BOLD signal and vessel dynamics: a hierarchical cluster analysis

Area of Science:

• Neuroimaging
• Physiology
• Vascular Biology

Background:

• Functional magnetic resonance imaging (fMRI) measures brain activity by detecting changes in blood oxygenation.
• Assessing cerebral vascular dynamics is crucial for understanding brain function and disease.
• Apnea-based tasks can induce measurable physiological changes in the brain.

Purpose of the Study:

• To evaluate the capability of fMRI in estimating cerebral vascular dynamic effects.
• To analyze blood oxygenation level-dependent (BOLD) signal variations during an inspiratory apnea (IA) task.
• To map spatial and temporal brain responses to apnea using fMRI.

Main Methods:

• Healthy subjects performed an inspiratory apnea (IA) task during fMRI scanning.
• Blood oxygenation level-dependent (BOLD) contrast was measured.
• Hierarchical cluster analysis was applied to fMRI time courses, focusing on signal variations in gray and white matter voxels near large venous vessels.
• Root mean square and absolute variation differences were calculated.

Main Results:

• Significant BOLD signal variations were observed in specific brain voxels during the IA task and recovery.
• Results were presented as spatio-temporal maps of time series variations using hierarchical clustering.
• Clustering of signal response delay identified specific brain sites affected by the apnea task.

Conclusions:

• fMRI is capable of detecting and mapping cerebral vascular dynamic effects induced by tasks like inspiratory apnea.
• The study successfully identified brain regions, including white and gray matter, responsive to apnea-induced vascular changes.
• This approach provides a method for partitioning and identifying specific brain sites based on their vascular response dynamics.