arXiv:2604.00291cs.CL2026-04

用数学模型揭示语言的生物基础,推动神经科学探索语法机制

Frege in the Flesh: Biolinguistics and the Neural Enforcement of Syntactic Structures

  • 将语法生成视为可计算的代数操作,以揭示语言的自然结构
  • 提出语法结构需符合生物神经机制的非平凡约束条件
  • 适合对语言演化与神经机制交叉研究感兴趣的学者

生物语言学是研究人类语言的生物学基础、演化及遗传机制的跨学科科学。它将语言视为心智的先天生物器官,而非文化工具,挑战了行为主义认为语言习得源于刺激-反应关联的观点。其核心思想是:数学与代数模型能真实反映世界的本质。其中,语法结构构建操作MERGE被认为提供了一个‘自然的关节’,不仅是形式产物,更是自然界的新方面。该理论为生物学家、遗传学家和神经科学家提供了更清晰的研究路径。本文分四步论证:首先明确生物语言学的研究对象并非语音、交流或一般序列处理,而是生成层次化表达的内部计算系统;其次主张这一形式化表征对进化解释至关重要,因不同语法观意味着不同的解释标准;第三指出,足够明确的代数语法体系会对候选神经机制施加非平凡约束;最后探讨近期神经计算研究如何将这些约束转化为可检验的假设,同时强调当前研究仍具推测性与可修订性。

原文摘要 · Abstract (English)

Biolinguistics is the interdisciplinary scientific study of the biological foundations, evolution, and genetic basis of human language. It treats language as an innate biological organ or faculty of the mind, rather than a cultural tool, and it challenges a behaviorist conception of human language acquisition as being based on stimulus-response associations. Extracting its most essential component, it takes seriously the idea that mathematical, algebraic models of language capture something natural about the world. The syntactic structure-building operation of MERGE is thought to offer the scientific community a "real joint of nature", "a (new) aspect of nature" (Mukherji 2010), not merely a formal artefact. This mathematical theory of language is then seen as being able to offer biologists, geneticists and neuroscientists clearer instructions for how to explore language. The argument of this chapter proceeds in four steps. First, I clarify the object of inquiry for biolinguistics: not speech, communication, or generic sequence processing, but the internal computational system that generates hierarchically structured expressions. Second, I argue that this formal characterization matters for evolutionary explanation, because different conceptions of syntax imply different standards of what must be explained. Third, I suggest that a sufficiently explicit algebraic account of syntax places non-trivial constraints on candidate neural mechanisms. Finally, I consider how recent neurocomputational work begins to transform these constraints into empirically tractable hypotheses, while also noting the speculative and revisable character of the present program.

生物语言学语法结构神经机制

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