Lagged and instantaneous dynamical influences related to brain structural connectivity

Area of Science:

• Neuroscience
• Medical Imaging
• Computational Neuroscience

Background:

• Neuroimaging methods like MRI reveal brain networks at macroscale.
• Diffusion-weighted MRI (dMRI) shows structural connectivity (SC), while functional MRI (fMRI) shows functional connectivity (FC).
• The relationship between brain structure (SC) and function (FC) remains a key neuroscience challenge.

Purpose of the Study:

• To investigate the relationship between structural connectivity (SC) and functional connectivity (FC) using different analytical methods.
• To compare the efficacy of various functional connectivity measures in reflecting underlying brain structure.
• To explore the role of directionality and time scales in functional-structural brain relationships.

Main Methods:

• Acquired resting-state fMRI and dMRI data.
• Constructed SC matrices based on fiber counts between brain areas.
• Calculated FC matrices using exploratory structural equation modeling (eSEM), linear correlations (C), and partial correlations (PC).
• Analyzed lagged correlations using a lagged eSEM and Granger causality (GC).

Main Results:

• eSEM showed comparable SC correlation to C and PC but uniquely provided directional information.
• Instantaneous connectivity methods demonstrated a stronger relationship with SC than lagged methods (GC, lagged eSEM).
• Slow directed influences captured by lagged analysis were less related to SC compared to instantaneous interactions.

Conclusions:

• Instantaneous functional connectivity measures are more closely aligned with structural brain connectivity than lagged measures.
• eSEM offers valuable directional insights into functional brain interactions, complementing structural data.
• Understanding the interplay between SC and FC is crucial for brain physiology and function studies.