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The Input–Output Transformation of the Hippocampal Granule Cells: From Grid Cells to Place Fields

机译:海马颗粒细胞的输入输出转换:从网格细胞到放置场

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摘要

Grid cells in the rat medial entorhinal cortex fire (periodically) over the entire environment. These cells provide input to hippocampal granule cells whose output is characterized by one or more small place fields. We sought to understand how this input–output transformation occurs. Available information allows simulation of this process with no freely adjustable parameters. We first examined the spatial distribution of excitation in granule cells produced by the convergence of excitatory inputs from randomly chosen grid cells. Because the resulting summation depends on the number of inputs, it is necessary to use a realistic number (∼1200) and to take into consideration their 20-fold variation in strength. The resulting excitation maps have only modest peaks and valleys. To analyze how this excitation interacts with inhibition, we used an E%-max (percentage of maximal suprathreshold excitation) winner-take-all rule that describes how gamma-frequency inhibition affects firing. We found that simulated granule cells have firing maps that have one or more place fields whose size and number approximates those observed experimentally. A substantial fraction of granule cells have no place fields, as observed experimentally. Because the input firing rates and synaptic properties are known, the excitatory charge into granule cells could be calculated (2–3 pC) and was found to be only somewhat larger than required to fire granule cells (1 pC). We conclude that the input–output transformation of dentate granule does not depend strongly on synaptic modification; place field formation can be understood in terms of simple summation of randomly chosen excitatory inputs, in conjunction with a winner-take-all network mechanism.
机译:大鼠内侧内嗅皮层的网格细胞在整个环境中(周期性地)射击。这些细胞向海马颗粒细胞提供输入,其输出以一个或多个小位置场为特征。我们试图了解这种输入-输出转换是如何发生的。现有信息允许在没有自由可调参数的情况下模拟此过程。我们首先检查了来自随机选择的网格单元的兴奋性输入的收敛产生的颗粒单元中的激发空间分布。由于所得的总和取决于输入的数量,因此有必要使用一个实际数字(〜1200)并考虑其强度的20倍变化。所得的激励图仅具有适度的峰和谷。为了分析这种激发与抑制的相互作用,我们使用了一个E%-max(最大超阈激发的百分比)获胜者通吃规则,该规则描述了伽马频率抑制如何影响发射。我们发现,模拟的颗粒细胞具有发射图,该图具有一个或多个位置场,其大小和数量与实验观察到的近似。如实验观察到的,大部分颗粒细胞没有位置场。由于已知输入的发射速率和突触特性,因此可以计算出进入颗粒细胞的兴奋性电荷(2-3 pC),发现它仅比发射颗粒细胞所需的兴奋性电荷(1 pC)大一些。我们得出的结论是,齿状颗粒的输入-输出转换并不强烈依赖于突触修饰。可以通过将随机选择的激励输入与赢家通吃的网络机制相结合的简单总和来理解场所场的形成。

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