Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Brain Struct Funct. 2018 Jun;223(5):2519-2526. doi: 10.1007/s00429-018-1619-z. Epub 2018 Feb 16.
Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.
在人类大脑疾病的神经生理学研究中，经常观察到神经解剖网络内的同步性增加。这种现象通常归因于面对损伤的补偿过程，尽管支持这种解释的证据有限。鉴于静息态功能连接（rsFC）对潜在结构连接（SC）的已知依赖性，我们检验了另一种假设：即 SC 的拓扑变化，特别是特定的断开模式，导致网络 rsFC 的增加。我们使用 fMRI 获得 rsFC 的测量值，并使用概率轨迹追踪获得 50 名健康人和 28 名多发性硬化症患者的 SC 测量值。我们使用神经元动力学的计算模型，使用健康受试者的 SC 来模拟 BOLD 耦合区域。我们发现，通过引入那些具有高网络 rsFC 的多发性硬化症患者中观察到的结构断开模式来改变模型，会产生具有高 rsFC 的模拟结果，这表明断开本身在产生高网络功能连接中起着作用。然后，我们在个体中检查 SC 数据。在具有高网络 rsFC 的多发性硬化症患者中，我们发现相关网络与更广泛的系统之间存在优先断开。我们通过向模型中引入随机断开来检查这种网络隔离的意义。正如经验观察到的那样，模拟网络 rsFC 随着连接大脑其余部分的社区的连接的去除而增加。因此，我们表明，多发性硬化症中已知发生的结构断开导致多发性硬化症中网络 rsFC 的变化，并且进一步表明社区隔离是导致网络功能连接升高的原因。
