# Reproductibilité et réplicabilité en neuroImagerie

Gaëlle Leroux

► To cite this version:

Gaëlle Leroux. Reproductibilité et réplicabilité en neuroImagerie. Doctorat. Journée Reproductibilité en Sciences, Lyon, France. 2024, pp.27. hal-04534013

HAL Id: hal-04534013

https://hal.science/hal-04534013

Submitted on 5 Apr 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Reproductibilité et réplicabilité en neuroImagerie

Gaëlle Leroux

► To cite this version:

Gaëlle Leroux. Reproductibilité et réplicabilité en neuroImagerie. Doctorat. Journée Reproductibilité en Sciences, Lyon, France. 2024, pp.27. hal-04534013

HAL Id: hal-04534013

https://hal.science/hal-04534013v1

Submitted on 5 Apr 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

LYON St-ETIENNE
UNIVERSITIES
GRADUATE +

# Reproductibilité & réplicabilité en neurolmagerie

04 avril 2024

<figure><img src="image_3.png" /></figure>

Centre de Recherche en
Neurosciences de Lyon

Gaëlle Leroux, PhD

gaelle.leroux@cnrs.fr

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

https://orcid.org/0000-0003-2729-4945

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

https://cv.hal.science/gaëlle-leroux

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

REMi

Réseau d'Entraide Multicentrique en IRM

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

Ouvrir
la science !

Collège des données de la recherche
<figure><img src="image_2.png" /></figure>

LYON St-ETIENNE
UNIVERSITIES
GRADUATE +

# Reproductibilité & réplicabilité en neurolmagerie

04 avril 2024

<figure><img src="image_3.png" /></figure>

Centre de Recherche en
Neurosciences de Lyon

Gaëlle Leroux, PhD

gaelle.leroux@cnrs.fr

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

https://orcid.org/0000-0003-2729-4945

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

https://cv.hal.science/gaëlle-leroux

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

REMi

Réseau d'Entraide Multicentrique en IRM

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

Ouvrir
la science !

Collège des données de la recherche
# Neurolmagerie ou imagerie cérébrale : principales techniques

## Transcranial Magnetic Stimulation – TMS

Stimulation transcrânienne
à courant direct – tDCS

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

Source

## ElectroEncéphalo Graphie – EEG –

Near InfraRed
Spectroscopy – NIRS

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

Source

## Magnéto Encéphalo Graphie – MEG

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

© C. Beurtey/CEA

## Imagerie par Résonance Magnétique – IRM

Tomographie par Émission de Positons – TEP

<figure><img src="image_11.png" /></figure>
# Neurolmagerie ou imagerie cérébrale : principales techniques

## Transcranial Magnetic Stimulation – TMS

Stimulation transcrânienne
à courant direct – tDCS

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

Source

## ElectroEncéphalo Graphie – EEG –

Near InfraRed
Spectroscopy – NIRS

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

Source

## Magnéto Encéphalo Graphie – MEG

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

© C. Beurtey/CEA

## Imagerie par Résonance Magnétique – IRM

Tomographie par Émission de Positons – TEP

<figure><img src="image_11.png" /></figure>
# Neurolmagerie ou imagerie cérébrale : types de données

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

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

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

<figure><img src="image_15.png" /><figcaption>Data time courses</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>ERP-image</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>Source analysis</figcaption></figure>

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

Source

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

Source

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

Source

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

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

Source

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

Source

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

Source
# Neurolmagerie ou imagerie cérébrale : types de données

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

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

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

<figure><img src="image_15.png" /><figcaption>Data time courses</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>ERP-image</figcaption></figure>

<figure><img src="image_17.png" /><figcaption>Source analysis</figcaption></figure>

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

Source

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

Source

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

Source

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

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

Source

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

Source

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

Source
# « Recherche reproductible »? – RR -

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

Goodman & al. 2016. *Sci Transl Med.* DOI: 10.1126/scitranslmed.aaf5027

<table><thead><tr><th colspan="3">Data</th></tr><tr><th></th><th>Same</th><th>Different</th></tr></thead><tbody><tr><th>Analysis</th><td>Reproducible</td><td>Replicable</td></tr><tr><th>Different</th><td>Robust</td><td>Generalisable</td></tr></tbody></table>

