Research into the human connectome (i.e., all connections in the human brain) with the use of resting state functional MRI has rapidly increased in popularity in recent years, especially with the growing availability of large-scale neuroimaging datasets. The goal of this review article is to describe innovations in functional connectome representations that have come about in the past 8 years, since the 2013 NeuroImage special issue on ‘Mapping the Connectome’. In the period, research has shifted from group-level brain parcellations towards the characterization of the individualized connectome and of relationships between individual connectomic differences and behavioral/clinical variation. Achieving subject-specific accuracy in parcel boundaries while retaining cross-subject correspondence is challenging, and a variety of different approaches are being developed to meet this challenge, including improved alignment, improved noise reduction, and robust group-to-subject mapping approaches. Beyond the interest in the individualized connectome, new representations of the data are being studied to complement the traditional parcellated connectome representation (i.e., pairwise connections between distinct brain regions), such as methods that capture overlapping and smoothly varying patterns of connectivity (‘gradients’). These different connectome representations offer complimentary insights into the inherent functional organization of the brain, but challenges for functional connectome research remain. Interpretability will be improved by future research towards gaining insights into the neural mechanisms underlying connectome observations obtained from functional MRI. Validation studies comparing different connectome representations are also needed to build consensus and confidence to proceed with clinical trials that may produce meaningful clinical translation of connectome insights.

近年来，利用静息态功能 MRI 对人类连接组（即人脑中的所有连接）进行的研究迅速普及，特别是随着大规模神经影像数据集的可用性不断增加。这篇综述文章的目的是描述自 2013 年 NeuroImage 特刊“映射连接组”以来过去 8 年中出现的功能性连接组表示方面的创新。在此期间，研究已从群体水平的大脑分区转向个体化连接组的表征以及个体连接组差异与行为/临床变异之间的关系。在保持跨主题对应性的同时实现宗地边界中主题特定的准确性具有挑战性，并且正在开发各种不同的方法来应对这一挑战，包括改进的对齐、改进的降噪和强大的组到主题映射方法。除了对个性化连接组的兴趣之外，正在研究数据的新表示形式，以补充传统的分割连接组表示（即不同大脑区域之间的成对连接），例如捕获重叠和平滑变化的连接模式（“梯度”）的方法）。这些不同的连接组表示提供了对大脑固有功能组织的补充见解，但功能连接组研究仍然面临挑战。未来的研究将提高可解释性，以深入了解从功能性 MRI 获得的连接组观察结果背后的神经机制。还需要比较不同连接组表示的验证研究，以建立共识和信心，以进行临床试验，从而可能产生有意义的连接组见解的临床转化。