Functional magnetic resonance imaging analytical workflows are highly flexible with no definite consensus on how to choose a pipeline. While methods have been developed to explore this analytical space, there is still a lack of understanding of the relationships between the different pipelines. We use community detection algorithms to explore the pipeline space and assess its stability across different contexts. We show that there are subsets of pipelines that give similar results, especially those sharing specific parameters (e.g. number of motion regressors, software packages, etc.), with relative stability across groups of participants. By visualizing the differences between these subsets, we describe the effect of pipeline parameters and derive general relationships in the analytical space.

翻译：功能磁共振成像分析工作流具有高度灵活性，目前尚未就如何选择分析流程达成明确共识。尽管已有方法用于探索这一分析空间，但不同流程之间的关系仍缺乏深入理解。我们采用社区检测算法来探索流程空间，并评估其在不同情境下的稳定性。研究表明，存在能产生相似结果的分析流程子集——尤其是那些共享特定参数（如运动回归量数量、软件包等）的流程——且这些子集在不同参与者群体间具有相对稳定性。通过可视化这些子集间的差异，我们描述了流程参数的影响，并推导出分析空间中的一般性关联规律。