Enhancing studies of the connectome in autism using the autism brain imaging data exchange II
By A. di Martino, David O’Connor, Bosi Chen, K. Alaerts, Jeffrey S. Anderson, Michal Assaf, Joshua H. Balsters, L. Baxter, A. Beggiato, Sylvie Bernaerts and 29 more. Scientific Data, 2017
670 citations recorded by the source corpus.
The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity. Design Type(s) data integration objective • observation design Measurement Type(s) nuclear magnetic resonance assay Technology Type(s) digital curation Factor Type(s) research institute • study design • Autism Sample Characteristic(s) Homo sapiens • brain Design Type(s) data integration objective • observation design Measurement Type(s) nuclear magnetic resonance assay Technology Type(s) digital curation Factor Type(s) research institute • study design • Autism Sample Characteristic(s) Homo sapiens • brain Machine-accessible metadata file describing the reported data (ISA-Tab format)
Subfields: Cognitive Neuroscience, Pediatrics, Perinatology and Child Health
View Paper: https://www.semanticscholar.org/paper/6bb98e82c0d0603c12a24a1ce74e26325e43328b
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In Cognitive Neuroscience
- Zening Fu
- Yuhui Du
- Meng-Chuan Lai
- Michael V. Lombardo
- Simon Baron-Cohen
- Vince D. Calhoun
- Enzo Ferrante
- Sally J. Wheelwright
In Pediatrics, Perinatology and Child Health
Citations in the corpus
- Big data approaches to decomposing heterogeneity across the autism spectrum (2018, methodology): “There are some current resources that are immediately available to meet such needs (e.g., the ABIDE datasets76, the National Database for Autism Research (NDAR)77, the Simons Simplex Collection78, SPARK79, the Healthy Brain Network80, and see81, 82) and we would expect much more in the coming years.”
- Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis (2020, background): “, Autism Brain Imaging Data Exchange (ABIDE) I (28)].”
- Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging (2018, background): “…Autism Brain Imaging Data Exchange (ABIDE) initiative has aggregated functional and structural brain imaging data collected from laboratories around the world to accelerate the understanding of the neural bases of ASD (http://fcon_1000.projects.nitrc.org/indi/abide/)(Di Martino et al., 2014, 2017).”