Department of Medicine, University of California, San Diego, La Jolla, CA, United States of America.
Departments of Radiology and Neurosciences, UCSD, San Diego, CA, United States of America.
PLoS Comput Biol. 2018 Jun 27;14(6):e1006171. doi: 10.1371/journal.pcbi.1006171. eCollection 2018 Jun.
Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.
睡眠纺锤波是在非快速眼动 (NREM) 睡眠期间出现的短暂振荡事件。纺锤波的密度和同步特性在人类的 MEG 与 EEG 记录中有所不同，而且还与学习表现有关，这表明纺锤波参与了记忆巩固。在这里，我们使用计算模型确定了可能解释皮质结构之间纺锤波特性差异的网络机制。首先，我们报告说，MEG 和 EEG 数据之间纺锤波发生的差异可能源于核心和基质丘脑皮质系统的对比特性。与投射到中层的核心系统相比，投射到浅层的基质系统具有更广泛的丘脑皮质扇出，并且需要募集更大的神经元群体来启动纺锤波。该特性足以解释 EEG 信号中观察到的浅层皮质层中纺锤波密度较低和空间同步性较高的现象。相比之下，在 MEG 记录中，核心系统中的纺锤波发生得更频繁，但同步性较低。此外，与人类记录一致，在模型中，核心系统中的纺锤波独立发生，而基质系统中的纺锤波通常与核心纺锤波共同发生。我们还发现，从 III/IV 层到 V 层的皮质内兴奋性连接促进了从核心系统到基质系统的纺锤波传播，从而导致广泛的纺锤波活动。我们的研究预测，皮质内和皮质间连接的可塑性可能是学习过程中观察到的纺锤波密度增加的一种机制。
