Jeewajee A, Barry C, O'Keefe J, Burgess N
Institute of Cognitive Neuroscience, University College London (UCL), London, United Kingdom.
Hippocampus. 2008;18(12):1175-85. doi: 10.1002/hipo.20510.
The oscillatory interference model (Burgess et al. (2007) Hippocampus 17:801-812) explains the generation of spatially stable, regular firing patterns by medial entorhinal cortical (mEC) grid cells in terms of the interference between velocity-controlled oscillators (VCOs) with different preferred directions. This model predicts specific relationships between the intrinsic firing frequency and spatial scale of grid cell firing, the EEG theta frequency, and running speed (Burgess,2008). Here, we use spectral analyses of EEG and of spike autocorrelograms to estimate the intrinsic firing frequency of grid cells, and the concurrent theta frequency, in mEC Layer II in freely moving rats. The intrinsic firing frequency of grid cells increased with running speed and decreased with grid scale, according to the quantitative prediction of the model. Similarly, theta frequency increased with running speed, which was also predicted by the model. An alternative Moiré interference model (Blair et al.,2007) predicts a direction-dependent variation in intrinsic firing frequency, which was not found. Our results suggest that interference between VCOs generates the spatial firing patterns of entorhinal grid cells according to the oscillatory interference model. They also provide specific constraints on this model of grid cell firing and have more general implications for viewing neuronal processing in terms of interfering oscillatory processes.
振荡干扰模型(Burgess等人,2007年,《海马体》17:801 - 812)依据具有不同偏好方向的速度控制振荡器(VCO)之间的干扰,解释了内侧内嗅皮质(mEC)网格细胞如何产生空间稳定、规则的放电模式。该模型预测了网格细胞放电的固有放电频率与空间尺度、脑电图θ频率以及奔跑速度之间的特定关系(Burgess,2008年)。在此,我们利用脑电图和尖峰自相关图的频谱分析,来估计自由活动大鼠mEC第二层中网格细胞的固有放电频率以及同时出现的θ频率。根据该模型的定量预测,网格细胞的固有放电频率随奔跑速度增加而升高,随网格尺度减小而降低。同样,θ频率也随奔跑速度增加,这也是该模型所预测的。另一种莫尔干涉模型(Blair等人,2007年)预测固有放电频率存在方向依赖性变化,但未得到证实。我们的结果表明,VCO之间的干扰根据振荡干扰模型产生了内嗅网格细胞的空间放电模式。它们还为这种网格细胞放电模型提供了具体限制,并对从干扰振荡过程角度看待神经元处理具有更广泛的意义。