Merge-based syntax is mediated by distinct neurocognitive mechanisms: A clustering analysis of comprehension abilities in 84,000 individuals with language deficits across nine languages
Elliot Murphy, Rohan Venkatesh, Edward Khokhlovich, Andrey Vyshedskiy

TL;DR
This study analyzes how different neurocognitive mechanisms support various Merge-based syntactic structures, revealing three distinct processing types in a large, diverse population, with implications for language development and impairments.
Contribution
It provides evidence for multiple neurocognitive mechanisms underlying Merge-based syntax, challenging the idea of a single, elementary operation in language processing.
Findings
Identified three distinct structural types in comprehension abilities
Behavioral evidence suggests different mechanisms support different Merge types
Implications for language development and neurocognitive models
Abstract
In the modern language sciences, the core computational operation of syntax, 'Merge', is defined as an operation that combines two linguistic units (e.g., 'brown', 'cat') to form a categorized structure ('brown cat', a Noun Phrase). This can then be further combined with additional linguistic units based on this categorial information, respecting non-associativity such that abstract grouping is respected. Some linguists have embraced the view that Merge is an elementary, indivisible operation that emerged in a single evolutionary step. From a neurocognitive standpoint, different mental objects constructed by Merge may be supported by distinct mechanisms: (1) simple command constructions (e.g., "eat apples"); (2) the merging of adjectives and nouns ("red boat"); and (3) the merging of nouns with spatial prepositions ("laptop behind the sofa"). Here, we systematically investigate…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
