Pre-surgical language mapping with functional magnetic resonance imaging (fMRI) is routinely conducted to assist the neurosurgeon in preventing damage to brain regions responsible for language. Functional differences exist between the monolingual versus the bilingual brain, whereas clinical fMRI tasks are typically conducted in a single language. The presence of secondary language processing mechanisms is a potential source of error in the inferred language map. From fMRI data of healthy bilingual and monolingual subjects we obtain language maps as functional networks. Our results show a sub-network "core" architecture consisting of the Broca's, pre-supplementary motor, and premotor areas present across all subjects. Wernicke's Area was found to connect to the "core" to a different extent across groups. The k core centrality measure shows "core" areas belong to the maximum core while WA and other fROIs vary across groups. The results may provide a benchmark to preserve equal treatment outcomes for bilingual patients.
@article{arxiv.1909.03109,
title = {Monolingual and bilingual language networks in healthy subjects using functional MRI and graph theory},
author = {Qiongge Li and Luca Pasquini and Gino Del Ferraro and Madeleine Gene and Kyung K. Peck and Hernán A. Makse and Andrei I. Holodny},
journal= {arXiv preprint arXiv:1909.03109},
year = {2020}
}