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海马结构空间信号的神经网络建模及其在导航中的可能作用:一种模块化方法。

Neural network modeling of the hippocampal formation spatial signals and their possible role in navigation: a modular approach.

作者信息

Sharp P E, Blair H T, Brown M

机构信息

Department of Psychology, Yale University, New Haven, Connecticut 06520-8205, USA.

出版信息

Hippocampus. 1996;6(6):720-34. doi: 10.1002/(SICI)1098-1063(1996)6:6<720::AID-HIPO14>3.0.CO;2-2.

Abstract

Cells throughout the hippocampal formation show striking spatial firing correlates as a rat navigates through space. These cells are thought to play a critical role in orchestrating the navigational abilities of the animals, since damage to the hippocampal formation causes spatial learning deficits. Here, we present a theoretical framework aimed at explaining how the different spatial signals are generated, as well as how they may help guide navigational behavior. Earlier work from our laboratory has presented a simple model for how the location-related signals exhibited by hippocampal place cells could be generated, based on convergent sensory information. Here, the results of this work are combined with two more recent models, to provide a more comprehensive theoretical framework. Specifically, we present 1) A neural network model of head direction cells, based on the idea that the directional signals are generated using a path integration mechanism. Cells which combine directional and angular head velocity information project onto the head direction cells, to "update" the current directional signal. This model reproduces the basic phenomenon of direction-specific firing, as well as the anticipatory nature of this firing, reported for some head direction cells. 2) A network simulation of how the hippocampal spatial signals could be used to orchestrate instrumental learning. Here, place and directional signals converge onto motor cells, each of which are thus driven to fire to specific combinations of location and directional heading. Each active motor cell generates a small leftward or rightward "step" of the simulated animal. When the simulated goal is encountered, recently active synapses are strengthened, so that goal-directed trajectories are "stamped in". We have found these models useful in helping to clarify our thinking about the proposed theoretical principles, as well as in generating testable predictions.

摘要

当大鼠在空间中导航时,海马结构中的细胞会表现出显著的空间放电相关性。这些细胞被认为在协调动物的导航能力方面起着关键作用,因为海马结构受损会导致空间学习缺陷。在这里,我们提出一个理论框架,旨在解释不同的空间信号是如何产生的,以及它们如何帮助引导导航行为。我们实验室早期的工作基于汇聚的感官信息,提出了一个关于海马位置细胞所表现出的与位置相关信号如何产生的简单模型。在这里,这项工作的结果与另外两个更新的模型相结合,以提供一个更全面的理论框架。具体来说,我们提出:1)一个头部方向细胞的神经网络模型,其基于方向信号是使用路径积分机制产生的这一观点。将方向和角向头部速度信息相结合的细胞投射到头部方向细胞上,以“更新”当前的方向信号。该模型再现了一些头部方向细胞所报道的方向特异性放电的基本现象,以及这种放电的预期性质。2)一个关于海马空间信号如何用于协调工具性学习的网络模拟。在这里,位置和方向信号汇聚到运动细胞上,每个运动细胞因此被驱动以特定的位置和方向组合进行放电。每个活跃的运动细胞会使模拟动物产生一个小的向左或向右“步长”。当遇到模拟目标时,最近活跃的突触会被加强,从而使目标导向的轨迹被“铭刻”下来。我们发现这些模型有助于澄清我们对所提出的理论原则的思考,以及产生可测试的预测。

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