Goldberg Joshua A, Rokni Uri, Sompolinsky Haim
Racah Institute of Physics and The Interdisciplinary Center for Neural Computation, The Hebrew University, Jerusalem 91904, Israel.
Neuron. 2004 May 13;42(3):489-500. doi: 10.1016/s0896-6273(04)00197-7.
Ongoing spontaneous activity in the cerebral cortex exhibits complex spatiotemporal patterns in the absence of sensory stimuli. To elucidate the nature of this ongoing activity, we present a theoretical treatment of two contrasting scenarios of cortical dynamics: (1) fluctuations about a single background state and (2) wandering among multiple "attractor" states, which encode a single or several stimulus features. Studying simplified network rate models of the primary visual cortex (V1), we show that the single state scenario is characterized by fast and high-dimensional Gaussian-like fluctuations, whereas in the multiple state scenario the fluctuations are slow, low dimensional, and highly non-Gaussian. Studying a more realistic model that incorporates correlations in the feed-forward input, spatially restricted cortical interactions, and an experimentally derived layout of pinwheels, we show that recent optical-imaging data of ongoing activity in V1 are consistent with the presence of either a single background state or multiple attractor states encoding many features.
在没有感觉刺激的情况下，大脑皮层中持续的自发活动呈现出复杂的时空模式。为了阐明这种持续活动的本质，我们对皮层动力学的两种对比情况进行了理论探讨：（1）围绕单一背景状态的波动；（2）在多个“吸引子”状态之间徘徊，这些状态编码单个或多个刺激特征。通过研究初级视觉皮层（V1）的简化网络速率模型，我们发现单一状态情况的特征是快速且高维的类高斯波动，而在多状态情况下，波动缓慢、低维且高度非高斯。通过研究一个更现实的模型，该模型纳入了前馈输入中的相关性、空间受限的皮层相互作用以及实验得出的风车布局，我们发现最近关于V1中持续活动的光学成像数据与存在单一背景状态或编码许多特征的多个吸引子状态相一致。
