ENIGMA datasets

  • Sun, D., Ching, C. R., Lin, A., Forsyth, J. K., Kushan, L., Vajdi, A., … & Jonas, R. K. (2018). Large-scale mapping of cortical alterations in 22q11. 2 deletion syndrome: convergence with idiopathic psychosis and effects of deletion size. Molecular psychiatry, 1-13.
  • Boedhoe, P. S., Van Rooij, D., Hoogman, M., Twisk, J. W., Schmaal, L., Abe, Y., … & Arango, C. (2020). Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD working groups. American Journal of Psychiatry, 177(9), 834-843.
  • Van Rooij, D., Anagnostou, E., Arango, C., Auzias, G., Behrmann, M., Busatto, G. F., … & Dinstein, I. (2018). Cortical and subcortical brain morphometry differences between patients with autism spectrum disorder and healthy individuals across the lifespan: results from the ENIGMA ASD Working Group. American Journal of Psychiatry, 175(4), 359-369.
  • Hibar, D. P., Westlye, L. T., Doan, N. T., Jahanshad, N., Cheung, J. W., Ching, C. R., … & Krämer, B. (2018). Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group. Molecular psychiatry, 23(4), 932-942.
  • Whelan, C. D., Altmann, A., Botía, J. A., Jahanshad, N., Hibar, D. P., Absil, J., … & Bergo, F. P. (2018). Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study. Brain, 141(2), 391-408.
  • Schmaal, L., Hibar, D. P., Sämann, P. G., Hall, G. B., Baune, B. T., Jahanshad, N., … & Vernooij, M. W. (2017). Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Molecular psychiatry, 22(6), 900-909.
  • Schmaal, L., Veltman, D. J., van Erp, T. G., Sämann, P. G., Frodl, T., Jahanshad, N., … & Vernooij, M. W. (2016). Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Molecular psychiatry, 21(6), 806-812.
  • Boedhoe, P. S., Schmaal, L., Abe, Y., Alonso, P., Ameis, S. H., Anticevic, A., … & Bollettini, I. (2018). Cortical abnormalities associated with pediatric and adult obsessive-compulsive disorder: findings from the ENIGMA Obsessive-Compulsive Disorder Working Group. American Journal of Psychiatry, 175(5), 453-462.
  • Van Erp, T. G., Walton, E., Hibar, D. P., Schmaal, L., Jiang, W., Glahn, D. C., … & Okada, N. (2018). Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biological psychiatry, 84(9), 644-654.
  • van Erp, T. G., Hibar, D. P., Rasmussen, J. M., Glahn, D. C., Pearlson, G. D., Andreassen, O. A., … & Melle, I. (2016). Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Molecular psychiatry, 21(4), 547-553.

Connectivity data

  • Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E., Yacoub, E., Ugurbil, K., & Wu-Minn HCP Consortium. (2013). The WU-Minn human connectome project: an overview. Neuroimage, 80, 62-79.
  • Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., … & Van Essen, D. C. (2013). The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage, 80, 105-124.

Gene co-expression data

  • Arnatkevic̆iūtė, A., Fulcher, B. D., & Fornito, A. (2019). A practical guide to linking brain-wide gene expression and neuroimaging data. Neuroimage, 189, 353-367.
  • Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., … & Abajian, C. (2012). An anatomically comprehensive atlas of the adult human brain transcriptome. Nature, 489(7416), 391-399.
  • Markello, Ross, Shafiei, Golia, Zheng, Ying-Qiu, Mišić, Bratislav. abagen: A toolbox for the Allen Brain Atlas genetics data. Zenodo; 2020. Available from:


