Tangent functional connectomes uncover more unique phenotypic traits.

Area of Science:

• Neuroscience
• Brain Imaging Analysis
• Computational Psychiatry

Background:

• Functional connectomes (FCs) represent brain functional couplings using correlation matrices.
• Tangent-FCs, derived from FCs via tangent space projection, show promise as superior biomarkers for predicting brain conditions and aging.

Purpose of the Study:

• To investigate if tangent-FCs exhibit a higher individual "fingerprint" compared to traditional FCs.
• To explore the impact of six factors on tangent-FC fingerprinting: fMRI condition, scan length, parcellation granularity, reference matrix, main-diagonal regularization, and distance metric.

Main Methods:

• Functional connectomes were transformed into tangent-FCs using tangent space projections.
• The 'fingerprint gradient' was assessed using test-retest data, monozygotic twins, and dizygotic twins.
• Six factors influencing tangent-FCs were systematically evaluated to optimize identification rates.

Main Results:

• Identification rates were consistently higher for tangent-FCs across all tested 'fingerprint gradient' conditions.
• Optimal identification was achieved with minimal (0.01) regularization, Riemann reference matrix, and correlation distance.
• The optimized tangent-FC approach was successfully validated on a separate resting-state fMRI dataset.

Conclusions:

• Tangent-FCs possess a stronger individual fingerprint than conventional FCs, enhancing their utility as biomarkers.
• Specific configurations of regularization, reference matrix, and distance metric optimize tangent-FC fingerprinting.
• This refined method offers improved potential for individual brain identification and clinical applications.