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Spectral mapping of brain functional connectivity from diffusion imaging
Cassiano O Becker1, Sérgio Pequito2, George J Pappas1
1Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, USA.
Scientific Reports
|January 25, 2018
Summary
This study introduces a new method to map brain functional connectivity from structural brain graphs. The findings reveal how brain anatomy constrains neural dynamics and cognitive system activity.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Brain Imaging
Background:
- Understanding the brain's structure-function relationship is key in neuroscience.
- Neuroimaging reveals brain anatomy (structural graphs) and activity (functional graphs).
- Current models show a weak link between brain structure and function, with unclear constraints.
Purpose of the Study:
- To develop a methodology linking structural brain graphs to functional connectivity.
- To systematically investigate how anatomical structure constrains neural dynamics.
- To explore the relationship between mapped functional connectivity and cognitive systems.
Main Methods:
- Constructing structural graphs from diffusion tensor imaging data.
- Developing a methodology to map functional connectivity from structural graphs.
- Analyzing the role of structural walks in functional correlation formation.
- Examining eigenmodes of mapped functional connectivity.
Main Results:
- A novel methodology successfully maps functional connectivity from structural graphs.
- The approach systematically accounts for structural walks influencing functional correlations.
- Eigenmodes of the mapped functional connectivity correlate with distinct cognitive system activity patterns.
Conclusions:
- The study provides a framework for understanding how brain anatomy constrains neural dynamics.
- This methodology offers insights into the weak but present structure-function relationship.
- Findings suggest a link between structural constraints, functional connectivity, and cognitive processes.
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