# Center-Embedding and Constituency in the Brain and a New Characterization of Context-Free Languages

arXiv: https://arxiv.org/abs/2206.13217 · HTML: https://mlsanity.com/paper/2206.13217/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 13 references that are in the map.
- First posted on arXiv 27 Jun 2022.

## Builds on (most cited first, 1 of 1)

- [A Biologically Plausible Parser](https://mlsanity.com/paper/2108.02189/) (2021)

## Built on by (most cited first, 4 of 4)

- [Computation with Sequences in a Model of the Brain](https://mlsanity.com/paper/2306.03812/) (2023)
- [The Architecture of a Biologically Plausible Language Organ](https://mlsanity.com/paper/2306.15364/) (2023)
- [A Bionic Natural Language Parser Equivalent to a Pushdown Automaton](https://mlsanity.com/paper/2404.17343/) (2024)
- [Simulated Language Acquisition in a Biologically Realistic Model of the Brain](https://mlsanity.com/paper/2507.11788/) (2025)

## Abstract (arXiv)

A computational system implemented exclusively through the spiking of neurons was recently shown capable of syntax, that is, of carrying out the dependency parsing of simple English sentences. We address two of the most important questions left open by that work: constituency (the identification of key parts of the sentence such as the verb phrase) and the processing of dependent sentences, especially center-embedded ones. We show that these two aspects of language can also be implemented by neurons and synapses in a way that is compatible with what is known, or widely believed, about the structure and function of the language organ. Surprisingly, the way we implement center embedding points to a new characterization of context-free languages.