Hallquist Michael N, Hillary Frank G
Department of Psychology, Pennsylvania State University, University Park, PA, USA.
Netw Neurosci. 2018 Oct 1;3(1):1-26. doi: 10.1162/netn_a_00054. eCollection 2019.
Over the past two decades, resting-state functional connectivity (RSFC) methods have provided new insights into the network organization of the human brain. Studies of brain disorders such as Alzheimer's disease or depression have adapted tools from graph theory to characterize differences between healthy and patient populations. Here, we conducted a review of clinical network neuroscience, summarizing methodological details from 106 RSFC studies. Although this approach is prevalent and promising, our review identified four challenges. First, the composition of networks varied remarkably in terms of region parcellation and edge definition, which are fundamental to graph analyses. Second, many studies equated the number of connections across graphs, but this is conceptually problematic in clinical populations and may induce spurious group differences. Third, few graph metrics were reported in common, precluding meta-analyses. Fourth, some studies tested hypotheses at one level of the graph without a clear neurobiological rationale or considering how findings at one level (e.g., global topology) are contextualized by another (e.g., modular structure). Based on these themes, we conducted network simulations to demonstrate the impact of specific methodological decisions on case-control comparisons. Finally, we offer suggestions for promoting convergence across clinical studies in order to facilitate progress in this important field.
在过去二十年中，静息态功能连接（RSFC）方法为人类大脑的网络组织提供了新的见解。对诸如阿尔茨海默病或抑郁症等脑部疾病的研究采用了图论工具来表征健康人群与患者群体之间的差异。在此，我们对临床网络神经科学进行了综述，总结了106项RSFC研究的方法学细节。尽管这种方法很普遍且很有前景，但我们的综述确定了四个挑战。首先，网络的组成在区域划分和边的定义方面差异显著，而这两者对于图分析至关重要。其次，许多研究将不同图之间的连接数量等同起来，但这在临床人群中在概念上存在问题，并且可能导致虚假的组间差异。第三，很少有共同报告的图指标，这使得荟萃分析无法进行。第四，一些研究在图的一个层面上检验假设，却没有明确的神经生物学原理，也没有考虑一个层面（例如全局拓扑）的发现如何由另一个层面（例如模块结构）来进行背景化。基于这些主题，我们进行了网络模拟，以证明特定方法学决策对病例对照比较的影响。最后，我们为促进临床研究之间的趋同提供建议，以便推动这一重要领域的进展。
