A simple neural network model of the hippocampus suggesting its pathfinding role in episodic memory retrieval.
A simple neural network model of the hippocampus suggesting its pathfinding role in episodic memory retrieval.
复制标题
海马体的简单神经网络模型表明其在情景记忆检索中的寻路作用。
DOI：
10.1101/lm.85205
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Ascoli,GiorgioA
中科院分区：
文献类型：
--
作者：
Samsonovich,AlexeiV;Ascoli,GiorgioA
本研究的目的是将对海马体空间和记忆功能关系的理论认识扩展到空间导航和情景记忆检索的神经生理机制水平。提出的统一理论在一个独特的框架内描述了这两种现象，基于海马体的一个相同的寻路功能。我们提出了一种重建经验背景的机制，包括在记忆背景的空间中寻找几乎最短的路径。为了详细分析这一概念，我们定义了一个简单的连接主义模型，与现有的啮齿动物和人类神经生理学数据一致。该模型的数值研究从空间域开始，作为对更复杂现象的简单类比。它演示了如何在熟悉的环境中快速找到几乎最短的路径。我们在数值上证明，在尖波期间的联想学习可以解释海马位置细胞的必要特性。该模型的计算研究扩展到其他认知范式，主要集中在情景记忆检索。我们表明，找到正确路径的能力可能对成功检索至关重要。该模型在多个因素范围内稳健地展示了寻路能力，包括其记忆负荷（多达30,000个抽象上下文），与潜在目标上下文相关的情节数量以及动态噪声水平。我们在空间和记忆领域提供了几个可测试的关键预测来验证该理论。研究结果表明：(1)海马的寻路功能，以及其联想和记忆索引功能，可能对某些情景记忆的检索至关重要；(2)海马空间导航功能可能是其记忆功能的先驱。
The goal of this work is to extend the theoretical understanding of the relationship between hippocampal spatial and memory functions to the level of neurophysiological mechanisms underlying spatial navigation and episodic memory retrieval. The proposed unifying theory describes both phenomena within a unique framework, as based on one and the same pathfinding function of the hippocampus. We propose a mechanism of reconstruction of the context of experience involving a search for a nearly shortest path in the space of remembered contexts. To analyze this concept in detail, we define a simple connectionist model consistent with available rodent and human neurophysiological data. Numerical study of the model begins with the spatial domain as a simple analogy for more complex phenomena. It is demonstrated how a nearly shortest path is quickly found in a familiar environment. We prove numerically that associative learning during sharp waves can account for the necessary properties of hippocampal place cells. Computational study of the model is extended to other cognitive paradigms, with the main focus on episodic memory retrieval. We show that the ability to find a correct path may be vital for successful retrieval. The model robustly exhibits the pathfinding capacity within a wide range of several factors, including its memory load (up to 30,000 abstract contexts), the number of episodes that become associated with potential target contexts, and the level of dynamical noise. We offer several testable critical predictions in both spatial and memory domains to validate the theory. Our results suggest that (1) the pathfinding function of the hippocampus, in addition to its associative and memory indexing functions, may be vital for retrieval of certain episodic memories, and (2) the hippocampal spatial navigation function could be a precursor of its memory function.
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