising. The methodology is also seen to be robust in determining areas of activation and their corresponding certainties.