Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Institució Catalana de la Recerca i Estudis Avançats, Universitat Pompeu Fabra, Barcelona, Spain.
Nat Rev Neurosci. 2019 Feb;20(2):117-127. doi: 10.1038/s41583-018-0094-0.
The brain is organized as a network of highly specialized networks of spiking neurons. To exploit such a modular architecture for computation, the brain has to be able to regulate the flow of spiking activity between these specialized networks. In this Opinion article, we review various prominent mechanisms that may underlie communication between neuronal networks. We show that communication between neuronal networks can be understood as trajectories in a two-dimensional state space, spanned by the properties of the input. Thus, we propose a common framework to understand neuronal communication mediated by seemingly different mechanisms. We also suggest that the nesting of slow (for example, alpha-band and theta-band) oscillations and fast (gamma-band) oscillations can serve as an important control mechanism that allows or prevents spiking signals to be routed between specific networks. We argue that slow oscillations can modulate the time required to establish network resonance or entrainment and, thereby, regulate communication between neuronal networks.
大脑组织为高度专业化的神经元网络网络。为了利用这种模块化架构进行计算,大脑必须能够调节这些专门网络之间的尖峰活动的流动。在这篇观点文章中,我们回顾了可能构成神经元网络之间通信基础的各种突出机制。我们表明,神经元网络之间的通信可以理解为二维状态空间中的轨迹,该状态空间由输入的特性来界定。因此,我们提出了一个共同的框架来理解由看似不同的机制介导的神经元通信。我们还建议,慢(例如,alpha 波段和 theta 波段)振荡和快(gamma 波段)振荡的嵌套可以作为一种重要的控制机制,允许或阻止尖峰信号在特定网络之间路由。我们认为,慢振荡可以调节建立网络共振或同步所需的时间,从而调节神经元网络之间的通信。