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3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N = 3,373).

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A Scalable Toolkit for Modeling 3D Surface-Based Brain Geometry

  • 会议论文

  • 发表日期：

    2026年

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  • Yanghee Im,
  • Leila Nabulsi,
  • Melody J. Y. Kang,
  • Sophia I. Thomopoulos,
  • Ana M. Diaz Zuluaga,
  • Anders M. Dale,
  • Andriana Karuk,
  • Annabella Di Giorgio,
  • Benson Mwangi,
  • Boris Gutman,
  • Bronwyn Overs,
  • Carlos López Jaramillo,
  • Colm McDonald,
  • Dan J. Stein,
  • Dara M. Cannon,
  • David Glahn,
  • Diego Hidalgo-Mazzei,
  • Diliana Pecheva,
  • Dominik Grotegerd,
  • Edith Pomarol-Clotet,
  • Eduard Vieta,
  • Emilie Olie,
  • Enric Vilajosana Chertó,
  • Fabio Sambataro,
  • Fleur Howells,
  • Freda Scheffler,
  • Geraldo Busatto,
  • Gerard Anmella,
  • Giovana B. Zunta-Soares,
  • Gloria Roberts,
  • Henk Temmingh,
  • Ian Gotlib,
  • Ingrid Agartz,
  • Jair C. Soares,
  • James A. Karantonis,
  • James Prisciandaro,
  • Janice M. Fullerton,
  • Joaquim Radua,
  • Jonathan Savitz,
  • Josselin Houenou,
  • Kang Sim,
  • Kenichiro Harada,
  • Klaus Berger,
  • Koji Matsuo,
  • Lakshmi Yatham,
  • Lars Tjelta Westlye,
  • Lisa Eyler,
  • Lisa Furlong,
  • Luisa Klahn,
  • Marco Hermesdorf,
  • Marcus V. Zanetti,
  • Matthew Kempton,
  • Matthew Sacchet,
  • Mikael Landen,
  • Mon-Ju Wu,
  • Pedro Rosa,
  • Philip Mitchell,
  • Pravesh Parekh,
  • Raymond Salvador,
  • Rayus Kuplicki,
  • Salvador Sarró,
  • Susan Rossell,
  • Tamsyn Van Rheenen,
  • Theodore Satterthwaite,
  • Tilo Kircher,
  • Tomas Hajek,
  • Udo Dannlowski,
  • Xavier Caseras,
  • Yuji Zhao,
  • Ole A. Andreassen,
  • Paul M. Thompson,
  • Christopher R. K. Ching

摘要

3D surface-based computational mapping is more sensitive to localized brain alterations in neurological, developmental and psychiatric conditions than traditional gross volumetric analysis, providing fine-scale 3D maps of a wide range of surface-based features. Here we introduce a scalable toolkit for large-scale computational surface analysis, with efficient algorithms for multisite data integration, statistical harmonization, accelerated multivariate statistics, and visualization. We showcase the utility of the toolkit by mapping subcortical shape variations and factors that affect them across 21 international samples from the ENIGMA Bipolar Disorder Working Group (N = 3,373).