Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The intensively studied neuron type circuitry of the hippocampus is a particularly conducive substrate for spiking neural models. Here we present an online knowledge base of spiking neural network simulations of hippocampal functions. First, we overview theories involving the hippocampal formation in subjects such as spatial representation, learning, and memory. Then we describe an original literature mining process to organize published reports in various key aspects, including: (i) subject area (e.g., navigation, pattern completion, epilepsy); (ii) level of modeling detail (Hodgkin-Huxley, integrate-and-fire, etc.); and (iii) theoretical framework (attractor dynamics, oscillatory interference, self-organizing maps, and others). Moreover, every peer-reviewed publication is also annotated to indicate the specific neuron types represented in the network simulation, establishing a direct link with the Hippocampome.org portal. The web interface of the knowledge base enables dynamic content browsing and advanced searches, and consistently presents evidence supporting every annotation. Moreover, users are given access to several types of statistical reports about the collection, a selection of which is summarized in this paper. This open access resource thus provides an interactive platform to survey spiking neural network models of hippocampal functions, compare available computational methods, and foster ideas for suitable new directions of research.

计算模型以多种方式和多种方法为海马体研究做出了贡献，反映了该大脑区域的许多高级认知作用。深入研究的海马体神经元型电路是脉冲神经模型的特别有利的基质。在这里，我们提出了海马功能的尖峰神经网络模拟在线知识库。首先，我们概述了涉及空间表征、学习和记忆等学科中海马体形成的理论。然后我们描述了一个原始文献挖掘过程，以在各个关键方面组织已发表的报告，包括：（i）主题领域（例如，导航、模式完成、癫痫）；(ii) 建模细节级别（Hodgkin-Huxley、integrate-and-fire 等）；(iii) 理论框架（吸引子动力学、振荡干扰、自组织映射等）。此外，每份经过同行评审的出版物还附有注释，以指明网络模拟中表示的特定神经元类型，从而与 Hippocampome.org 门户网站建立直接链接。知识库的 Web 界面支持动态内容浏览和高级搜索，并始终如一地提供支持每个注释的证据。此外，用户可以访问有关馆藏的几种类型的统计报告，本文总结了其中的一部分。因此，这种开放获取资源提供了一个交互式平台，用于调查海马功能的尖峰神经网络模型、比较可用的计算方法，并为合适的新研究方向培养想法。