Summary: A new study has fundamentally redrawn our understanding of the bilingual brain, proving that multilingual speakers do not possess separate grammatical rulebooks in their gray matter, but instead rely on a single, shared neural engine.
Utilizing millisecond-by-millisecond magnetoencephalography (MEG) brain imaging, the research team monitored Spanish-English bilingual speakers as they performed real-time grammatical transformations on real words, cognates, and completely fabricated pseudowords.
The empirical tracking data unmasked an identical, language-transcendent neural template firing across both tongues, demonstrating that human grammar is executed as a highly reusable, universal computational loop rather than a collection of separate, language-specific engines.
Key Facts
- Dismantling the Dual Engine Myth: While bilingual individuals occasionally slip and mix up grammatical rules across tongues, this study delivers definitive neural proof that these errors are not caused by separate grammar engines colliding. Instead, the brain uses a single, unified system to handle every language a person speaks.
- Millisecond-by-Millisecond Tracking: To capture the lightning-fast speed of human speech processing, the NYU team used high-resolution magnetoencephalography (MEG). This advanced neuroimaging tool maps exact magnetic fields in the brain, allowing scientists to watch grammatical computations unfold down to the millisecond.
- The Morphological Stress Test: During the MEG scans, bilingual participants were tasked with instantly transforming singular words into their correct grammatical plural forms across both English and Spanish, such as shifting “boat” to “boats” or “barco” to “barcos.”
- Deploying Pseudoword Controls: To make sure the brain was not simply pulling pre-memorized words from a mental dictionary, the investigators introduced fabricated pseudowords like “paple.” The identical neural firing pattern emerged during these novel trials, proving the brain applies a generalized grammatical formula to new vocabulary.
- A Reusable Computational Template: The data proves that the brain treats grammar as an abstract, reusable computation. Whether processing distinct phonetic sounds, matching cognates, or navigating completely fake terms, the underlying neural network remains perfectly constant.
- The Evolution of Language Acquisition: These findings provide public education sectors, language developers, and cognitive scientists with a foundational insight into how humans learn new languages. Because the core grammatical engine is shared, learning a third or fourth language involves feeding new vocabulary into an existing template rather than building a new cognitive system from scratch.
- Federal Research Backing: Highlighting its immediate value to the fields of linguistics and cognitive healthspan, this neurotrauma and language architecture project was funded by major federal grants from the National Science Foundation and the National Institutes of Health.
Source: NYU
It’s not uncommon for bilingual speakers to mistakenly apply the grammatical rules of one language while speaking the other—for example, saying “I have 20 years” instead of “I am 20” when asked about their age.
Some may wonder if these language mashups are evidence of deeper neurological distinctions among languages: If you speak English and Spanish, for instance, do you have an English “grammatical engine” that learns and applies English rules and a Spanish one that learns and applies Spanish rules?
A new study by a team of New York University scientists finds that, in fact, bilingualism is not powered by separate grammar engines in the brain, but, rather, by a common neural system that works across languages.
“Our research suggests that brains have a single grammatical engine that fuels all of the languages we speak—rather than separate engines for each one,” explains Esti Blanco-Elorrieta, an assistant professor of psychology and neural science at NYU and the senior author of the study, which appears in Journal of Neuroscience. “We show that the same brain patterns support grammar in English and Spanish, indicating that human language may be built from neural computations that transcend any one language.”
While previous research has found neurological commonality across speakers of different languages and other NYU research has explored “bilingual brains,” less clear is how the brain builds grammar across languages in bilingual speakers.
To address this, Blanco-Elorrieta and Xuanyi Jessica Chen, an NYU doctoral student and the paper’s first author, used magnetoencephalography (MEG) to track brain activity millisecond-by-millisecond while Spanish-English bilingual speakers transformed both English and Spanish words into grammatically correct forms. For instance, participants would hear a singular form of a word (“boat” [English] or “barco” [Spanish]) and were asked to say the plural version of the term (e.g., “boats” or “barcos”).
The researchers also tested how participants responded to both cognates—words in different languages that share a similar meaning, spelling, and pronunciation because of their common linguistic roots—and “pseudowords” (made-up words such as “paple”).
This method, which reached beyond existing words in English and Spanish, was aimed at determining if the same neural mechanisms apply when novel words enter our vocabulary.
The findings showed that the brain relies on a shared neural mechanism for grammar across languages, even when words differ in sound or structure. Moreover, the same neural system also applied to completely novel words (i.e., pseudowords), further suggesting that the brain implements grammar as a reusable computation—or universal language template—rather than deploying multiple language-specific rulebooks.
“The results provide some of the clearest neural evidence to date that grammatical computations are shared across languages in bilingual speakers,” says Blanco-Elorrieta, who previously teamed up with Chen to create a calculator to measure multilingualism. “More broadly, because the brain appears to use a common neural system across languages, our findings offer new insight into how we communicate and learn new 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: While it feels like your brain is accidentally crossing the wires between two separate language systems, this NYU study proves the opposite is true. Bilingual slip-ups happen precisely because your brain uses a single, shared grammatical engine to power every language you speak. Instead of spinning up a brand-new motor for a second language, the brain runs all your vocabulary through the exact same computational loop, occasionally causing a rule from one language to temporarily overlap onto another.
A: An MEG scan, or magnetoencephalography, is a highly advanced brain-imaging tool that measures the microscopic magnetic fields produced by the brain’s natural electrical activity. Because human thought and speech happen in a fraction of a second, standard brain scans are simply too slow to catch the process in action. MEG imaging tracks the brain millisecond-by-millisecond, allowing neuroscientists to watch the exact moment a grammatical rule is calculated and proving the same neural pattern fires regardless of the language spoken.
A: To prove that the brain is actively calculating grammar rules on the fly rather than just pulling memorized words from a mental storage locker. If the scientists only used real words like “boats,” critics could argue the brain was just remembering the word as a whole piece. By forcing bilingual speakers to pluralize completely made-up pseudowords like “paple,” the team proved that the brain possesses an abstract, reusable grammatical formula that it can instantly stamp onto any new word that enters your vocabulary.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this language and neuroscience research news
Author: James Devitt
Source: NYU
Contact: James Devitt – 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 implements abstract computations that must generalize across superficially different inputs. Language provides a strong test case: the same grammatical operation, such as pluralization, can be realized through distinct rules and forms across languages.
Whether such transformations rely on language-specific neural systems or on abstract mechanisms that generalize across linguistic contexts remains unresolved. Crucially, these transformations must be computed online and integrated into speech planning within a tightly constrained time window.
Using magnetoencephalography (MEG), we tracked the millisecond dynamics of grammatical word-form transformations during semi-naturalistic phrase completion in humans of both sexes. Highly proficient Spanish–English bilinguals produced singular and plural noun forms in both languages in a design that fully orthogonalized semantic number, phonological changes, grammatical inflection and produced language. Adjusting words to fit their grammatical context engaged a left-lateralized fronto-temporal network beginning ∼100 ms after cue onset.
Multivariate decoding revealed that the neural patterns supporting this computation generalized across languages, across different surface plural forms, and to pseudowords, demonstrating that abstractly equivalent operations are instantiated in the same neural substrates despite differences in linguistic form. Together, these findings provide time-resolved neural evidence for a language-general computational mechanism, showing that the brain implements grammatical transformations as abstract, generative operations.
More broadly, they show how bilingualism can be used to probe general principles of neural organization, revealing how abstract computations may be shared and reused across representational systems.
