NeoRS

NeoRS processes neonatal resting-state fMRI (rsfMRI) data to provide preprocessing and functional connectivity analyses tailored to neonatal brain anatomy and myelination-dependent contrast.

Key Features:

• Adaptation to Neonatal Brain Characteristics: Accommodates reversed myelination-dependent contrast, non-collaborative neonatal behavior, and variations in brain size during rsfMRI processing.
• Image Registration: Performs registration using a neonatal-specific atlas that accounts for brain size and contrast differences.
• Skull Stripping and Tissue Segmentation: Executes skull stripping and tissue segmentation to isolate brain tissue from non-brain elements.
• Slice Timing and Head Motion Correction: Applies slice timing correction and head motion correction with emphasis on managing neonatal motion artifacts.
• Regression of Confounds: Regresses confounding signals to improve functional data quality.
• Quality Control: Incorporates visual assessment checkpoints to verify integrity and reliability of processed data.
• Functional Connectivity Analysis: Computes seed-to-seed and seed-to-voxel correlation analyses for networks including language, default mode, dorsal attention, visual, ventral attention, motor, and fronto-parietal networks.
• Compatibility and Dataset Applicability: Supports multi-band and single-band acquisitions and is applicable to smaller datasets.
• Performance Evaluation: Validated on 10 neonates from the Baby Connectome Project with processed networks consistent with published neonatal studies.
• Technical Implementation: Implemented in Matlab with support for parallel computing.

Scientific Applications:

• Intrinsic Functional Connectivity Studies: Enables examination of intrinsic brain functional connectivity in neonates using rsfMRI.
• Neonatal Cerebral Development: Supports investigation of cerebral development and network maturation in early life stages.
• Developmental Disorder Research: Facilitates exploration of network interactions relevant to potential developmental disorders in neonates.

Methodology:

Computational steps include neonatal-specific atlas registration, skull stripping, tissue segmentation, slice timing and head motion correction, regression of confounds, and seed-to-seed and seed-to-voxel functional connectivity analyses; implemented in Matlab with parallel computing.