Fractal analysis of brain shape formation predicts age and genetic similarity in human newborns

Abstract The neonatal period represents a critical phase of human brain development. During this time, the brain shows a dramatic increase in size, but how its morphology emerges in early life remains largely unknown. Here we show that human newborns undergo a rapid formation of brain shape, beyond the expected growth in brain size. Using fractal dimensionality (FD) analysis of structural neuroimaging data, we show that brain shape strongly reflects infant maturity beyond differences in brain size, significantly outperforms brain size in predicting infant age at scan (mean error approximately 4 days), detects signatures of premature birth that are not captured by brain size, is systematically more sensitive to genetic variability among infants and is superior in predicting which newborns are twin siblings, with up to 97% accuracy. Additionally, FD captures age and genetic information significantly better than earlier morphological measures, including cortical thickness, curvature, gyrification, sulcation, surface area and the T1-weighted/T2-weighted ratio. These findings identify the formation of brain shape as a fundamental maturational process in human brain development and show that, biologically, FD should be interpreted as a developmental marker of early-life brain maturity, which is rooted in geometry rather than size.