The Turing Way Community. (2022). The Turing Way: A handbook for reproducible, ethical and collaborative research. Zenodo. doi: 10.5281/zenodo.3233853 (lien vers la figure)

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

## Message #1

### La RR se décline pour les :

- Méthodes

- Résultats

- Inférences
# « Recherche reproductible »? – RR -

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

Goodman & al. 2016. *Sci Transl Med.* DOI: 10.1126/scitranslmed.aaf5027

<table><thead><tr><th colspan="3">Data</th></tr><tr><th></th><th>Same</th><th>Different</th></tr></thead><tbody><tr><th>Analysis</th><td>Reproducible</td><td>Replicable</td></tr><tr><th>Different</th><td>Robust</td><td>Generalisable</td></tr></tbody></table>

The Turing Way Community. (2022). The Turing Way: A handbook for reproducible, ethical and collaborative research. Zenodo. doi: 10.5281/zenodo.3233853 (lien vers la figure)

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

## Message #1

### La RR se décline pour les :

- Méthodes

- Résultats

- Inférences
# Crise de la reproductibilité : alertes et prise de conscience

## IS THERE A REPRODUCIBILITY CRISIS?

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

©nature

## HAVE YOU FAILED TO REPRODUCE AN EXPERIMENT?

Most scientists have experienced failure to reproduce results.

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

Baker. 1,500 scientists lift the lid on reproducibility. *Nature* (2016). https://doi.org/10.1038/533452a
# Crise de la reproductibilité : alertes et prise de conscience

## IS THERE A REPRODUCIBILITY CRISIS?

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

©nature

## HAVE YOU FAILED TO REPRODUCE AN EXPERIMENT?

Most scientists have experienced failure to reproduce results.

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

Baker. 1,500 scientists lift the lid on reproducibility. *Nature* (2016). https://doi.org/10.1038/533452a
Facteurs de la crise de reproductibilité

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

Source
Facteurs de la crise de reproductibilité

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

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

Peng (2011) Reproducible Research in Computational Science. *Science* https://doi.org/10.1126/science.1213847

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

La reproductibilité n'est pas binaire mais c'est plutôt un continuum
<figure><img src="image_30.png" /></figure>

Peng (2011) Reproducible Research in Computational Science. *Science* https://doi.org/10.1126/science.1213847

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

La reproductibilité n'est pas binaire mais c'est plutôt un continuum
## ÉCONOMIE LINÉAIRE

<figure><img src="image_32.png" /></figure>

PRENDRE

FABRIQUER

JETER

## ÉCONOMIE CIRCULAIRE

<figure><img src="image_33.png" /></figure>
## ÉCONOMIE LINÉAIRE

<figure><img src="image_32.png" /></figure>

PRENDRE

FABRIQUER

JETER

## ÉCONOMIE CIRCULAIRE

<figure><img src="image_33.png" /></figure>
<figure><img src="image_34.png" /></figure>

Message à l'attention des PI:

« envisager le partage des données dès le début »

FUTURE PARADIGM
CURRENT

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

Message à l'attention des PI:
envisager la réutilisation des données avant d'en collecter de nouvelles

Lambin, P. et al. (2013) Rapid Learning health care in oncology - an approach towards decision support systems enabling customised radiotherapy'. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology. http://dx.doi.org/10.1016/j.radonc.2013.07.007
<figure><img src="image_34.png" /></figure>

Message à l'attention des PI:

« envisager le partage des données dès le début »

FUTURE PARADIGM
CURRENT

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

Message à l'attention des PI:
envisager la réutilisation des données avant d'en collecter de nouvelles

Lambin, P. et al. (2013) Rapid Learning health care in oncology - an approach towards decision support systems enabling customised radiotherapy'. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology. http://dx.doi.org/10.1016/j.radonc.2013.07.007
# Changement culturel

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

Le partage des données devient la norme en neuro-imagerie

I might add another layer at the bottom of the pyramid:
“Raise awareness of the problem.”
Burk, 2023.

