Structural connectome fingerprinting and age prediction in pediatric development: assessing voxel- and surface-based white matter connectivity

Abstract

Mapping structural white matter connectivity is a challenge, with many barriers to accurate representation. Here, we assessed the replicability and reliability of two connectome-generating methods, voxel- or surface-based, using test-retest analyses, fingerprinting and age prediction. The two connectomic methods are initiated by the same state-of-the-art dMRI processing pipeline before diverging at the tractography and connectome-generating steps using either voxels or surfaces. While both methods performed very well across all analyses, voxel-based connectomes performed marginally better than surface-based connectomes. Notably, structural connectomes derived from either method demonstrate reliably accurate representations of both individuals and their chronological age, comparable to similar analyses employing multi-modal features. The difference in methodological performance could be attributed to a number of method-specific features but ultimately show that cutting-edge tractography with robust dMRI processing produces reliable white matter connectivity measures.