Title: fMRI group analysis based on outputs from Matrix-Variate Dynamic Linear Models Show Chinese title

Title: 基于矩阵变元动态线性模型输出的脑成像群体分析

Abstract: In this work, we describe in more detail how to perform fMRI group analysis using inputs from modeling fMRI signal using Matrix-Variate Dynamic Linear Models (MDLM) at the individual level. After computing a posterior distribution for the average group activation, the three algorithms (FEST, FSTS, and FFBS) proposed from the previous work by Jim\'enez et al. [2019] can be easily implemented. We also propose an additional algorithm, which we call AG-algorithm, to draw on-line trajectories of the state parameter and therefore assess voxel activation at the group level. The performance of our method is illustrated through one practical example using real fMRI data from a "voice-localizer" experiment. Show Chinese abstract

Abstract: 在这项工作中，我们更详细地描述了如何通过使用矩阵可变动态线性模型（MDLM）在个体层面建模fMRI信号来执行fMRI群体分析。 在计算出平均群体激活的后验分布之后，Jiménez 等人 [2019] 的先前工作提出的三种算法（FEST、FSTS 和 FFBS）可以轻松实现。 我们还提出了一种附加算法，我们称之为 AG 算法，以绘制状态参数的在线轨迹，从而评估群体水平上的体素激活。 我们的方法性能通过一个实际例子进行了说明，该例子使用了来自“声音定位器”实验的真实fMRI数据。