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SPM and Data Sharing Guillaume Flandin Wellcome Trust Centre for - - PowerPoint PPT Presentation

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SPM and Data Sharing Guillaume Flandin Wellcome Trust Centre for Neuroimaging University College London Brainhack Warwick, 3 rd March 2017 Reproducible Research An article about computational science in a scientific publication is not the

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SPM and Data Sharing

Brainhack Warwick, 3rd March 2017 Guillaume Flandin Wellcome Trust Centre for Neuroimaging University College London

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Reproducible Research

“An article about computational science in a scientific publication is not the scholarship itself, it is merely advertising of the scholarship. The actual scholarship is the complete software development environment and the complete set of instructions which generated the figures.”

WaveLab and Reproducible Research, J.B. Buckheit and D.L. Donoho. In: Wavelets and Statistics. Springer-Verlag 1995.

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q Internet: distribution, collaboration. q Freeware: GNU licences, copyleft. q Quantitative Programming Environments: high-level, fourth generation programming languages (MATLAB, R, Python, Julia, …)

Reproducible Research

Screenshot of first paragraph of page 24

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SPM & Reproducible Research

Karl Friston’s DEM toolbox

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SPM & Reproducible Research

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q Open Methodology q Open Source q Open Data q Open Access q Open Peer Review q Open Educational Resources

Open Science

https://en.wikipedia.org/wiki/Open_science

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Neuroimaging publications

Publication Peak locations Figure (selected slices) Thresholded statistics

Analysis Pre-processing Publication Raw data Pre-processed data Results Publication

ü Repor&ng guidelines: COBIDAS û Incomplete sta&s&cal results û Ambiguous/incomplete methods û Metadata is not machine readable

Slide: C. Maumet

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International Collaborative Effort

http://nidm.nidash.org http://reproducibility.stanford.edu http://www.reproducibleimaging.org

q INCF Neuroimaging data sharing Task Force (NIDASH)

– Representing 13 labs – Weekly teleconferences, focused workshops, GitHub – Open

q Stanford Center for Reproducible Neuroscience q ReproNim

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Brain Imaging Data Structure NeuroImaging Data Model

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Brain Imaging Data Structure (BIDS)

Benefits of a common standard: q Minimised curation Ø Within a lab over time Ø Between labs (collaboration and multi-centre studies) Ø Between public databases (e.g. OpenfMRI) q Error reduction (automated validation) q Optimised usage of data analysis software (completely automated analysis workflows) “A simple and intuitive way to organise and describe your neuroimaging and behavioural data.”

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Brain Imaging Data Structure (BIDS)

http://bids.neuroimaging.io/

K.J. Gorgolewski et al. The brain imaging data structure, a format for organizing and describing

  • utputs of neuroimaging experiments. Scientific Data (2016)
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Brain Imaging Data Structure (BIDS)

participant_id age sex Sub-001 34 M Sub-002 22 F Sub-003 33 F

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Brain Imaging Data Structure (BIDS)

NIfTI

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Brain Imaging Data Structure (BIDS)

{ “RepetitionTime”: 2, “EchoTime”: 0.03, “FlipAngle”: 78, “SliceTiming”: [0,1.0325,0.06,…], “PhaseEncodingDirection”: “j-” }

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BIDS Validator

http://incf.github.io/bids-validator/

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q Work in progress: – PET / SPECT – EEG / MEG – Model and hypothesis specifications – …

BIDS Extensions

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BIDS Apps

http://bids-apps.neuroimaging.io/ https://www.docker.com/ http://singularity.lbl.gov/ K.J. Gorgolewski et al. BIDS Apps: improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods. PLOS Computational Biology (2017) docker run … bids/spm /bids /output participant --participant_label 01 docker run … bids/spm /bids /output group

BIDS App BIDS Derived data

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Available BIDS Apps

http://bids-apps.neuroimaging.io/

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Brain Imaging Data Structure NeuroImaging Data Model

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NIDM: a set of specifications to describe neuroimaging data

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NIDM: a set of specifications to describe neuroimaging data

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NIDM-Results

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NIDM-Results pack: Compressed file containing a NIDM-Results serialisation and some or all of the referenced image data files.

NIDM-Results

Standard error map (NIfTI)

Statistical map SPM{t} (NIfTI)

Contrast map (NIfTI) Design matrix (png and csv) NIDM-Results graph

.nidm .zip

Slide: C. Maumet

  • C. Maumet et al. Sharing brain mapping statistical results with the neuroimaging

data model. Scientific Data (2017).

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SPM export to NIDM-Results

.nidm .zip

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NIDM-Results Viewer

.nidm .zip

Thomas Maullin-Sapey & Camille Maumet https://github.com/incf-nidash/nidmresults-spmhtml

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Upload NIDM-Results to NeuroVault

K.J. Gorgolewski et al. NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Frontiers in Neuroinformatics (2015).

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Upload NIDM-Results to NeuroVault

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From NeuroVault to Neurosynth

  • T. Yarkoni et al. Large-scale automated synthesis of human functional neuroimaging data.

Nature Methods (2011)

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NIDM: a set of specifications to describe neuroimaging data

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Conclusion

q BIDS q BIDS Apps

spm_BIDS.m hub.docker.com/r/bids/spm/

q NIDM-Results

– Export – Viewer – Upload to NeuroVault

spm_provenance.m spm_results_nidm.m github.com/incf-nidash/ nidmresults-spmhtml

q NIDM-Experiment q NIDM-Workflow

NeuroVault

  • penfMRI
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Acknowledgements

INCF Neuroimaging data sharing Task Force (NIDASH): David Kennedy and Jean-Baptiste Poline. NIDM working group: Tibor Auer, Samir Das, Fariba Fana, Guillaume Flandin, Satra Ghosh, Tristan Glatard, Chris Gorgolewski, Karl Helmer, David Keator, Camille Maumet, Nolan Nichols, Jean-Baptiste Poline, Vanessa Sochat, Jason Steffener, Jessica Turner. Stanford Center for Reproducible Neuroscience: Oscar Esteban, Chris Gorgolewski, Russ Poldrack. Warwick neurodata sharing: Tom Nichols, Alex Bowring, Tom Maullin- Sapey, Ruth Pauli, Peter Williams.