# Towards reusable derived data in neuroimaging

Camille Maumet

► To cite this version:

Camille Maumet. Towards reusable derived data in neuroimaging. MRI Together 2023 - Global workshop on open, reproducible, and inclusive MR research, Dec 2023, Online, Germany. pp.1-53, 2023. [https://hal-04328352](https://hal-04328352)

HAL Id: hal-04328352

https://inria.hal.science/hal-04328352

Submitted on 7 Dec 2023

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# Towards reusable derived data in neuroimaging

December 7, 2023

Camille Maumet

Inria, Univ Rennes, Inserm, CNRS, IRISA
# FAIR neuroimaging

## Findable Accessible Interoperable Reusable

**Technical solutions:** Standards, Databases, Good practices (version control, etc.)

<figure><img src="image_3.png" /></figure>
# FAIR neuroimaging

Findable Accessible Interoperable Reusable

<figure><img src="image_4.png" /></figure>

**Technical solutions:** Standards, Databases, Good practices (version control, etc.)

**A culture change: towards community-driven research**

* Making resources available to the scientific community

* Reusing existing resources (datasets, tools) that were created by others
# Sharing FAIR research products

Acquisition

<figure><img src="image_5.png" /></figure>

Data preparation

<figure><img src="image_6.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_10.png" /></figure>

Data preparation

<figure><img src="image_11.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_15.png" /></figure>

Data preparation

<figure><img src="image_16.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_19.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_20.png" /></figure>

Data preparation

<figure><img src="image_21.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_25.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_26.png" /></figure>

Data preparation

<figure><img src="image_27.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_31.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR datasets

<figure><img src="image_32.png" /></figure>
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

OpenNEURO

<figure><img src="image_35.png" /></figure>

<figure><img src="image_36.png" /></figure>

LORIS

<figure><img src="image_37.png" /></figure>

SHANOIR
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_38.png" /></figure>

<figure><img src="image_39.png" /></figure>

OpenNEURO

<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /></figure>

LORIS

<figure><img src="image_42.png" /></figure>

SHANOIR

<figure><img src="image_43.png" /></figure>

**Findable** we can search
for open datasets in each
repository
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_44.png" /></figure>

<figure><img src="image_45.png" /></figure>

OpenNEURO

<figure><img src="image_46.png" /></figure>

XNAT

<figure><img src="image_47.png" /></figure>

LORIS

<figure><img src="image_48.png" /></figure>

SHANOIR

<figure><img src="image_49.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_50.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /></figure>

OpenNEURO

<figure><img src="image_53.png" /></figure>

XNAT

<figure><img src="image_54.png" /></figure>

<figure><img src="image_55.png" /></figure>

LORIS

<figure><img src="image_56.png" /></figure>

SHANOIR

<figure><img src="image_57.png" /></figure>

## Interoperable?

<figure><img src="image_58.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_59.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Standards for neuroimaging data sharing

* Data and **meta-data**

* A common “language”

<figure><img src="image_60.png" /></figure>
# Brain Imaging Data Structure

<figure><img src="image_61.png" /></figure>

my_dataset/

<figure><img src="image_62.png" /></figure>

participants.tsv

<figure><img src="image_63.png" /></figure>

sub-01/

<figure><img src="image_64.png" /></figure>

anat/

<figure><img src="image_65.png" /></figure>

sub-01_T1w.nii.gz

<figure><img src="image_66.png" /></figure>

func/

<figure><img src="image_67.png" /></figure>

sub-01_task-rest bold.nii.gz

<figure><img src="image_68.png" /></figure>

sub-01_task-rest bold.json

<figure><img src="image_69.png" /></figure>

dwi/

<figure><img src="image_70.png" /></figure>

sub-01_dwi.nii.gz

<figure><img src="image_71.png" /></figure>

sub-01_dwi.json

<figure><img src="image_72.png" /></figure>

sub-01_dwi.bval

<figure><img src="image_73.png" /></figure>

sub-01_dwi.bvec

<figure><img src="image_74.png" /></figure>

sub-02/

<figure><img src="image_75.png" /></figure>

sub-03/

<figure><img src="image_76.png" /></figure>

sub-04/

<figure><img src="image_77.png" /></figure>

The Brain Imaging Data Structure
(BIDS): As Easy as Baking a Cake

Patricia Clement, Ghent
University Hospital, BE

<figure><img src="image_78.png" /></figure>
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_79.png" /></figure>

