Developmental tuning of functional manifold dimensionality across the human brain

Neural representations vary in their complexity across brain regions and tasks. How this variation emerges over human development remains poorly understood. We estimated intrinsic dimensionality in five naturalistic fMRI datasets ( $N=781$ unique participants, aged 3 months to 53 years) with T-PHATE - a nonlinear manifold learning method robust to noisy, autocorrelated signals. In adults, brain regions relevant to a task had higher-dimensional activity than task-irrelevant regions across auditory, visual, and audiovisual stimuli. The modulation of representational complexity by tasks was absent in infants, emerged in early childhood, and strengthened logarithmically through adolescence. It reflected a selective collapse in dimensionality in task-irrelevant regions, relative to a resting-state baseline, rather than an expansion of dimensionality in task-relevant regions. Such compression followed a trajectory from global and nonselective in infants to local and precise by adulthood. These results identify selective compression as a developmental engine of functional specialization: rather than adding complexity where it is needed, the brain dynamically pares it away where it is not.