Commonality and Variability in Functional Networks In Young Children Under 5 Years Old

Functional brain networks exhibit striking individual variability in adults, while less is known about the functional network variability in young children under 5 years. Conventional group-average approaches to obtain the group-level network may have obscured some fine developmental details. We combined data-driven template creation at a coarse parcel level and template-matching at a fine vertex level to map individualized functional networks from single fMRI scans in children aged 8-60 months in two datasets, revealing four key insights: (1) Individual-specific networks show moderate stability across longitudinal scans (Normalized Mutual Information ∼ 0.52 with ∼ 20 minutes of low-motion data) despite developmental changes; (2) Across the population, sensory cortices demonstrate higher consistency in network assignment than association cortices; (3) Network lateralization in the language network increases with age and correlates with age-normalized verbal developmental quotient (r ∼ 0.17), suggesting a correspondence between the individual functional topography and the emergence of functional specialization; and (4) Our 23-network solution identifies finer subdivisions than previously reported using group-average approaches, with many networks resembling the subdivisions found in adult fMRI data. Our findings revealed neurodevelopmental variations in functional network topography that are reliable within individuals and behaviorally relevant, opening new avenues for investigating how person-specific network architecture supports emerging cognitive abilities.