  • Demontis, D., Walters, R. K., Martin, J., Mattheisen, M., Als, T. D., Agerbo, E., … & Cerrato, F. (2019). Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nature genetics, 51(1), 63-75.
  • Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., … & Awashti, S. (2019). Identification of common genetic risk variants for autism spectrum disorder. Nature genetics, 51(3), 431-444.
  • Stahl, E. A., Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., Trubetskoy, V., … & de Leeuw, C. A. (2019). Genome-wide association study identifies 30 loci associated with bipolar disorder. Nature genetics, 51(5), 793-803.
  • Howard, D. M., Adams, M. J., Clarke, T. K., Hafferty, J. D., Gibson, J., Shirali, M., … & Alloza, C. (2019). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature neuroscience, 22(3), 343-352.
  • Consortium, T. I. L. A. E. (2018). Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies. Nature communications, 9.
  • Pardiñas, A. F., Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., … & Han, J. (2018). Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nature genetics, 50(3), 381-389.
  • Yu, D., Sul, J. H., Tsetsos, F., Nawaz, M. S., Huang, A. Y., Zelaya, I., … & Greenberg, E. (2019). Interrogating the genetic determinants of Tourette’s syndrome and other tic disorders through genome-wide association studies. American Journal of Psychiatry, 176(3), 217-227.


  • Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M. É., … & Shah, N. J. (2013). BigBrain: an ultrahigh-resolution 3D human brain model. Science, 340(6139), 1472-1475.
  • vPapoulis, A., & Pillai, S. U. (2002). Probability, random variables, and stochastic processes. Tata McGraw-Hill Education.
  • Paquola, C., De Wael, R. V., Wagstyl, K., Bethlehem, R. A., Hong, S. J., Seidlitz, J., … & Smallwood, J. (2019). Microstructural and functional gradients are increasingly dissociated in transmodal cortices. PLoS biology, 17(5), e3000284.

von Economo and Koskinas atlas

  • von Economo, C. F., & Koskinas, G. N. (1925). Die cytoarchitektonik der hirnrinde des erwachsenen menschen. J. Springer.
  • Scholtens, L. H., de Reus, M. A., de Lange, S. C., Schmidt, R., & van den Heuvel, M. P. (2018). An mri von economo–koskinas atlas. NeuroImage, 170, 249-256.
  • Triarhou, L. C. (2007). The Economo-Koskinas atlas revisited: cytoarchitectonics and functional context. Stereotactic and functional neurosurgery, 85(5), 195-203.

Network-based atrophy models (hubs)

  • Fornito, A., Zalesky, A., & Breakspear, M. (2015). The connectomics of brain disorders. Nature Reviews Neuroscience, 16(3), 159-172.
  • van den Heuvel, M. P., & Sporns, O. (2013). Network hubs in the human brain. Trends in cognitive sciences, 17(12), 683-696.
  • Crossley, N. A., Mechelli, A., Scott, J., Carletti, F., Fox, P. T., McGuire, P., & Bullmore, E. T. (2014). The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain, 137(8), 2382-2395.

Network-based atrophy models (disease epicenters)

  • Larivière, S., Rodríguez-Cruces, R., Royer, J., Caligiuri, M. E., Gambardella, A., Concha, L., … & Gleichgerrcht, E. (2020). Network-based atrophy modeling in the common epilepsies: a worldwide ENIGMA study. Science Advances, 6.
  • Shafiei, G., Markello, R. D., Makowski, C., Talpalaru, A., Kirschner, M., Devenyi, G. A., … & Chakravarty, M. M. (2020). Spatial patterning of tissue volume loss in schizophrenia reflects brain network architecture. Biological psychiatry, 87(8), 727-735.
  • Zeighami, Y., Ulla, M., Iturria-Medina, Y., Dadar, M., Zhang, Y., Larcher, K. M. H., … & Dagher, A. (2015). Network structure of brain atrophy in de novo Parkinson’s disease. Elife, 4, e08440.
  • Brown, J. A., Deng, J., Neuhaus, J., Sible, I. J., Sias, A. C., Lee, S. E., … & Grinberg, L. T. (2019). Patient-tailored, connectivity-based forecasts of spreading brain atrophy. Neuron, 104(5), 856-868.

Spin permutations

  • Alexander-Bloch, A. F., Shou, H., Liu, S., Satterthwaite, T. D., Glahn, D. C., Shinohara, R. T., … & Raznahan, A. (2018). On testing for spatial correspondence between maps of human brain structure and function. Neuroimage, 178, 540-551.
  • Váša, F., Seidlitz, J., Romero-Garcia, R., Whitaker, K. J., Rosenthal, G., Vértes, P. E., … & Jones, P. B. (2018). Adolescent tuning of association cortex in human structural brain networks. Cerebral Cortex, 28(1), 281-294.