Resting-state fMRI (rs-fMRI) is widely used to investigate brain functional connectivity, but the reliability of these measurements remains a key concern for ensuring reproducibility. The distance-based intraclass correlation coefficient (dbICC) generalizes classical ICC to more general data types, making it well-suited for assessing the reliability of measures of functional connectivity. In this study, we applied dbICC to assess the reliability of rs-fMRI data from the Midnight Scanning Club (MSC) dataset, which consists of 10 subjects, each undergoing 10 sessions of 30-minute rs-fMRI scans. The functional connectivity was estimated using Pearson's correlation coefficients between all pairs of brain regions, resulting in a correlation matrix for each session. We compared two distance metrics-the widely used Frobenius metric and the Affine Invariant Riemannian Metric (AIRM) selected to respect the geometry of the space of covariance matrices-to evaluate how the choice of metric affects the reliability of estimating correlation. In addition, we investigated the impact of scan length and time interval between sessions on reliability. Results based on each metric agreed in some respects but disagreed in others, illustrating the impact of choice of metric. We also found that longer scan lengths significantly improve reliability, while the time interval between sessions has less impact.

翻译：静息态功能磁共振成像(rs-fMRI)被广泛用于研究大脑功能连接性，但测量结果的可靠性仍是确保可重复性的关键问题。基于距离的组内相关系数(dbICC)将经典ICC推广至更一般的数据类型，使其特别适用于评估功能连接性测量的可靠性。本研究将dbICC应用于评估午夜扫描俱乐部(MSC)数据集中rs-fMRI数据的可靠性，该数据集包含10名受试者，每位受试者接受10次30分钟时长的rs-fMRI扫描。通过计算所有脑区对之间的皮尔逊相关系数来估计功能连接性，每次扫描生成一个相关矩阵。我们比较了两种距离度量——广泛使用的弗罗贝尼乌斯度量和为尊重协方差矩阵空间几何特性而选取的仿射不变黎曼度量(AIRM)——以评估度量选择对估计相关性的可靠性影响。此外，我们还探究了扫描时长及扫描间隔时间对可靠性的影响。基于两种度量的结果在某些方面一致而在其他方面存在差异，揭示了度量选择的影响。研究同时发现，增加扫描时长能显著提升可靠性，而扫描间隔时间的影响相对较小。