Center for Neuroscience - Swammerdam Institute for Life Sciences, Universiteit van Amsterdam, Science Park 904 1098XH, Amsterdam, The Netherlands.
Neurosci Biobehav Rev. 2012 Aug;36(7):1626-39. doi: 10.1016/j.neubiorev.2012.04.004. Epub 2012 Apr 17.
Much of animal and human cognition is compositional in nature: higher order, complex representations are formed by (rule-governed) combination of more primitive representations. We review here some of the evidence for compositionality in perception and memory, motivating an approach that takes ideas and techniques from computational linguistics to model aspects of structural representation in cognition. We summarize some recent developments in our work that, on the one hand, use algorithms from computational linguistics to model memory consolidation and the formation of semantic memory, and on the other hand use insights from the neurobiology of memory to develop a neurally inspired model of syntactic parsing that improves over existing (not cognitively motivated) models in computational linguistics. These two theoretical studies highlight interesting analogies between language acquisition, semantic memory and memory consolidation, and suggest possible neural mechanisms, implemented in computational algorithms that may underlie memory consolidation.
更高级、更复杂的表示形式是通过（受规则支配的）原始表示形式的组合形成的。我们在这里回顾了一些关于感知和记忆中的组合性的证据，提出了一种方法，该方法借鉴了计算语言学的思想和技术，以模型认知中的结构表示的某些方面。我们总结了我们工作中的一些最新进展，一方面，使用计算语言学中的算法来模型记忆巩固和语义记忆的形成，另一方面，利用记忆神经生物学的见解来开发一种受神经启发的句法分析模型，该模型在计算语言学中的现有（非认知驱动的）模型基础上进行了改进。这两个理论研究强调了语言习得、语义记忆和记忆巩固之间的有趣相似之处，并提出了可能的神经机制，这些机制通过计算算法实现，可能是记忆巩固的基础。
