Exploring the Relationship Between White Matter Tracts and Resting-State Functional Language Lateralization Index

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Neuroanatomy

Background:

• Resting-state fMRI (rs-fMRI) assesses language networks and lateralization with minimal bias.
• Diffusion MRI (dMRI) tractography complements rs-fMRI by mapping language-associated white matter pathways.
• Understanding the relationship between white matter structure and functional language lateralization is crucial for cognitive neuroscience.

Purpose of the Study:

• To identify structural white matter predictors of language lateralization index (LI) using tractography.
• To investigate the relationship between micro- and macro-structural white matter measures and functional LI.
• To determine if structural measures can serve as proxies for functional language lateralization.

Main Methods:

• Utilized rs-fMRI and dMRI data from 618 healthy Human Connectome Project participants.
• Employed linear regression and random forest models to analyze tractography data.
• Examined structural measures of arcuate fasciculi, inferior longitudinal fasciculi, frontal aslant tracts, and corpus callosum sections.

Main Results:

• Suggested a potential association between white matter micro- and macro-structural measures and resting-state functional language lateralization.
• Identified structural predictors were not sufficiently representative to act as proxies for functional LI.
• Both hemispheres and various white matter tracts showed potential relevance.

Conclusions:

• While white matter structure and functional lateralization are related, structural measures alone are insufficient predictors.
• Both micro- and macro-structural characteristics, across both hemispheres, are important considerations.
• Further research is needed to fully elucidate the complex relationship between brain structure and language lateralization.