Mapping language with resting‐state functional magnetic resonance imaging: A study on the functional profile of the language network

Resting‐state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task‐execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that lan...

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Bibliographic Details
Published in:Human brain mapping 2020-02, Vol.41 (2), p.545-560
Main Authors: Branco, Paulo, Seixas, Daniela, Castro, São L.
Format: Article
Language:English
Subjects:
Brain
Brain mapping
Computational linguistics
functional connectivity
Functional magnetic resonance imaging
Homology
Language
language network
Language processing
Magnetic resonance imaging
Mapping
Natural language interfaces
Neuroimaging
NMR
Nuclear magnetic resonance
presurgical planning
Resonance
resting‐state fMRI
Semantics
Sentences
Stimuli
Symbols
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Summary:Resting‐state functional magnetic resonance imaging (rsfMRI) is a promising technique for language mapping that does not require task‐execution. This can be an advantage when language mapping is limited by poor task performance, as is common in clinical settings. Previous studies have shown that language maps extracted with rsfMRI spatially match their task‐based homologs, but no study has yet demonstrated the direct participation of the rsfMRI language network in language processes. This demonstration is critically important because spatial similarity can be influenced by the overlap of domain‐general regions that are recruited during task‐execution. Furthermore, it is unclear which processes are captured by the language network: does it map rather low‐level or high‐level (e.g., syntactic and lexico‐semantic) language processes? We first identified the rsfMRI language network and then investigated task‐based responses within its regions when processing stimuli of increasing linguistic content: symbols, pseudowords, words, pseudosentences and sentences. The language network responded only to language stimuli (not to symbols), and higher linguistic content elicited larger brain responses. The left fronto‐parietal, the default mode, and the dorsal attention networks were examined and yet none showed language involvement. These findings demonstrate for the first time that the language network extracted through rsfMRI is able to map language in the brain, including regions subtending higher‐level syntactic and semantic processes.
ISSN:1065-9471
1097-0193
DOI:10.1002/hbm.24821