Honey Christopher J, Kötter Rolf, Breakspear Michael, Sporns Olaf
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA.
Proc Natl Acad Sci U S A. 2007 Jun 12;104(24):10240-5. doi: 10.1073/pnas.0701519104. Epub 2007 Jun 4.
Neuronal dynamics unfolding within the cerebral cortex exhibit complex spatial and temporal patterns even in the absence of external input. Here we use a computational approach in an attempt to relate these features of spontaneous cortical dynamics to the underlying anatomical connectivity. Simulating nonlinear neuronal dynamics on a network that captures the large-scale interregional connections of macaque neocortex, and applying information theoretic measures to identify functional networks, we find structure-function relations at multiple temporal scales. Functional networks recovered from long windows of neural activity (minutes) largely overlap with the underlying structural network. As a result, hubs in these long-run functional networks correspond to structural hubs. In contrast, significant fluctuations in functional topology are observed across the sequence of networks recovered from consecutive shorter (seconds) time windows. The functional centrality of individual nodes varies across time as interregional couplings shift. Furthermore, the transient couplings between brain regions are coordinated in a manner that reveals the existence of two anticorrelated clusters. These clusters are linked by prefrontal and parietal regions that are hub nodes in the underlying structural network. At an even faster time scale (hundreds of milliseconds) we detect individual episodes of interregional phase-locking and find that slow variations in the statistics of these transient episodes, contingent on the underlying anatomical structure, produce the transfer entropy functional connectivity and simulated blood oxygenation level-dependent correlation patterns observed on slower time scales.
即使在没有外部输入的情况下，大脑皮层内展开的神经元动力学也呈现出复杂的空间和时间模式。在这里，我们使用一种计算方法，试图将自发皮层动力学的这些特征与潜在的解剖连接性联系起来。在一个捕捉猕猴新皮层大规模区域间连接的网络上模拟非线性神经元动力学，并应用信息论方法识别功能网络，我们在多个时间尺度上发现了结构 - 功能关系。从长时间（数分钟）的神经活动窗口中恢复的功能网络在很大程度上与潜在的结构网络重叠。因此，这些长期功能网络中的枢纽对应于结构枢纽。相比之下，在从连续较短（数秒）时间窗口中恢复的网络序列中，观察到功能拓扑结构存在显著波动。随着区域间耦合的变化，单个节点的功能中心性随时间而变化。此外，脑区之间的瞬时耦合以一种揭示两个反相关簇存在的方式进行协调。这些簇由前额叶和顶叶区域连接，而这些区域是潜在结构网络中的枢纽节点。在更快的时间尺度（数百毫秒）上，我们检测到区域间锁相的单个事件，并发现这些瞬态事件统计量的缓慢变化，取决于潜在的解剖结构，产生了在较慢时间尺度上观察到的转移熵功能连接性和模拟的血氧水平依赖相关性模式。
