Feasibility of Precision Functional Mapping in Youth Multi-Echo fMRI Data

Area of Science:

• Neuroscience
• Developmental Psychology
• Medical Imaging

Background:

• Adolescent brain development is crucial for understanding cognition, personality, and psychopathology.
• Precision Functional Mapping (PFM) is a promising MRI technique for mapping individualized brain networks.
• Understanding PFM's performance in adolescents and with multi-echo fMRI is essential.

Purpose of the Study:

• To evaluate the efficacy of Precision Functional Mapping (PFM) in an adolescent population using multi-echo fMRI.
• To assess the reliability and stability of brain networks derived from PFM in youth.
• To compare different network detection algorithms and task-based network utility.

Main Methods:

• Applied PFM to 80 minutes of combined resting-state and task-based multi-echo fMRI data from eight adolescents (ages 10-17).
• Utilized multivariate similarity and Intraclass Correlation Coefficient (ICC) to assess functional connectivity reliability.
• Employed Infomap and a Bayesian algorithm (MS-HBM) for network stability analysis.

Main Results:

• PFM generated highly modular adolescent brain networks, consistent with adult templates.
• Functional connectivity reliability stabilized early (10-15 minutes) but improved with more data.
• The Bayesian algorithm (MS-HBM) showed higher stability than Infomap; sensory networks exhibited greatest stability.
• Individualized mapping uniquely benefited the auditory network for task-based responses.

Conclusions:

• PFM is effective for characterizing adolescent sensory and perceptual brain networks within constrained scanning times.
• Early stabilization of functional connectivity suggests efficient mapping in youth.
• Further validation is needed to bridge individual case studies and large-scale developmental research.