Gluck M A, Myers C E
Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, New Jersey, USA.
Annu Rev Psychol. 1997;48:481-514. doi: 10.1146/annurev.psych.48.1.481.
We review current computational models of hippocampal function in learning and memory, concentrating on those that make strongest contact with psychological issues and behavioral data. Some models build upon Marr's early theories for modeling hippocampal field CA3's putative role in the fast, temporary storage of episodic memories. Other models focus on hippocampal involvement in incrementally learned associations, such as classical conditioning. More recent efforts have attempted to bring functional interpretations of the hippocampal region in closer contact with underlying anatomy and physiology. In reviewing these psychobiological models, three major themes emerge. First, computational models provide the conceptual glue to bind together data from multiple levels of analysis. Second, models serve as important tools to integrate data from both animal and human studies. Third, previous psychological models that capture important behavioral principles of memory provide an important top-down constraint for developing computational models of the neural bases of these behaviors.
我们回顾了当前关于海马体在学习和记忆中功能的计算模型,重点关注那些与心理学问题和行为数据联系最为紧密的模型。一些模型基于马尔早期的理论,用于模拟海马体CA3区在情景记忆快速、临时存储中的假定作用。其他模型则关注海马体在渐进式学习关联中的作用,如经典条件反射。最近的研究试图使对海马体区域的功能解释与基础解剖学和生理学更紧密地联系起来。在回顾这些心理生物学模型时,出现了三个主要主题。第一,计算模型提供了概念框架,将来自多个分析层面的数据整合在一起。第二,模型是整合动物和人类研究数据的重要工具。第三,先前捕捉到记忆重要行为原则的心理学模型,为开发这些行为神经基础的计算模型提供了重要的自上而下的约束。