Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA.
Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, USA.
Neuron. 2018 Apr 18;98(2):439-452.e5. doi: 10.1016/j.neuron.2018.03.035.
The organization of human brain networks can be measured by capturing correlated brain activity with fMRI. There is considerable interest in understanding how brain networks vary across individuals or neuropsychiatric populations or are altered during the performance of specific behaviors. However, the plausibility and validity of such measurements is dependent on the extent to which functional networks are stable over time or are state dependent. We analyzed data from nine high-quality, highly sampled individuals to parse the magnitude and anatomical distribution of network variability across subjects, sessions, and tasks. Critically, we find that functional networks are dominated by common organizational principles and stable individual features, with substantially more modest contributions from task-state and day-to-day variability. Sources of variation were differentially distributed across the brain and differentially linked to intrinsic and task-evoked sources. We conclude that functional networks are suited to measuring stable individual characteristics, suggesting utility in personalized medicine.
人类大脑网络的组织可以通过 fMRI 捕捉相关的大脑活动来测量。人们非常感兴趣的是了解大脑网络在个体或神经精神人群中如何变化，或者在执行特定行为时如何变化。然而，这种测量的合理性和有效性取决于功能网络在多大程度上随时间稳定或依赖于状态。我们分析了来自九名高质量、高采样个体的数据，以解析网络变异性在个体、会话和任务之间的幅度和解剖分布。至关重要的是，我们发现功能网络主要由共同的组织原则和稳定的个体特征主导，而任务状态和日常变化的贡献则要小得多。变异源在大脑中分布不均，并与内在和任务诱发的源不同程度地相关。我们的结论是，功能网络适合测量稳定的个体特征，这表明在个性化医疗中有一定的应用价值。