<figure><img src="image_80.png" /></figure>

OpenNEURO

<figure><img src="image_81.png" /></figure>

XNAT

<figure><img src="image_82.png" /></figure>

<figure><img src="image_83.png" /></figure>

LORIS

<figure><img src="image_84.png" /></figure>

SHANOIR

<figure><img src="image_85.png" /></figure>

**Interoperable?**

<figure><img src="image_86.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_87.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_88.png" /></figure>

<figure><img src="image_89.png" /></figure>

<figure><img src="image_90.png" /></figure>

<figure><img src="image_91.png" /></figure>

<figure><img src="image_92.png" /></figure>

OpenNEURO

<figure><img src="image_93.png" /></figure>

<figure><img src="image_94.png" /></figure>

LORIS

<figure><img src="image_95.png" /></figure>

SHANOIR

<figure><img src="image_96.png" /></figure>

**Interoperable** BIDS acts
as a common languages
across tools

<figure><img src="image_97.png" /></figure>

**Findable** we can search
for open datasets in each
repository

<figure><img src="image_98.png" /></figure>

**Accessible** Direct
download (e.g. Openneuro)
or with Data User
Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_99.png" /></figure>

<figure><img src="image_100.png" /></figure>

<figure><img src="image_101.png" /></figure>

<figure><img src="image_102.png" /></figure>

<figure><img src="image_103.png" /></figure>

OpenNEURO

<figure><img src="image_104.png" /></figure>

<figure><img src="image_105.png" /></figure>

LORIS

<figure><img src="image_106.png" /></figure>

SHANOIR

<figure><img src="image_107.png" /></figure>

**Interoperable** BIDS acts as a common language for tools across the field.

<figure><img src="image_108.png" /></figure>

**Findable** we can search for open datasets in each repository.

<figure><img src="image_109.png" /></figure>

**Reusable** Metadata in BIDS were selected to enable reuse. e.g. *onsets of the task for task-based fMRI*.

<figure><img src="image_110.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_111.png" /></figure>

<figure><img src="image_112.png" /></figure>

<figure><img src="image_113.png" /></figure>

<figure><img src="image_114.png" /></figure>

<figure><img src="image_115.png" /></figure>

OpenNEURO

<figure><img src="image_116.png" /></figure>

<figure><img src="image_117.png" /></figure>

LORIS

<figure><img src="image_118.png" /></figure>

SHANOIR

<figure><img src="image_119.png" /></figure>

**Interoperable** BIDS acts as a common language for tools across the field.

<figure><img src="image_120.png" /></figure>

**Findable** we can search for open datasets in each repository.

<figure><img src="image_121.png" /></figure>

**Reusable** Metadata in BIDS were selected to enable reuse. e.g. *onsets of the task for task-based fMRI*.

<figure><img src="image_122.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR research products

Acquisition

<figure><img src="image_123.png" /></figure>

Data preparation

<figure><img src="image_124.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_125.png" /></figure>

<figure><img src="image_126.png" /></figure>

<figure><img src="image_127.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_128.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

<figure><img src="image_129.png" /></figure>

Credits: Parcels 1, 2 & 4 (CC0), Parcel 3 (CC0), Parcel 5 (CC0).
# Sharing FAIR research products

<figure><img src="image_130.png" /></figure>

Credits: Parcels 1, 2 & 4 (CC0), Parcel 3 (CC0), Parcel 5 (CC0).
# Sharing FAIR research products

