Joaquim Radua, Eduard Vieta, Russell Shinohara, Peter Kochunov, Yann Quidé, Melissa Green, Cynthia Weickert, Thomas Weickert, Jason Bruggemann, Tilo Kircher, Igor Nenadic, Murray Cairns, Marc Seal, Ulrich Schall, Frans Henskens, Janice Fullerton, Bryan Mowry, Christos Pantelis, Rhoshel Lenroot, Vanessa Cropley, Carmel Loughland, Rodney Scott, Daniel Wolf, Theodore Satterthwaite, Yunlong Tan, Kang Sim, Fabrizio Piras, Gianfranco Spalletta, Nerisa Banaj, Edith Pomarol-Clotet, Aleix Solanes, Anton Albajes-Eizagirre, Erick Canales-Rodriguez, Salvador Sarro, Annabella Di Giorgio, Alessandro Bertolino, Michael Stäblein, Viola Oertel, Christian Knöchel, Stefan Borgwardt, Stefan du Plessis, Je-Yeon Yun, Jun Soo Kwon, Udo Dannlowski, Tim Hahn, Dominik Grotegerd, Clara Alloza, Celso Arango, Joost Janssen, Covadonga Díaz-Caneja, Wenhao Jiang, Vince Calhoun, Stefan Ehrlich, Kun Yang, Nicola Cascella, Yoichiro Takayanagi, Akira Sawa, Alexander Tomyshev, Irina Lebedeva, Vasily Kaleda, Matthias Kirschner, Cyril Hoschl, David Tomecek, Antonin Skoch, Therese van Amelsvoort, Geor Bakker, Anthony James, Adrian Preda, Andrea Weideman, Dan Stein, Fleur Howells, Anne Uhlmann, Henk Temmingh, Carlos López-Jaramillo, Ana Díaz-Zuluaga, Lydia Fortea, Eloy Martinez-Heras, Elisabeth Solana, Sara Llufriu
A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power...
May 26, 2020: NeuroImage