Institució Catalana de Recerca i Estudis Avançats, Universitat Pompeu Fabra, Computational Neuroscience, Plaça de la Mercè, 10-12, 08002 Barcelona, Spain.
Nat Rev Neurosci. 2011 Jan;12(1):43-56. doi: 10.1038/nrn2961.
A broad body of experimental work has demonstrated that apparently spontaneous brain activity is not random. At the level of large-scale neural systems, as measured with functional MRI (fMRI), this ongoing activity reflects the organization of a series of highly coherent functional networks. These so-called resting-state networks (RSNs) closely relate to the underlying anatomical connectivity but cannot be understood in those terms alone. Here we review three large-scale neural system models of primate neocortex that emphasize the key contributions of local dynamics, signal transmission delays and noise to the emerging RSNs. We propose that the formation and dissolution of resting-state patterns reflects the exploration of possible functional network configurations around a stable anatomical skeleton.
大量的实验工作表明，显然自发的大脑活动并非随机的。在功能磁共振成像 (fMRI) 测量的大规模神经系统水平上，这种持续的活动反映了一系列高度相干的功能网络的组织。这些所谓的静息态网络 (RSN) 与潜在的解剖连通性密切相关，但不能仅从这些方面来理解。在这里，我们回顾了三种强调局部动力学、信号传输延迟和噪声对新兴 RSN 关键贡献的灵长类新皮质的大规模神经网络模型。我们提出，静息态模式的形成和溶解反映了围绕稳定解剖骨架探索可能的功能网络配置的过程。
