Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, 338 Krieger Hall, 3400 N. Charles St., Baltimore, MD 21218, USA.
J Neurophysiol. 2010 Jun;103(6):3167-83. doi: 10.1152/jn.00932.2009. Epub 2010 Mar 31.
The discovery of grid cells in the medial entorhinal cortex (MEC) permits the characterization of hippocampal computation in much greater detail than previously possible. The present study addresses how an integrate-and-fire unit driven by grid-cell spike trains may transform the multipeaked, spatial firing pattern of grid cells into the single-peaked activity that is typical of hippocampal place cells. Previous studies have shown that in the absence of network interactions, this transformation can succeed only if the place cell receives inputs from grids with overlapping vertices at the location of the place cell's firing field. In our simulations, the selection of these inputs was accomplished by fast Hebbian plasticity alone. The resulting nonlinear process was acutely sensitive to small input variations. Simulations differing only in the exact spike timing of grid cells produced different field locations for the same place cells. Place fields became concentrated in areas that correlated with the initial trajectory of the animal; the introduction of feedback inhibitory cells reduced this bias. These results suggest distinct roles for plasticity of the perforant path synapses and for competition via feedback inhibition in the formation of place fields in a novel environment. Furthermore, they imply that variability in MEC spiking patterns or in the rat's trajectory is sufficient for generating a distinct population code in a novel environment and suggest that recalling this code in a familiar environment involves additional inputs and/or a different mode of operation of the network.
网格细胞在内侧内嗅皮层（MEC）中的发现使得对海马体计算的描述比以前更加详细。本研究探讨了由网格细胞尖峰序列驱动的积分-点火单元如何将网格细胞的多峰空间发射模式转化为海马体位置细胞典型的单峰活动。以前的研究表明，如果位置细胞在其放电场的位置从具有重叠顶点的网格接收输入，则在没有网络相互作用的情况下，这种转换只能成功。在我们的模拟中，这些输入的选择仅通过快速海伯氏可塑性来完成。由此产生的非线性过程对小输入变化非常敏感。仅在网格细胞的精确尖峰定时上有所不同的模拟会为相同的位置细胞产生不同的场位置。位置场集中在与动物初始轨迹相关的区域；引入反馈抑制细胞会降低这种偏差。这些结果表明，在新环境中形成位置场时，穿通路径突触的可塑性和通过反馈抑制的竞争起着不同的作用。此外，它们表明 MEC 尖峰模式或大鼠轨迹的可变性足以在新环境中产生独特的群体代码，并表明在熟悉的环境中回忆此代码涉及额外的输入和/或网络的不同操作模式。
