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A normative reference for large-scale human brain dynamics across the lifespan

Yang, Y.; Sharma, N.; Dai, S.; Mallus, F.; Su, G.; Kand, A.; Zabihi, M.; Alnaes, D.; Buitelaar, J. K.; Croy, I.; Dinga, R.; Durstewitz, D.; Fallgatter, A. J.; Gaser, C.; Greven, C.; Mostafa Kia, S.; Kim, M.; Klein, M.; Korbmacher, M.; Kruger, J.; Kumar Jangir, V.; Leonardsen, E.; Moberget, T.; Van Roij, D.; Vidal-Pineiro, D.; Walter, M.; Wang, Y.; Westlye, L. T.; Franke, B.; Rutherford, S.; Wolfers, T.

2026-03-06 neuroscience
10.64898/2026.03.06.710057 bioRxiv
Show abstract

Human brain function emerges from dynamic reconfigurations of large-scale neural networks. While population-level reference charts have transformed the study of static brain structure and connectivity, an equivalent normative framework for intrinsic brain dynamics has been lacking. This gap has limited our ability to characterize individual variability, development, ageing, and mental health conditions at scale. Here, we establish a population-level normative reference for large-scale human brain dynamics using resting-state fMRI data from more than 10,000 individuals spanning the lifespan and 91 scanning sites. We derive a compact set of recurring brain-state configurations that are reproducible across scanners and acquisition paradigms and that generalize to previously unseen cohorts. Anchoring these dynamic states to normative lifespan models enables the quantification of individual deviations relative to population reference distributions. We show that intrinsic brain dynamics undergo systematic reorganization across development and ageing, with pronounced changes before early adulthood and more gradual modulation thereafter. Applying this framework across multiple mental health conditions reveals disorder-specific and highly heterogeneous deviations in brain dynamics that are not captured by static neuroimaging measures. Robust transfer to independent cohorts and longitudinal analyses demonstrate that normative brain dynamics can be reliably assessed out of distribution. These results delineate a population-scale dynamic architecture of the human brain and extend normative brain mapping from static phenotypes to the temporal domain, providing a reference framework for studying brain function across the lifespan in health and disease.

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