Department of Physics, University of California Berkeley, Berkeley, California, United States of America.
PLoS Comput Biol. 2010 Sep 9;6(9):e1000927. doi: 10.1371/journal.pcbi.1000927.
Synchronized gamma frequency oscillations in neural networks are thought to be important to sensory information processing, and their effects have been intensively studied. Here we describe a mechanism by which the nervous system can readily control gamma oscillation effects, depending selectively on visual stimuli. Using a model neural network simulation, we found that sensory response in the primary visual cortex is significantly modulated by the resonance between "spontaneous" and "stimulus-driven" oscillations. This gamma resonance can be precisely controlled by the synaptic plasticity of thalamocortical connections, and cortical response is regulated differentially according to the resonance condition. The mechanism produces a selective synchronization between the afferent and downstream neural population. Our simulation results explain experimental observations such as stimulus-dependent synchronization between the thalamus and the cortex at different oscillation frequencies. The model generally shows how sensory information can be selectively routed depending on its frequency components.
神经网络中的同步伽马频率振荡被认为对感觉信息处理很重要,其影响已得到深入研究。在这里,我们描述了一种机制,通过该机制,神经系统可以根据视觉刺激选择性地控制伽马振荡效应。使用模型神经网络模拟,我们发现初级视觉皮层的感觉反应显著受到“自发”和“刺激驱动”振荡之间的共振的调制。这种伽马共振可以通过丘脑皮质连接的突触可塑性精确控制,并且根据共振条件,皮质反应会被差异化调节。该机制在传入和下游神经元群体之间产生选择性同步。我们的模拟结果解释了实验观察结果,例如在不同的振荡频率下,丘脑和皮层之间的刺激依赖性同步。该模型通常说明了如何根据其频率成分有选择地路由感觉信息。