fMRIPrep Lifespan: Extending A Robust Pipeline for Functional MRI Preprocessing to Developmental Neuroimaging

Area of Science:

• Neuroimaging
• Developmental Neuroscience
• Computational Neuroscience

Background:

• Standardized preprocessing workflows are crucial for neuroimaging research reproducibility and data sharing.
• Existing tools like fMRIPrep are limited in processing early-life MRI data, hindering lifespan studies.
• Bridging this gap is essential for understanding brain development and aging.

Purpose of the Study:

• Introduce fMRIPrep Lifespan, an extension of fMRIPrep for comprehensive, lifespan neuroimaging data preprocessing.
• Enable standardized processing of neonatal, infant, and toddler structural and functional MRI data.
• Enhance the NiPreps suite for broader applicability across the entire human lifespan.

Main Methods:

• Integrated NiBabies workflow for early-life MRI data with upstream NiPreps enhancements.
• Incorporated multi-echo data processing and modularized workflow components.
• Ensured processing convergence with established pipelines like ABCD-BIDS and HCP Pipelines.

Main Results:

• Demonstrated high-quality preprocessing outputs for fMRIPrep Lifespan using Baby Connectome Project data (ages 1-43 months).
• Validated the tool's effectiveness across a wide developmental age range.
• Confirmed the production of robust and reproducible functional MRI data.

Conclusions:

• fMRIPrep Lifespan successfully extends standardized MRI preprocessing from infancy to senescence.
• The tool's scalable and modular design ensures adaptability for future lifespan neuroimaging research.
• fMRIPrep Lifespan provides a robust framework for reproducible functional MRI studies across all ages.