Modality-Independent Core Brain Network for Language as Proved by Sign Language
Abstract
The human brain has the capacity to automatically compute the grammatical relations of words in sentences, be they spoken or written. This species-specific ability for syntax lies at the core of our capacity for language and is primarily subserved by a left-hemispheric fronto- temporal network consisting of the posterior inferior frontal gyrus (pIFG), as well as the posterior middle temporal gyrus and superior temporal sulcus (pMTG/STS). To date, it remains unclear whether this core network for syntactic processing identified for spoken and written language in hearing people also holds for the processing of the grammatical structure of a natural sign language in deaf people. Using functional magnetic resonance imaging, a sign language paradigm that systematically varied the presence of syntactic and lexical- semantic information, and meta-analytically defined functional regions-of-interests derived from a large dataset of syntactic processing in hearing non-signers, we demonstrate that deaf native signers of German Sign Language (DGS) also recruit left pIFG and pMTG/STS for computing grammatical relations in sign language—indicating the universality of the core language network. These findings suggest that the human brain evolved a dedicated neural network for processing the grammatical structure of natural languages independent of language modality, which flexibly interacts with different externalization systems depending on the modality of language use.
Related
- Naturalistic language assessment and brain-network biomarkers in post-stroke aphasia for precision neurorehabilitation
- The Extended Language Network: Language-Responsive Brain Areas Whose Contributions to Language Remain To Be Discovered
- From Images and Words to Modality-Independent Semantic Representations: When and Where They Emerge
- A Multiverse Approach to Brain Age Prediction: Exploring the Impact of Modality, Bias Adjustment, and Atlas
- Dose- and modality-specific effects of exercise on BDNF and depression in middle-aged and older adults with mild cognitive impairment: A Bayesian network meta-analysis
BibTeX
@misc{trettenbrein2026modalityindependent,
title = {{Modality-Independent Core Brain Network for Language as Proved by Sign Language}},
author = {Patrick C. Trettenbrein and Nina-Kristin Meister and Ksenija Slivac and Thomas A. Finkbeiner and Markus Steinbach and Angela D. Friederici and Emiliano Zaccarella},
howpublished = {PsyArXiv},
year = {2026},
month = oct,
doi = {10.31234/osf.io/hnzgp_v2},
url = {https://osf.io/preprints/psyarxiv/hnzgp_v2/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Modality-Independent Core Brain Network for Language as Proved by Sign Language
AU - Patrick C. Trettenbrein
AU - Nina-Kristin Meister
AU - Ksenija Slivac
AU - Thomas A. Finkbeiner
AU - Markus Steinbach
AU - Angela D. Friederici
AU - Emiliano Zaccarella
PY - 2026
DA - 2026/10/01
PB - PsyArXiv
DO - 10.31234/osf.io/hnzgp_v2
UR - https://osf.io/preprints/psyarxiv/hnzgp_v2/
AB - The human brain has the capacity to automatically compute the grammatical relations of words in sentences, be they spoken or written. This species-specific ability for syntax lies at the core of our capacity for language and is primarily subserved by a left-hemispheric fronto- temporal network consisting of the posterior inferior frontal gyrus (pIFG), as well as the posterior middle temporal gyrus and superior temporal sulcus (pMTG/STS). To date, it remains unclear whether this core network for syntactic processing identified for spoken and written language in hearing people also holds for the processing of the grammatical structure of a natural sign language in deaf people. Using functional magnetic resonance imaging, a sign language paradigm that systematically varied the presence of syntactic and lexical- semantic information, and meta-analytically defined functional regions-of-interests derived from a large dataset of syntactic processing in hearing non-signers, we demonstrate that deaf native signers of German Sign Language (DGS) also recruit left pIFG and pMTG/STS for computing grammatical relations in sign language—indicating the universality of the core language network. These findings suggest that the human brain evolved a dedicated neural network for processing the grammatical structure of natural languages independent of language modality, which flexibly interacts with different externalization systems depending on the modality of language use.
ER -