Unique local gradient-based functional fingerprints enable precisely identifying individual infants over ages.

Brain functional connectivity (FC) exhibits individualized patterns that can serve as reliable "fingerprints" for identifying individual adults. However, the rapid and complex development of the infant brain poses significant challenges in establishing individualized, developmentally-robust functional fingerprints during infancy. In this study, we introduce a novel approach that captures fine-grained local gradients of FC derived from functional MRI, enabling precise characterization of unique subject-specific FC patterns. Our method achieved approximately 99% individual identification accuracy across longitudinal scans spanning infancy in 103 infants, substantially outperforming conventional connectome-based fingerprinting, which achieved approximately 70% accuracy. Importantly, these local gradient-based functional fingerprints, predominantly localized within association and sensory networks, were also modestly but significantly associated with infant cognitive performance. Together, these findings support the existence of individualized functional fingerprints that are stable across dynamic early brain development, offering new insights into the early development of functional individuality and its cognitive relevance.