Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Clinical Neurology

Background:

• Language function is critical for human uniqueness.
• Preserving language function during brain surgery is a significant challenge.
• Task-based fMRI is the standard for language lateralization but can be difficult for some patients.

Purpose of the Study:

• To evaluate resting-state fMRI's efficacy in lateralizing language function in healthy individuals.
• To establish resting-state fMRI as a viable alternative for patients unable to perform task-based fMRI.

Main Methods:

• Eighteen healthy right-handed volunteers underwent both resting-state and task-based fMRI.
• Language networks were assessed using seed-based connectivity and fractional amplitude of low-frequency fluctuation (fALFF).
• Laterality indices from task-based fMRI were correlated with resting-state fMRI parameters.

Main Results:

• A strong positive correlation (r=0.849, P<0.05) was found between fALFF and the language laterality index.
• Regression analysis showed fALFF explained 72.1% of the variance in task-based fMRI laterality.
• Resting-state fMRI connectivity maps accurately reflected language networks in both hemispheres.

Conclusions:

• Fractional amplitude of low-frequency fluctuation (fALFF) is a reliable indicator of language laterality.
• Resting-state fMRI with fALFF serves as an effective alternative to task-based fMRI.
• This approach enhances the assessment of language function, particularly for non-cooperative patients.