Honey C J, Sporns O, Cammoun L, Gigandet X, Thiran J P, Meuli R, Hagmann P
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA.
Proc Natl Acad Sci U S A. 2009 Feb 10;106(6):2035-40. doi: 10.1073/pnas.0811168106. Epub 2009 Feb 2.
In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks--including their spatial statistics and their persistence across time--can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct structural connection, rendering the inference of structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct structural linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.
在大脑皮层中，神经元群体的活动水平不断波动。当使用功能磁共振成像（fMRI）测量的神经元活动在两个群体之间在时间上具有连贯性时，这些群体就被认为是功能连接的。功能连接先前已被证明在总体水平上与结构（解剖学）连接模式相关。在本研究中，我们借助计算模型来探究功能网络的系统级属性——包括其空间统计特性及其随时间的持续性——是否可以由基础解剖网络的属性来解释。我们在同一批个体中以高分辨率测量了静息态功能连接（使用fMRI）和结构连接（使用扩散谱成像纤维束示踪）。然后，结构连接为宏观皮层动力学模型提供了耦合。在模型和数据中，我们都观察到：（i）在没有直接结构连接的区域之间通常存在强功能连接，这使得从功能连接推断结构连接不切实际；（ii）间接连接和区域间距离解释了一些无法由直接结构连接解释的功能连接方差；（iii）静息态功能连接在扫描会话和模型运行中都表现出内部和跨时间的变异性。这些实证和建模结果表明，尽管静息态功能连接是可变的，且经常出现在没有直接结构联系的区域之间，但其强度、持续性和空间统计特性仍然受到人类大脑皮层大规模解剖结构的限制。
