标题： 在生物现实模型中的模拟语言习得 显示英文标题

标题： Simulated Language Acquisition in a Biologically Realistic Model of the Brain

摘要： 尽管在神经科学领域取得了巨大进展，但我们还没有一个令人信服的叙述，说明我们大脑中神经元的放电如何精确地导致高层次的认知现象，如计划和语言。 我们引入了神经科学六个基本且广泛接受的原则的简单数学公式：兴奋性神经元，脑区，随机突触，赫布可塑性，局部抑制和区域间抑制。 我们实现了一个基于这种形式主义的模拟神经形态系统，该系统能够进行基本的语言习得：从一张白纸开始，系统在任何语言中学习单词的语义、它们的句法角色（动词与名词）以及语言的词序，包括生成新句子的能力，通过暴露于同一语言中的少量具体句子。 我们讨论了这个结果的几种可能扩展和含义。 显示英文摘要

摘要： Despite tremendous progress in neuroscience, we do not have a compelling narrative for the precise way whereby the spiking of neurons in our brain results in high-level cognitive phenomena such as planning and language. We introduce a simple mathematical formulation of six basic and broadly accepted principles of neuroscience: excitatory neurons, brain areas, random synapses, Hebbian plasticity, local inhibition, and inter-area inhibition. We implement a simulated neuromorphic system based on this formalism, which is capable of basic language acquisition: Starting from a tabula rasa, the system learns, in any language, the semantics of words, their syntactic role (verb versus noun), and the word order of the language, including the ability to generate novel sentences, through the exposure to a modest number of grounded sentences in the same language. We discuss several possible extensions and implications of this result.