Source

Image credit: "EPFL Open science" twitter account

Original by Nosek

Image credit: icon made by Freepik on www.flaticon.com
# Changement culturel

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

Le partage des données devient la norme en neuro-imagerie

I might add another layer at the bottom of the pyramid:
“Raise awareness of the problem.”
Burk, 2023.

Source

Image credit: "EPFL Open science" twitter account

Original by Nosek

Image credit: icon made by Freepik on www.flaticon.com
## STUDY INCEPTION AND PLANNING

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

### Study Preparation

Ensure quality of data and design

* Release Standard Operating Procedures

* Pilot your experiment

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

https://compose.neurosynth.org/

protocol exchange

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

protocols.io

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

https://dmp.opidor.fr/

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

### Pre-Registration

Have a thorough research plan:
study design, hypotheses and
analysis

* Follow best practices

* Use pre-registration / Registered Reports, report deviations

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

OSF
PREREGISTRATION

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

AS PREDICTED

ClinicalTrials.gov

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
## STUDY INCEPTION AND PLANNING

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

### Study Preparation

Ensure quality of data and design

* Release Standard Operating Procedures

* Pilot your experiment

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

https://compose.neurosynth.org/

protocol exchange

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

protocols.io

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

https://dmp.opidor.fr/

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

### Pre-Registration

Have a thorough research plan: study design, hypotheses and analysis

* Follow best practices

* Use pre-registration / Registered Reports, report deviations

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

OSF
PREREGISTRATION

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

AS PREDICTED

ClinicalTrials.gov

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
Pre-registration of a project
with peer-reviews: “registered reports”

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

https://www.cos.io/initiatives/registered-reports

Registration Forms and Templates: https://osf.io/zab38/wiki/home/

Nosek et al. (2018) The preregistration revolution. *Proc. Natl Acad. Sci. USA* https://doi.org/10.1073/pnas.1708274114

Nosek & Lakens (2014) Registered reports: a method to increase the credibility of published results. *Soc. Psychol.*
https://doi.org/10.1027/1864-9335/a000192
Pre-registration of a project
with peer-reviews: “registered reports”

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

https://www.cos.io/initiatives/registered-reports

Registration Forms and Templates: https://osf.io/zab38/wiki/home/

Nosek et al. (2018) The preregistration revolution. *Proc. Natl Acad. Sci. USA* https://doi.org/10.1073/pnas.1708274114

Nosek & Lakens (2014) Registered reports: a method to increase the credibility of published results. *Soc. Psychol.*
https://doi.org/10.1027/1864-9335/a000192
Pre-registration of a project
with peer-reviews: “registered reports”

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

*Figure 2. Positive result rates for standard reports and Registered Reports. Error bars indicate 95% confidence intervals around the observed positive result rate.*

Scheel et al. (2021) An excess of positive results: Comparing the standard Psychology literature with Registered Reports. *Advances in Methods and Practices in Psychological Science*. https://doi.org/10.1177/25152459211007467
Pre-registration of a project
with peer-reviews: “registered reports”

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

*Figure 2. Positive result rates for standard reports and Registered Reports. Error bars indicate 95% confidence intervals around the observed positive result rate.*

Scheel et al. (2021) An excess of positive results: Comparing the standard Psychology literature with Registered Reports. *Advances in Methods and Practices in Psychological Science*. https://doi.org/10.1177/25152459211007467
# Écosystème d'outils pour améliorer la reproductibilité/réplicabilité

