Yu Shan, Huang Debin, Singer Wolf, Nikolic Danko
Department of Neurophysiology, Max-Planck Institute for Brain Research, D-60528 Frankfurt am Main, Germany.
Cereb Cortex. 2008 Dec;18(12):2891-901. doi: 10.1093/cercor/bhn047. Epub 2008 Apr 9.
A small-world network has been suggested to be an efficient solution for achieving both modular and global processing-a property highly desirable for brain computations. Here, we investigated functional networks of cortical neurons using correlation analysis to identify functional connectivity. To reconstruct the interaction network, we applied the Ising model based on the principle of maximum entropy. This allowed us to assess the interactions by measuring pairwise correlations and to assess the strength of coupling from the degree of synchrony. Visual responses were recorded in visual cortex of anesthetized cats, simultaneously from up to 24 neurons. First, pairwise correlations captured most of the patterns in the population's activity and, therefore, provided a reliable basis for the reconstruction of the interaction networks. Second, and most importantly, the resulting networks had small-world properties; the average path lengths were as short as in simulated random networks, but the clustering coefficients were larger. Neurons differed considerably with respect to the number and strength of interactions, suggesting the existence of "hubs" in the network. Notably, there was no evidence for scale-free properties. These results suggest that cortical networks are optimized for the coexistence of local and global computations: feature detection and feature integration or binding.
小世界网络被认为是实现模块化和全局处理的有效解决方案——这是大脑计算非常需要的一种特性。在此，我们使用相关性分析来识别功能连接，从而研究皮质神经元的功能网络。为了重建相互作用网络，我们基于最大熵原理应用了伊辛模型。这使我们能够通过测量成对相关性来评估相互作用，并通过同步程度来评估耦合强度。在麻醉猫的视觉皮层中记录视觉反应，同时记录多达24个神经元的活动。首先，成对相关性捕捉了群体活动中的大部分模式，因此为相互作用网络的重建提供了可靠的基础。其次，也是最重要的，所得网络具有小世界特性；平均路径长度与模拟随机网络中的一样短，但聚类系数更大。神经元在相互作用的数量和强度方面有很大差异，这表明网络中存在“枢纽”。值得注意的是，没有证据表明存在无标度特性。这些结果表明，皮质网络针对局部和全局计算（特征检测和特征整合或绑定）的共存进行了优化。
