Brain charts for the human lifespan.
Bethlehem RAI., Seidlitz J., White SR., Vogel JW., Anderson KM., Adamson C., Adler S., Alexopoulos GS., Anagnostou E., Areces-Gonzalez A., Astle DE., Auyeung B., Ayub M., Bae J., Ball G., Baron-Cohen S., Beare R., Bedford SA., Benegal V., Beyer F., Blangero J., Blesa Cábez M., Boardman JP., Borzage M., Bosch-Bayard JF., Bourke N., Calhoun VD., Chakravarty MM., Chen C., Chertavian C., Chetelat G., Chong YS., Cole JH., Corvin A., Costantino M., Courchesne E., Crivello F., Cropley VL., Crosbie J., Crossley N., Delarue M., Delorme R., Desrivieres S., Devenyi GA., Di Biase MA., Dolan R., Donald KA., Donohoe G., Dunlop K., Edwards AD., Elison JT., Ellis CT., Elman JA., Eyler L., Fair DA., Feczko E., Fletcher PC., Fonagy P., Franz CE., Galan-Garcia L., Gholipour A., Giedd J., Gilmore JH., Glahn DC., Goodyer IM., Grant PE., Groenewold NA., Gunning FM., Gur RE., Gur RC., Hammill CF., Hansson O., Hedden T., Heinz A., Henson RN., Heuer K., Hoare J., Holla B., Holmes AJ., Holt R., Huang H., Im K., Ipser J., Jack CR., Jackowski AP., Jia T., Johnson KA., Jones PB., Jones DT., Kahn RS., Karlsson H., Karlsson L., Kawashima R., Kelley EA., Kern S., Kim KW., Kitzbichler MG., Kremen WS., Lalonde F., Landeau B., Lee S., Lerch J., Lewis JD., Li J., Liao W., Liston C., Lombardo MV., Lv J., Lynch C., Mallard TT., Marcelis M., Markello RD., Mathias SR., Mazoyer B., McGuire P., Meaney MJ., Mechelli A., Medic N., Misic B., Morgan SE., Mothersill D., Nigg J., Ong MQW., Ortinau C., Ossenkoppele R., Ouyang M., Palaniyappan L., Paly L., Pan PM., Pantelis C., Park MM., Paus T., Pausova Z., Paz-Linares D., Pichet Binette A., Pierce K., Qian X., Qiu J., Qiu A., Raznahan A., Rittman T., Rodrigue A., Rollins CK., Romero-Garcia R., Ronan L., Rosenberg MD., Rowitch DH., Salum GA., Satterthwaite TD., Schaare HL., Schachar RJ., Schultz AP., Schumann G., Schöll M., Sharp D., Shinohara RT., Skoog I., Smyser CD., Sperling RA., Stein DJ., Stolicyn A., Suckling J., Sullivan G., Taki Y., Thyreau B., Toro R., Traut N., Tsvetanov KA., Turk-Browne NB., Tuulari JJ., Tzourio C., Vachon-Presseau É., Valdes-Sosa MJ., Valdes-Sosa PA., Valk SL., van Amelsvoort T., Vandekar SN., Vasung L., Victoria LW., Villeneuve S., Villringer A., Vértes PE., Wagstyl K., Wang YS., Warfield SK., Warrier V., Westman E., Westwater ML., Whalley HC., Witte AV., Yang N., Yeo B., Yun H., Zalesky A., Zar HJ., Zettergren A., Zhou JH., Ziauddeen H., Zugman A., Zuo XN., 3R-BRAIN None., AIBL None., Alzheimer’s Disease Neuroimaging Initiative None., Alzheimer’s Disease Repository Without Borders Investigators None., CALM Team None., Cam-CAN None., CCNP None., COBRE None., cVEDA None., ENIGMA Developmental Brain Age Working Group None., Developing Human Connectome Project None., FinnBrain None., Harvard Aging Brain Study None., IMAGEN None., KNE96 None., Mayo Clinic Study of Aging None., NSPN None., POND None., PREVENT-AD Research Group None., VETSA None., Bullmore ET., Alexander-Bloch AF.
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.