<figure><img src="image_131.png" /></figure>

Donders Repository

OpenNEURO

XNAT

SHANOIR

LORIS

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_132.png" /></figure>

Credits: Parcels 1, 2 & 4 (CC0), Parcel 3 (CC0), Parcel 5 (CC0).
Sharing FAIR results

<figure><img src="image_133.png" /></figure>
Sharing FAIR results (task fMRI)

<figure><img src="image_134.png" /></figure>

<figure><img src="image_135.png" /></figure>

<figure><img src="image_136.png" /></figure>

**NEUROVAULT**
## Sharing FAIR results (task fMRI)

<figure><img src="image_137.png" /></figure>

<figure><img src="image_138.png" /></figure>

<figure><img src="image_139.png" /></figure>

**NEUROVAULT**

<figure><img src="image_140.png" /></figure>

**Findable** we can search
for datasets on
NeuroVault

<figure><img src="image_141.png" /></figure>

**Accessible** Direct
download
# Sharing FAIR results (task fMRI)

<figure><img src="image_142.png" /></figure>

<figure><img src="image_143.png" /></figure>

<figure><img src="image_144.png" /></figure>

NEUROVAULT

<figure><img src="image_145.png" /></figure>

**Interoperable?**

<figure><img src="image_146.png" /></figure>

**Findable** we can search
for datasets on
NeuroVault

<figure><img src="image_147.png" /></figure>

**Reusable?**

<figure><img src="image_148.png" /></figure>

**Accessible** Direct
download
# NIDM-Results pack

<figure><img src="image_149.png" /></figure>

<figure><img src="image_150.png" /><figcaption>NIDM-Results
.nidm.zip</figcaption></figure>

<figure><img src="image_151.png" /></figure>

ClusterLabels.nii.gz

<figure><img src="image_152.png" /></figure>

Contrast.nii.gz

<figure><img src="image_153.png" /></figure>

ContrastStandardError.nii.gz

<figure><img src="image_154.png" /></figure>

DesignMatrix.csv

<figure><img src="image_155.png" /></figure>

DesignMatrix.png

<figure><img src="image_156.png" /></figure>

ExcursionSet.nii.gz

<figure><img src="image_157.png" /></figure>

ExcursionSet.png

<figure><img src="image_158.png" /></figure>

GrandMean.nii.gz

<figure><img src="image_159.png" /></figure>

Mask.nii.gz

<figure><img src="image_160.png" /></figure>

nidm.json

<figure><img src="image_161.png" /></figure>

nidm.ttl

<figure><img src="image_162.png" /></figure>

ParameterEstimate_001.nii.gz

<figure><img src="image_163.png" /></figure>

ParameterEstimate_002.nii.gz

<figure><img src="image_164.png" /></figure>

ResidualMeanSquares.nii.gz

<figure><img src="image_165.png" /></figure>

SearchSpaceMask.nii.gz

<figure><img src="image_166.png" /></figure>

TStatistic.nii.gz

ZStatistic.nii.gz

<figure><img src="image_167.png" /></figure>

<figure><img src="image_168.png" /></figure>

Design of the
experiment, pre-
processed data...

<figure><img src="image_169.png" /></figure>

Statistical
estimation

<figure><img src="image_170.png" /></figure>

Effects, standard error
and statistical maps...

<figure><img src="image_171.png" /></figure>

Inference

<figure><img src="image_172.png" /></figure>

Thresholded maps, list
of peaks and clusters...

