Mapping Individualized Developmental Imbalance in Youth and Its Association with Psychopathology.

The emergence of psychiatric symptoms during adolescence is increasingly hypothesized as arising from maturational imbalance across brain systems. However, this concept largely lacks quantitative grounding, which requires measuring fine-grained imbalance patterns that accurately capture acceleration or delay relative to normative developmental trajectories of brain regions. To address this gap, we leverage predictive normative modeling to learn models that predict chronological age from regional multivariate functional connectivity patterns. We demonstrate that these region-specific models are highly generalizable across independent cohorts and capture greater developmental effects than traditional functional connectivity metrics. From these models, we then derive a region-wise Relative Maturity (RM) index that quantifies individualized, region-specific deviations from normative development. Rigorous cross-cohort and longitudinal evaluations across four datasets show that RM maps are reproducible, subject-specific fingerprints of neurodevelopmental imbalance. These fingerprints are organized along continuous, low-dimensional axes aligned with intrinsic functional gradients and can predict dimensions of psychopathological vulnerability. Together, our findings establish RM as a robust, sensitive, and generalizable framework for quantifying individual vulnerability to psychopathology through system-level patterns of developmental imbalance.