## STUDY INCEPTION AND PLANNING

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

### Study Preparation

Ensure quality of data and design

* Release Standard Operating Procedures

* Pilot your experiment

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

https://compose.neurosynth.org/

protocol exchange

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

protocols.io

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

https://dmp.opidor.fr/

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

### Pre-Registration

Have a thorough research plan: study design, hypotheses and analysis

* Follow best practices

* Use pre-registration / Registered Reports, report deviations

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

OSF
PREREGISTRATION

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

AS PREDICTED

ClinicalTrials.gov

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

### Ethics and Sharing plan

Meet ethical and regulatory requirements

* Informed consent

* Internationally oriented data governance

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

Open Brain
Consent

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

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

### Monitoring Quality

Ensure quality of acquired data

* Establish quality control checkpoints

* Quality assurance

* Include positive control analyses

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

ReproNim

MRIQC

XNAT

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

Qoala-T

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

VisualQC

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
# Écosystème d'outils pour améliorer la reproductibilité/réplicabilité

## STUDY INCEPTION AND PLANNING

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

### Study Preparation

Ensure quality of data and design

* Release Standard Operating Procedures

* Pilot your experiment

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

https://compose.neurosynth.org/

protocol exchange

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

protocols.io

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

https://dmp.opidor.fr/

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

### Pre-Registration

Have a thorough research plan: study design, hypotheses and analysis

* Follow best practices

* Use pre-registration / Registered Reports, report deviations

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

OSF
PREREGISTRATION

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

AS PREDICTED

ClinicalTrials.gov

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

### Ethics and Sharing plan

Meet ethical and regulatory requirements

* Informed consent

* Internationally oriented data governance

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

Open Brain
Consent

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

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

### Monitoring Quality

Ensure quality of acquired data

* Establish quality control checkpoints

* Quality assurance

* Include positive control analyses

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

ReproNim

MRIQC

XNAT

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

Qoala-T

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

VisualQC

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
■ dicomdir/

■ 1208200617178_22/

□ 1208200617178_22_8973.dcm

□ 1208200617178_22_8943.dcm

□ 1208200617178_22_2973.dcm

□ 1208200617178_22_8923.dcm

□ 1208200617178_22_4473.dcm

□ 1208200617178_22_8783.dcm

□ 1208200617178_22_7328.dcm

□ 1208200617178_22_9264.dcm

□ 1208200617178_22_9967.dcm

□ 1208200617178_22_3894.dcm

□ 1208200617178_22_3899.dcm

■ 1208200617178_23/

■ 1208200617178_24/

■ 1208200617178_25/

<figure><img src="image_60.png" /></figure>

■ my_dataset/

□ participants.tsv

■ sub-01/

■ anat/

□ sub-01_T1w.nii.gz

■ func/

□ sub-01_task-rest_bold.nii.gz

□ sub-01_task-rest_bold.json

■ dwi/

□ sub-01_dwi.nii.gz

□ sub-01_dwi.json

□ sub-01_dwi.bval

□ sub-01_dwi.bvec

■ sub-02/

■ sub-03/

■ sub-04/
■ dicomdir/

■ 1208200617178_22/

□ 1208200617178_22_8973.dcm

□ 1208200617178_22_8943.dcm

□ 1208200617178_22_2973.dcm

□ 1208200617178_22_8923.dcm

□ 1208200617178_22_4473.dcm

□ 1208200617178_22_8783.dcm

□ 1208200617178_22_7328.dcm

□ 1208200617178_22_9264.dcm

□ 1208200617178_22_9967.dcm

□ 1208200617178_22_3894.dcm

□ 1208200617178_22_3899.dcm

■ 1208200617178_23/

■ 1208200617178_24/

■ 1208200617178_25/

<figure><img src="image_60.png" /></figure>

■ my_dataset/

□ participants.tsv

■ sub-01/

■ anat/

□ sub-01_T1w.nii.gz

■ func/

□ sub-01_task-rest_bold.nii.gz

□ sub-01_task-rest_bold.json

■ dwi/

□ sub-01_dwi.nii.gz

□ sub-01_dwi.json

□ sub-01_dwi.bval

□ sub-01_dwi.bvec

■ sub-02/

■ sub-03/

■ sub-04/
<figure><img src="image_61.png" /></figure>

<table><thead><tr><th></th><th colspan="6">modality</th></tr><tr><th></th><th>MRI</th><th>PET</th><th>meeg</th><th>behavioral</th><th>microscopy</th><th>NIRS</th><th>motion</th></tr></thead><tbody><tr><th rowspan="5">datatype</th><td>anat</td><td>pet</td><td>eeg</td><td>beh</td><td>micr</td><td>nirs</td><td>motion</td></tr><tr><td>func</td><td></td><td>meg</td><td></td><td></td><td></td><td></td></tr><tr><td>dwi</td><td></td><td>ieeg</td><td></td><td></td><td></td><td></td></tr><tr><td>perf</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