<figure><img src="image_173.png" /></figure>
# NIDM in SPM, FSL & NeuroVault

## SPM

<figure><img src="image_174.png" /></figure>

### 1. Export

<figure><img src="image_175.png" /></figure>

$ nidmfsl fsl_ds107_group 49 -g Control

### 2. Publication on NeuroVault

NIDM-Results

<figure><img src="image_176.png" /></figure>

<figure><img src="image_177.png" /></figure>
# Sharing FAIR results (task fMRI)

<figure><img src="image_178.png" /></figure>

<figure><img src="image_179.png" /></figure>

<figure><img src="image_180.png" /></figure>

<figure><img src="image_181.png" /></figure>

<figure><img src="image_182.png" /></figure>

**NEUROVAULT**

<figure><img src="image_183.png" /></figure>

**Interoperable** NIDM-Results acts as a common languages across tools

<figure><img src="image_184.png" /></figure>

**Findable** we can search for datasets on NeuroVault

<figure><img src="image_185.png" /></figure>

**Reusable** Metadata in NIDM-Results selected to enable meta-analyses

<figure><img src="image_186.png" /></figure>

**Accessible** Direct download
# Sharing FAIR results (task fMRI)

<figure><img src="image_187.png" /></figure>

<figure><img src="image_188.png" /></figure>

<figure><img src="image_189.png" /></figure>

<figure><img src="image_190.png" /></figure>

<figure><img src="image_191.png" /></figure>

**NEUROVAULT**

<figure><img src="image_192.png" /></figure>

**Interoperable** NIDM-Results acts as a common languages across tools

<figure><img src="image_193.png" /></figure>

**Findable** we can search for datasets on NeuroVault

<figure><img src="image_194.png" /></figure>

**Reusable** Metadata in NIDM-Results selected to enable meta-analyses

<figure><img src="image_195.png" /></figure>

**Accessible** Direct download
# Sharing FAIR research products

<figure><img src="image_196.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

<figure><img src="image_197.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

<figure><img src="image_198.png" /></figure>
# Sharing FAIR intermediary datasets

<figure><img src="image_199.png" /></figure>

Derived data
# Sharing FAIR intermediary datasets

<figure><img src="image_200.png" /></figure>

Derived data

<figure><img src="image_201.png" /></figure>

NITRC

zenodo

General purpose repositories
# Sharing FAIR intermediary datasets

<figure><img src="image_202.png" /></figure>

Derived data

<figure><img src="image_203.png" /></figure>

NITRC

<figure><img src="image_204.png" /></figure>

zenodo

General purpose repositories

<figure><img src="image_205.png" /></figure>

**Findable** can search for open datasets (less specific queries)

<figure><img src="image_206.png" /></figure>

**Accessible** Direct download or Data User Agreement
# Sharing FAIR intermediary datasets

<figure><img src="image_207.png" /></figure>

Derived data

<figure><img src="image_208.png" /></figure>

NITRC

<figure><img src="image_209.png" /></figure>

zenodo

General purpose repositories

<figure><img src="image_210.png" /></figure>

**Findable** can search for open datasets (less specific queries)

<figure><img src="image_211.png" /></figure>

**Accessible** Direct download or Data User Agreement
# Sharing FAIR intermediary datasets

<figure><img src="image_212.png" /></figure>

Derived data

<figure><img src="image_213.png" /></figure>

<figure><img src="image_214.png" /></figure>

<figure><img src="image_215.png" /></figure>

<figure><img src="image_216.png" /></figure>

NITRC

zenodo

General purpose repositories

<figure><img src="image_217.png" /></figure>

**Interoperable?**

<figure><img src="image_218.png" /></figure>

**Findable** can search for
open datasets (less
specific queries)

<figure><img src="image_219.png" /></figure>

**Reusable?**

<figure><img src="image_220.png" /></figure>

**Accessible** Direct
download or Data User
Agreement
# Sharing other FAIR datasets

1. Look for existing standards and databases.

FAIR sharing.org
standards, databases, policies

2. You can help develop the next standards

## BIDS Derivatives

https://bids.neuroimaging.io/

Derivatives are outputs of common processing pipelines, capturing data and meta-data sufficient for a researcher to understand and (critically) reuse those outputs in subsequent processing.

Standardizing derivatives is motivated by use cases where formalized machine-readable access to processed data enables higher level processing.

