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The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses

View ORCID ProfileLukas Snoek, Maite M. van der Miesen, Tinka Beemsterboer, Andries van der Leij, Annemarie Eigenhuis, H. Steven Scholte
doi: https://doi.org/10.1101/2020.06.16.155317
Lukas Snoek
1University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
2Spinoza Centre for Neuroimaging, location Roeterseilandcampus, Amsterdam, The Netherlands
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  • ORCID record for Lukas Snoek
  • For correspondence: lukassnoek@gmail.com
Maite M. van der Miesen
1University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
3Currently at: Maastricht University, School for Mental Health and Neuroscience, Department of Anesthesiology, Maastricht, The Netherlands
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Tinka Beemsterboer
1University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
2Spinoza Centre for Neuroimaging, location Roeterseilandcampus, Amsterdam, The Netherlands
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Andries van der Leij
1University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
4Currently at: Brainsfirst BV, Amsterdam
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Annemarie Eigenhuis
1University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
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H. Steven Scholte
1University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
2Spinoza Centre for Neuroimaging, location Roeterseilandcampus, Amsterdam, The Netherlands
5Neurensics BV, Amsterdam.
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Abstract

We present the Amsterdam Open MRI Collection (AOMIC): three datasets with multimodal (3T) MRI data including structural (T1-weighted), diffusion-weighted, and (resting-state and task-based) functional BOLD MRI data, as well as detailed demographics and psychometric variables from a large set of healthy participants (N = 928, N = 226, and N = 216). Notably, task-based fMRI was collected during various robust paradigms (targeting naturalistic vision, emotion perception, working memory, face perception, cognitive conflict and control, and response inhibition) for which extensively annotated event-files are available. For each dataset and data modality, we provide the data in both raw and preprocessed form (both compliant with the Brain Imaging Data Structure), which were subjected to extensive (automated and manual) quality control. All data is publicly available from the Openneuro data sharing platform.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Updated the manuscript after finishing the ID1000 derivatives data upload.

  • https://openneuro.org/datasets/ds003097

  • https://openneuro.org/datasets/ds002785

  • https://openneuro.org/datasets/ds002790

  • #1 https://nipy.org/nibabel/

  • #2 https://cran.r-project.org/web/packages/oro.nifti

  • #3 https://cran.r-project.org/web/packages/gifti

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 05, 2020.
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The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses
Lukas Snoek, Maite M. van der Miesen, Tinka Beemsterboer, Andries van der Leij, Annemarie Eigenhuis, H. Steven Scholte
bioRxiv 2020.06.16.155317; doi: https://doi.org/10.1101/2020.06.16.155317
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The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses
Lukas Snoek, Maite M. van der Miesen, Tinka Beemsterboer, Andries van der Leij, Annemarie Eigenhuis, H. Steven Scholte
bioRxiv 2020.06.16.155317; doi: https://doi.org/10.1101/2020.06.16.155317

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