To be extended to:

* Animal electrophysiology

* Eyetracking

* Magnetic resonance spectroscopy

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

<table><thead><tr><th></th><th colspan="6">modality</th></tr><tr><th></th><th>MRI</th><th>PET</th><th>meeg</th><th>behavioral</th><th>microscopy</th><th>NIRS</th><th>motion</th></tr></thead><tbody><tr><th rowspan="5">datatype</th><td>anat</td><td>pet</td><td>eeg</td><td>beh</td><td>micr</td><td>nirs</td><td>motion</td></tr><tr><td>func</td><td></td><td>meg</td><td></td><td></td><td></td><td></td></tr><tr><td>dwi</td><td></td><td>ieeg</td><td></td><td></td><td></td><td></td></tr><tr><td>perf</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

To be extended to:

* Animal electrophysiology

* Eyetracking

* Magnetic resonance spectroscopy

* ...
sub-01

ses-01

anat

sub-01_ses-01_T1w.nii.gz

sub-01_ses-01_task-olfloc_run-01_eeg.edf

sub-01_ses-01_task-olfloc_run-01_events.tsv

sub-01_ses-01_task-olfloc_run-01_channelsvtsv

Slide from pres. Rémi Gau @CRNL 2023

Pernet et al. (2019) EEG-BIDS, an extension to the brain imaging data structure for
electroencephalography. Sci Data https://doi.org/10.1038/s41597-019-0104-8
sub-01

ses-01

anat

sub-01_ses-01_T1w.nii.gz

sub-01_ses-01_task-olfloc_run-01_eeg.edf

sub-01_ses-01_task-olfloc_run-01_events.tsv

sub-01_ses-01_task-olfloc_run-01_channelsvtsv

Slide from pres. Rémi Gau @CRNL 2023

Pernet et al. (2019) EEG-BIDS, an extension to the brain imaging data structure for
electroencephalography. Sci Data https://doi.org/10.1038/s41597-019-0104-8
Bienvenue sur le XNAT du CRNL dédié au stockage
des données source de tous les protocoles du
CRNL !

TOUS les types de données peuvent être déposés.

Les pré-traitements, les données générées et les analyses statistiques doivent être réalisés dans les espaces
disques des équipes, comme d'habitude.

Une question sur l'identification ? > merci d'ouvrir un ticket info (https://extranet.crnfr/ticket)

Une question sur les projets ? > merci d'envoyer un email à gaelle.leroux@cnrs.fr

Welcome to the CRNL XNAT dedicated to the
storage of the source data of all CRNL protocols!

ALL data types can be uploaded.

The pre-processing, derived data and statistical analyses are performed on the team disk space, as usual.

Any question about xnat login? > please, open a ticket to the IT service at the CRNL
(https://extranet.crnfr/ticket).

Any question about the projects? > please, send an email to gaelle.leroux@cnrs.fr

LOGIN

ldap1

USER

PASSWORD

Forgot login or password?

Login
Bienvenue sur le XNAT du CRNL dédié au stockage
des données source de tous les protocoles du
CRNL !

TOUS les types de données peuvent être déposés.

Les pré-traitements, les données générées et les analyses statistiques doivent être réalisés dans les espaces
disques des équipes, comme d'habitude.

Une question sur l'identification ? > merci d'ouvrir un ticket info (https://extranet.crnfr/ticket)

Une question sur les projets ? > merci d'envoyer un email à gaelle.leroux@cnrs.fr

Welcome to the CRNL XNAT dedicated to the
storage of the source data of all CRNL protocols!

