Dynamic Fingerprinting of the Human Functional Connectome

Area of Science:

• Neuroscience
• Brain Imaging
• Network Science

Background:

• Resting-state functional connectivity (FC) exhibits personalized patterns, acting as a unique brain fingerprint.
• The brain is a dynamic system with varying FC maps across metastable states, unlike static approaches.

Purpose of the Study:

• To investigate dynamic FC for improved individual brain identification.
• To explore the utility of state-specific FC in predicting cognitive scores.

Main Methods:

• Derived state-specific functional connectivity (FC) maps using sliding window correlation and clustering.
• Evaluated the performance of dynamic FC fingerprints against static methods for individual identification and cognitive prediction.

Main Results:

• Dynamic brain fingerprints demonstrated superior identification accuracy compared to static fingerprints.
• Certain brain states showed higher accuracy in predicting cognitive scores, suggesting their informativeness.

Conclusions:

• Dynamic FC information captures subject-specific connectivity features missed by static FC alone.
• Specific brain states identified through dynamic analysis show potential as biomarkers for cognitive abilities and brain disorders.