Mapping white-matter functional organization at rest and during naturalistic visual perception

Area of Science:

• Neuroimaging
• White Matter Neuroscience

Background:

• Functional magnetic resonance imaging (fMRI) is widely used for cortical gray matter analysis.
• Its application to white matter (WM) functions remains underexplored, often treating WM signals as noise.

Purpose of the Study:

• To investigate the spatiotemporal characteristics of fMRI data within human white matter.
• To explore WM functional information at rest and during a visual task.

Main Methods:

• Acquired fMRI data from human participants at rest and during naturalistic movie viewing.
• Applied independent component analysis (ICA) and hierarchical clustering to resting-state fMRI data.
• Analyzed and compared WM component reorganization and temporal coherence during rest versus visual tasks.

Main Results:

• De-noised resting-state WM fMRI data into independent components, organized into fiber bundles.
• Observed partial reorganization of WM components during natural vision.
• Found increased temporal coherence in optic radiations and correlations with visual networks during visual tasks.

Conclusions:

• fMRI data contain rich functional information about white matter activity and connectivity.
• Challenges the conventional view of white matter signals as mere artifacts.
• Suggests fMRI is a valuable tool for studying white matter in both resting and active states.