* BEP011 The structural preprocessing derivatives

* BEP012 The functional preprocessing derivatives

* BEP013 The resting state fMRI derivatives

* BEP016 The diffusion weighted imaging derivatives

* BEP017 Generic BIDS connectivity data schema

* BEP021 Common Electrophysiological Derivatives

And more!
# BIDS Provenance

<figure><img src="image_221.png" /></figure>

Satra
Ghosh

<figure><img src="image_222.png" /></figure>

BIDS

BRAIN IMAGING DATA STRUCTURE

<figure><img src="image_223.png" /></figure>

A) fMRI preprocessing using SPM

<figure><img src="image_224.png" /></figure>

B) fMRI preprocessing using
fMRIPrep

<figure><img src="image_225.png" /></figure>

Two examples of BIDS-Prov graphs with A) a detailed and B) a compact graph representing the derived data provenance.

https://github.com/bids-standard/BEP028_BIDSprov
Provenance Use Case 1 **An unambiguous description of the methods**

<figure><img src="image_226.png" /></figure>
Provenance Use Case 1 **An unambiguous description of the methods**

<figure><img src="image_227.png" /></figure>

<figure><img src="image_228.png" /></figure>

Which release of
SPM was used?

Which registration
algorithm was
selected?

How was the brain
mask computed?
Provenance Use Case 1 **An unambiguous description of the methods**

Can we
**reproduce**
**exactly the same**
**results**
(same data, same
methods)?
Provenance Use Case 1 **An unambiguous description of the methods**

<figure><img src="image_229.png" /></figure>

Can we
reproduce
exactly the same
results
(same data, same
methods)?
## Provenance Use Case 2 **Dealing with
unwanted variability**

> A previously
> widely-used
> parameter is no
> longer considered
> as best practice
## Provenance Use Case 2 **Dealing with
unwanted variability**

A previously
widely-used
parameter is no
longer considered
as best practice

A bug was found
in a given tool
version, can we
retrieve all
corresponding
results?
## Provenance Use Case 2 Dealing with unwanted variability

<figure><img src="image_230.png" /></figure>

A previously widely-used parameter is no longer considered as best practice

A bug was found in a given tool version, can we retrieve all corresponding results?
Provenance Use Case 3 **Exploring factors impacting analytical variability**

<figure><img src="image_231.png" /></figure>

Are my conclusions dependant on the **size of the smoothing kernel** used at Step 5?

<figure><img src="image_232.png" /></figure>

**BIDS-Prov** will soon be open for community feedback!

<figure><img src="image_233.png" /></figure>

http://bids.neuroimaging.io/bep028
# Sharing FAIR research products

<figure><img src="image_234.png" /></figure>
# Sharing FAIR research products

Donders Repository

<figure><img src="image_235.png" /></figure>

<figure><img src="image_236.png" /></figure>

SHANOIR

<figure><img src="image_237.png" /></figure>

OpenNEURO

<figure><img src="image_238.png" /></figure>

LORIS

Acquisition

<figure><img src="image_239.png" /></figure>

<figure><img src="image_240.png" /></figure>

<figure><img src="image_241.png" /></figure>

<figure><img src="image_242.png" /></figure>

Data preparation

<figure><img src="image_243.png" /></figure>

Derived data

<figure><img src="image_244.png" /></figure>

NITRC

zenodo

Statistical analysis

<figure><img src="image_245.png" /></figure>

<figure><img src="image_246.png" /></figure>

<figure><img src="image_247.png" /></figure>

<figure><img src="image_248.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_249.png" /></figure>

<figure><img src="image_250.png" /></figure>

<figure><img src="image_251.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

<figure><img src="image_252.png" /></figure>

<figure><img src="image_253.png" /></figure>
<figure><img src="image_254.png" /></figure>

# Reusing neuroimaging derived data?

Camille Maumet

Thank you!

<figure><img src="image_255.png" /></figure>

@cmaumet.bsky.social

<figure><img src="image_256.png" /></figure>

@cmaumet@fediscience.org