Brain charts for the human lifespan

Abstract

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Attention network drives cortical maturation linked to childhood cognition

“…Evidence for the scheduled timing of these neurodevelopmental events has emerged across biological scales, from regional profiles of cellular maturation 4 , synapse formation and dendritic pruning 5 , and intracortical myelination 6 through macro-scale morphological features including folding patterns 7 and associated areal expansion 8 . These processes are imbedded within age dependent anatomical changes across lifespan 9 , particularly the prolonged development of association cortex territories. In parallel, substantial progress has been made characterizing the organization 10,11 and spatiotemporal maturation of large-scale functional systems across cortex 12,13 .…”

Multisite Test-Retest Reliability and Compatibility of Brain Metrics derived from FreeSurfer Versions 7.1, 6.0, and 5.3

“…Subcortical volumes are also another set of metrics derived from FreeSurfer that are of major interest to neuroimaging researchers (Satizabal et al, 2019, Ohi et al, 2020). Efforts to provide references of normative subcortical volume changes that occur as a result of aging have been put forth (Potvin et al, 2016, Coupé et al, 2017, Narvacan et al, 2017, Dima et al, 2022, Miletić et al, 2022, Bethlehem et al, 2022). For example, Potvin et al, 2016 pooled data from 21 research groups (n=2790) and segmented subcortical volumes using FreeSurfer v5.3 to provide norms of volumetric estimate changes during healthy aging.…”

The Developing Human Connectome Project Neonatal Data Release

“…Human brain development accelerates rapidly in late pregnancy to reach maximum global growth rate before 6 months ( Bethlehem et al, 2022 ). This rapid growth is accompanied by equally dramatic changes in the brain’s associated architecture of structural and functional connectivity, and therefore understanding these processes in both the healthy and pathological brain can provide marked new insights into fundamental neural processes and the possible changes that underlie intractable neuropsychiatric conditions.…”