Monolingual and bilingual language networks in healthy subjects using functional MRI and graph theory

TL;DR

This study uses fMRI and graph theory to compare monolingual and bilingual brain language networks, identifying core regions and differences that could impact clinical language mapping.

Contribution

It introduces a novel network-based approach to compare language regions in monolingual and bilingual brains using fMRI data.

Findings

Core language network includes Broca's, pre-supplementary motor, and premotor areas.

Wernicke's Area connectivity varies between groups.

Bilingual and monolingual networks show distinct core structures.

Abstract

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.