ALL data types can be uploaded.

The pre-processing, derived data and statistical analyses are performed on the team disk space, as usual.

Any question about xnat login? > please, open a ticket to the IT service at the CRNL
(https://extranet.crnfr/ticket).

Any question about the projects? > please, send an email to gaelle.leroux@cnrs.fr

LOGIN

ldap1

USER

PASSWORD

Forgot login or password?

Login
# MRIQC pour contrôler la qualité des images en IRM (T1, T2, BOLD)

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

<figure><img src="image_63.png" /></figure>
# MRIQC pour contrôler la qualité des images en IRM (T1, T2, BOLD)

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

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

<figure><img src="image_64.png" /></figure>
# Écosystème d'outils pour améliorer la reproductibilité/réplicabilité

## DATA ACQUISITION

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

### Brain Data

Transparent and reproducible data acquisition

* Use open hardware

* Use open software

* Report full acquisition details

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

open source
imaging

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

MR-Hub

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

VENUS

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

OPENBCI

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

qMR
Lab

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

### Stimulus

Reproducible stimulus presentations

* Report detailed stimuli, timings, responses, etc.

* Use open frameworks and share stimulus materials

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

PsychoPy
the open source psychology library

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

PsychToolbox

ERP CORE™

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

Pavlovia

ReproStim

## RESEARCH DATA MANAGEMENT

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

### Data organization and standards

Ensure data are interoperable and reusable

* Organize your neuroimaging data following the Brain Imaging Data Structure (BIDS)

* Utilize available tools, converters and apps that work with BIDS

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

BIDS

BRAIN IMAGING DATA STRUCTURE

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

NIFTI

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

JSON

<figure><img src="image_78.png" /></figure>

TSV

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

### Metadata and data annotation

Ensure data are understandable, interoperable and reusable

* Annotate data using established structures

* Track provenance with Neuroimaging Data Model (NIDM)

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

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

PyNIDM
NIDM-Terms

InterLeX

CogPO

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

cognitive atlas

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

### Data management and tracking

Track and version control data for update, retrieval, and reuse

* Use open data hosting services

* Use tools for decentralized data management

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

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

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

GIN

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

brainlife

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

Labguru eLabFTW

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
# Écosystème d'outils pour améliorer la reproductibilité/réplicabilité

## DATA ACQUISITION

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

### Brain Data

Transparent and reproducible data acquisition

* Use open hardware

* Use open software

* Report full acquisition details

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

open source
imaging

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

MR-Hub

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

VENUS

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

OPENBCI

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

qMR
Lab

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

### Stimulus

Reproducible stimulus presentations

* Report detailed stimuli, timings, responses, etc.

* Use open frameworks and share stimulus materials

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

PsychoPy
the open source psychology library

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

PsychNII Toolbox

ERP CORE™

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

Pavlovia

ReproStim

## RESEARCH DATA MANAGEMENT

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

### Data organization and standards

Ensure data are interoperable and reusable

* Organize your neuroimaging data following the Brain Imaging Data Structure (BIDS)

* Utilize available tools, converters and apps that work with BIDS

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

BIDS

BRAIN IMAGING DATA STRUCTURE

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

<figure><img src="image_78.png" /></figure>

### Metadata and data annotation

Ensure data are understandable, interoperable and reusable

* Annotate data using established structures

* Track provenance with Neuroimaging Data Model (NIDM)

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

PyNIDM
NIDM-Terms

InterLeX

CogPO

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

cognitive atlas

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

### Data management and tracking

Track and version control data for update, retrieval, and reuse

* Use open data hosting services

* Use tools for decentralized data management

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

Data
Ldd

OpenNEURO

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

GIN

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

brainlife

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

Labguru eLabFTW

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
# Écosystème d'outils pour améliorer la reproductibilité/réplicabilité

