1 Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science, University of Sherbrooke , Sherbrooke, Canada .
2 Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University , Cardiff, United Kingdom .
Brain Connect. 2017 Oct;7(8):491-503. doi: 10.1089/brain.2017.0539.
Fingerprint patterns derived from functional connectivity (FC) can be used to identify subjects across groups and sessions, indicating that the topology of the brain substantially differs between individuals. However, the source of FC variability inferred from resting-state functional magnetic resonance imaging remains unclear. One possibility is that these variations are related to individual differences in white matter structural connectivity (SC). However, directly comparing FC with SC is challenging given the many potential biases associated with quantifying their respective strengths. In an attempt to circumvent this, we employed a recently proposed test-retest approach that better quantifies inter-subject variability by first correcting for intra-subject nuisance variability (i.e., head motion, physiological differences in brain state, etc.) that can artificially influence FC and SC measures. Therefore, rather than directly comparing the strength of FC with SC, we asked whether brain regions with, for example, low inter-subject FC variability also exhibited low SC variability. From this, we report two main findings: First, at the whole-brain level, SC variability was significantly lower than FC variability, indicating that an individual's structural connectome is far more similar to another relative to their functional counterpart even after correcting for noise. Second, although FC and SC variability were mutually low in some brain areas (e.g., primary somatosensory cortex) and high in others (e.g., memory and language areas), the two were not significantly correlated across all cortical and sub-cortical regions. Taken together, these results indicate that even after correcting for factors that may differently affect FC and SC, the two, nonetheless, remain largely independent of one another. Further work is needed to understand the role that direct anatomical pathways play in supporting vascular-based measures of FC and to what extent these measures are dictated by anatomical connectivity.
指纹图谱可以从功能连接（FC）中提取出来，用于在组间和会话间识别受试者，这表明大脑的拓扑结构在个体之间有很大的差异。然而，从静息态功能磁共振成像推断出的 FC 变异性的来源仍不清楚。一种可能性是，这些变化与白质结构连接（SC）的个体差异有关。然而，由于量化它们各自强度的许多潜在偏差，直接比较 FC 和 SC 具有挑战性。为了避免这一点，我们采用了最近提出的一种测试-再测试方法，该方法通过首先校正主体内的噪声变异性（即头部运动、大脑状态的生理差异等），更好地量化了主体间的变异性，从而更好地量化了主体间的变异性，这些变异性会人为地影响 FC 和 SC 测量值。因此，我们不是直接比较 FC 和 SC 的强度，而是询问例如，具有低主体间 FC 变异性的脑区是否也表现出低 SC 变异性。由此，我们报告了两个主要发现：首先，在全脑水平上，SC 变异性显著低于 FC 变异性，这表明一个人的结构连接组与另一个人的结构连接组更为相似，即使在对噪声进行校正后也是如此。其次，尽管在某些脑区（如初级体感皮层）FC 和 SC 变异性都较低，而在其他脑区（如记忆和语言区）变异性都较高，但在所有皮质和皮质下区域，两者之间没有显著相关性。总的来说，这些结果表明，即使在对可能不同地影响 FC 和 SC 的因素进行校正后，两者仍然在很大程度上相互独立。需要进一步的工作来了解直接解剖途径在支持基于血管的 FC 测量中的作用，以及这些测量在多大程度上由解剖连接决定。
