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Lookup NU author(s): Professor Peter TaylorORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2026 The Author(s). Language is one of the most extensively studied lateralised cognitive functions in the human brain, predominantly relying on the left hemisphere in most individuals. However, the mechanisms by which a stable white matter architecture underpins individual language functions remain unclear. Previous studies have employed structural connectivity (SC) and functional connectivity (FC) coupling for individual fingerprinting and task decoding, suggesting that variability in brain entropy may serve as a distinguishing characteristic for language lateralisation. We examined a large cohort of healthy adults (n = 285) to investigate SC-FC coupling and identify markers distinguishing different language laterality groups. Functional connectivity was measured using resting-state fMRI (rs-fMRI) time-series data, whereas structural connectivity was determined using probabilistic fiber tractography. SC-FC coupling was investigated using the SENSAAS language atlas and defined as the Pearson correlation between the non-zero elements of the regional structural and functional connectivity profiles. Group differences were assessed using the PALM toolbox in the FSL. Our findings revealed that increased SC-FC coupling in the left precentral sulcus was associated with typical language lateralisation, while increased coupling in the right middle temporal gyrus and left anterior insula was observed in individuals with atypical language lateralisation (pFDR <.05). Non-lateralised individuals exhibited increased coupling in the left anterior insula compared to lateralised (pFDR<.05). SC-FC coupling offers a promising framework to uncover functional and anatomical differences among individuals with varying language lateralisation. This regional specificity indicates that typical, atypical, and non-lateralised profiles rely on different structural-functional alignments, likely reflecting the recruitment of alternative pathways for language processing.
Author(s): Andrulyte I, Zago L, Jobard G, Lemaitre H, Taylor PN, Rheault F, Joliot M, Petit L, Keller SS
Publication type: Article
Publication status: Published
Journal: Cortex
Year: 2026
Volume: 204
Pages: 115-132
Print publication date: 01/11/2026
Online publication date: 14/08/2026
Acceptance date: 07/08/2026
Date deposited: 01/09/2026
ISSN (print): 0010-9452
ISSN (electronic): 1973-8102
Publisher: Masson SpA
URL: https://doi.org/10.1016/j.cortex.2026.08.001
DOI: 10.1016/j.cortex.2026.08.001
Data Access Statement: This study is based on the BIL&GIN dataset, which is accessible through collaborative research agreements designed to foster scientific cooperation. Details on data access policies can be found in Mazoyer et al. (2016). While the dataset itself is not publicly available, all analysis scripts used in this study are openly accessible on GitHub at https://github.com/andrulyte/SF-Coupling
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