Summary: New research reshapes our understanding of how bilingual brains handle grammar. The study shows that multilingual speakers do not store separate grammatical rulebooks for each language. Instead, they use a single, shared neural mechanism that computes grammar across languages.
Using high‑temporal‑resolution magnetoencephalography (MEG), researchers at New York University recorded millisecond‑by‑millisecond brain activity while Spanish‑English bilinguals performed live grammatical transformations on real words, cognates, and invented pseudowords.
Those fine‑grained measurements revealed the same neural template activating across both languages, indicating that grammar operates as a reusable, language‑general computational process rather than as separate language‑specific engines.
Key Facts
- Dismantling the dual‑engine idea: Although bilingual speakers sometimes insert rules from one language into another, the neural evidence shows these slips do not come from two distinct grammar systems colliding. The brain runs all languages through a single, unified grammatical computation.
- Millisecond tracking with MEG: To capture the rapid timing of speech planning, the team used magnetoencephalography. MEG records tiny magnetic fields linked to neural activity and reveals the precise moments when grammatical computations occur.
- The pluralization task: Participants heard singular nouns in English or Spanish and were asked to produce the plural form (for example, “boat” → “boats,” “barco” → “barcos”), allowing researchers to observe grammar computations in real time.
- Pseudoword controls: Introducing made‑up words such as “paple” ruled out reliance on memorized lexical forms. The same neural pattern emerged when participants pluralized pseudowords, showing the brain applies an abstract grammatical rule to novel items.
- A reusable computational template: The data indicate that a single neural network supports grammatical transformations across different sounds, cognate relationships, and entirely novel terms—evidence for an abstract, language‑general operation.
- Implications for language learning: Because grammar appears to be handled by a shared engine, acquiring additional languages likely involves mapping new vocabulary onto an existing computational framework rather than building a wholly new grammatical system.
- Funded research: This project received support from the National Science Foundation and the National Institutes of Health, reflecting its relevance to linguistics and cognitive neuroscience.
Source: NYU
Everyday slips: It is common for bilingual speakers to occasionally apply the grammar of one language while speaking another—for example, saying “I have 20 years” instead of “I am 20.” Such errors might seem to imply separate grammatical systems, but the study offers a different explanation.
Researchers led by Esti Blanco‑Elorrieta at New York University tested how the bilingual brain builds and applies grammatical rules. Rather than finding separate language‑specific grammar engines, they observed the same neural computations supporting grammar in both English and Spanish.
“Our results indicate that the brain uses one grammatical engine for all the languages a person speaks, not separate engines for each language,” says Esti Blanco‑Elorrieta, assistant professor of psychology and neural science and senior author of the study, published in the Journal of Neuroscience. “The same neural patterns supported grammatical processing in English and Spanish, suggesting that grammar relies on neural computations that generalize across languages.”
Previous work hinted at shared neural features across speakers of different languages, but the specific question of how bilingual individuals compute grammar in real time remained unresolved. To address it, Blanco‑Elorrieta and first author Xuanyi Jessica Chen recorded MEG while proficient Spanish‑English bilinguals completed a structured pluralization task that separated semantic number, phonological change, inflection type, and language produced.
Participants produced singular and plural noun forms in both languages and responded to cognates—words with shared form and meaning across languages—as well as to pseudowords. This approach tested whether the same neural computations applied when participants handled familiar vocabulary, cognates, and completely novel items.
Across conditions, grammatical adjustments engaged a left‑lateralized fronto‑temporal network beginning roughly 100 milliseconds after the cue. Multivariate analyses showed that the neural patterns supporting pluralization generalized across languages, across different plural forms, and to pseudowords. In short, abstractly equivalent grammatical operations were instantiated in the same neural substrates despite surface differences in linguistic form.
“These results offer clear, time‑resolved neural evidence that grammatical computations are shared across languages in bilingual speakers,” says Blanco‑Elorrieta. “They shed light on how we communicate and on the neural principles that let us learn additional languages.”
Funding: This research was supported by grants from the National Science Foundation (BCS‑Grant 2446452) and the National Institutes of Health (R00 DC019973‑01).
Key Questions Answered:
A: Those slips are a byproduct of using a single grammatical system for multiple languages. The brain runs all vocabulary through the same computational loop, so a rule from one language can occasionally influence output in another. That overlap reflects shared processing rather than two separate systems interfering with each other.
A: Magnetoencephalography (MEG) measures the tiny magnetic fields produced by neural electrical activity. Because grammar computations and speech planning unfold in milliseconds, MEG’s high temporal precision was essential to observe when and how grammatical rules are computed in the brain and to show that the same neural pattern appears regardless of language.
A: Pseudowords ensure participants cannot rely on memorized lexical forms. When the same neural pattern appears for made‑up words, it demonstrates the brain is computing grammatical structure dynamically, applying an abstract rule to novel items rather than retrieving stored word forms.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- The journal paper was reviewed in full.
- Additional context was added by staff.
About this language and neuroscience research news
Author: James Devitt
Source: NYU
Contact: James Devitt
Image: The image is credited to Neuroscience News
Original Research: Open access. “A Shared Neural Mechanism for Abstract Grammatical Computations Across Languages in Bilinguals” by Xuanyi Jessica Chen and Esti Blanco‑Elorrieta. Journal of Neuroscience
DOI: 10.1016/j.scib.2026.02.053
Abstract
A Shared Neural Mechanism for Abstract Grammatical Computations Across Languages in Bilinguals
A central question in cognitive neuroscience is how the brain carries out abstract computations that must generalize across inputs that look different on the surface. Language provides an ideal test case: the same grammatical operation, such as pluralization, can appear in distinct forms across languages. Do such transformations rely on language‑specific neural systems, or on abstract mechanisms that generalize across linguistic contexts?
Using magnetoencephalography, the study tracked millisecond dynamics of grammatical word‑form transformations during semi‑naturalistic phrase completion. Highly proficient Spanish–English bilinguals produced singular and plural noun forms in both languages in a design that fully separated semantic number, phonological change, grammatical inflection, and produced language. Adjusting words to fit grammatical context engaged a left‑lateralized fronto‑temporal network beginning about 100 ms after the cue.
Multivariate decoding showed that the neural patterns supporting this computation generalized across languages, across different surface plural forms, and to pseudowords. These results demonstrate that abstractly equivalent grammatical operations are implemented in the same neural substrates despite differences in linguistic form. Together, the findings provide time‑resolved neural evidence for a language‑general computational mechanism, showing that the brain implements grammatical transformations as abstract, generative operations and revealing how bilingualism can illuminate general principles of neural organization.