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. 2021 Jul;18(7):698-700.
doi: 10.1038/s41592-021-01186-4.

The ENIGMA Toolbox: multiscale neural contextualization of multisite neuroimaging datasets

Sara Larivière  1 , Casey Paquola  2   3 , Bo-Yong Park  2   4 , Jessica Royer  2 , Yezhou Wang  2 , Oualid Benkarim  2 , Reinder Vos de Wael  2 , Sofie L Valk  5   6 , Sophia I Thomopoulos  7 , Matthias Kirschner  8 , Lindsay B Lewis  9   10 , Alan C Evans  9   10 , Sanjay M Sisodiya  11   12 , Carrie R McDonald  13 , Paul M Thompson  7 , Boris C Bernhardt  14
Affiliations

The ENIGMA Toolbox: multiscale neural contextualization of multisite neuroimaging datasets

Sara Larivière et al. Nat Methods. 2021 Jul.
No abstract available

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Figures

Figure 1.
Figure 1.. Overview of the ENIGMA Toolbox.
(a) World map of a subset of Working Groups. 100+ summary statistics from published studies are accessible within the ENIGMA Toolbox. (b) Surface visualization tools are provided to project cortical and subcortical data results to the surface. As an example, we displayed gray matter atrophy in left focal epilepsy. (c) To contextualize neuroimaging data with respect to microscale brain organization, Toolbox users can fetch disease-related gene expression data (here, we displayed the average expression levels of focal epilepsy genes (left)), stratify atrophy (or other effect maps) according to BigBrain statistical moments (middle left) and gradient (middle right), and stratify atrophy patterns according to cytoarchitectonic classes (right). (d) To contextualize neuroimaging data with respect to macroscale brain organization, Toolbox users can load preprocessed functional and structural connectivity data (left), build hub susceptibility models to assess relationships between hub regions and atrophy patterns (middle left) and assess statistical significance of two surface maps using spin permutation testing (middle right), and identify cortical and subcortical disease epicenters that herald patterns of atrophy.
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