Macroscale coupling between structural and effective connectivity in the mouse brain.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Understanding the relationship between structural connectivity (SC) and functional connectivity (FC) in the brain is a fundamental challenge in neuroscience.
• Existing research often reveals a lack of one-to-one correspondence between anatomical structure and observed brain activity patterns.

Approach:

• This study utilized a directed structural connectome of the mouse brain derived from viral tracer data.
• Effective connectivity (EC) matrices were computed from whole-brain resting-state fMRI data using a novel dynamic causal modeling (DCM) approach.
• The coupling between SC and EC was analyzed by conditioning on the strongest links in both connectomes.

Key Points:

• When focusing on the strongest effective connectivity (EC) links, the observed coupling aligns with the established unimodal-transmodal functional hierarchy.
• Conversely, strong structural connectivity (SC) links within high-order cortical areas do not necessarily correspond to strong EC.
• Significant mismatches between SC and EC are evident across different brain networks, with sensory-motor networks showing the best alignment.

Conclusions:

• The findings highlight that the relationship between brain structure and function is not straightforward and is influenced by network properties and analytical approaches.
• The study underscores the importance of considering directed structural information and the limitations of functional connectivity measures for a comprehensive understanding of brain network organization.