## DATA PROCESSING AND ANALYSIS

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

### Software

Choose from the many open tools available

* Implement best practices when writing code, and share openly

* Test for analytical robustness

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

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

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

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

SPM

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

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

GitHub

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

GitLab

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

### Standardizing workflows

Enhance reproducibility

* Use standardized workflows for automation, reproducibility and transparency

* Use containers to ensure computational reproducibility

MRIQC

fMRIPrep

NiPreps

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

MNE

MNE-BIDS Pipeline

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

BIDS

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

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

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

docker

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

### Statistical modelling

Focus on reproducibility and transparency

* Use analysis pipelines with automatic (machine readable) documentation

* Use standardized structures

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

ni
learn

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

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

FitLins

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

Neuroscout

BIDS-SM

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

SPM

MNE

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

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

EEGLAB

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

Brainstorm

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

### Multiverse analysis

Explore effects of variations in analysis pipeline on study results

* Vary critical analysis parameters

* Re-run analysis with different tools and test for robustness

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

FUZZY

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

Explorable
Multiverse
Analyses

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

Les données ouvertes et des logiciels d'analyse ouverts sont essentiels pour la reproductibilité en analyse des données

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
# Écosystème d'outils pour améliorer la reproductibilité/réplicabilité

## DATA PROCESSING AND ANALYSIS

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

### Software

Choose from the many open tools available

* Implement best practices when writing code, and share openly

* Test for analytical robustness

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

AFNI FSL BrainStorm Nipype EEGLAB SPM

<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>

GitHub

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

GitLab

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

### Standardizing workflows

Enhance reproducibility

* Use standardized workflows for automation, reproducibility and transparency

* Use containers to ensure computational reproducibility

MRIQC

fMRIPrep

NiPreps

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

MNE

MNE-BIDS Pipeline

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

BIDS

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

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

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

docker

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

### Statistical modelling

Focus on reproducibility and transparency

* Use analysis pipelines with automatic (machine readable) documentation

* Use standardized structures

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

ni learn

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

AFNI FSL

FitLins

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

Neuroscout

BIDS-SM

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

SPM

MNE

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

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

EEGLAB

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

Brainstorm

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

### Multiverse analysis

Explore effects of variations in analysis pipeline on study results

* Vary critical analysis parameters

* Re-run analysis with different tools and test for robustness

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

FUZZY

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

Explorable Multiverse Analyses

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

Les données ouvertes et des logiciels d'analyse ouverts sont essentiels pour la reproductibilité en analyse des données

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
<figure><img src="image_116.png" /></figure>

Public-nEUro

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

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

OMEGA

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

The Open MEG
Archive (OMEGA)

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

ARTEM-IS

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

DISSEMINATION

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

Data sharing

FAIR (Findable, Accessible, Interoperable, Reusable)

* Standardize data with rich metadata, and share it under persistent identifiers on public repositories and a license

* Publish Data Descriptors

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

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

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

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

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

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

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

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

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

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

<figure><img src="image_133.png" /></figure>

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

Paper publication

Publish with openness and reproducibility in mind

* Follow best practices

* Publish on preprint servers and/or open access journals

bioRxiv

medRxiv

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

PsYArXiv

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

OSF PREPRINTS

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

NeuroLibre

CODE OCEAN

Jupyter {book}

Open Research Europe

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

Code sharing

FAIR for reproducible analysis

* Document code and share it on public repositories + license

* Use version control

* Use containers

cascad

git

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

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

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

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

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

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

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

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

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

zenodo

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

GIN

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

Beyond publication

Disseminate scientific results to the broader scientific community and to the society in general

* Conferences, workshops, mass media, social networks

<figure><img src="image_150.png" /></figure>

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

brainhack.org

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

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

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

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

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

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

Derived data sharing

FAIR derived data and results

* Share results of analyses in an interoperable and understandable way, so they are reusable and reproducible

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

NEUROVAULT

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

brainlife

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

OSF

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

EBRAINS

zenodo

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

Inclusive, diverse
community research

Open resources and welcoming spaces, diversity of ideas and approaches

* Equity, diversity and inclusivity

* Impact on careers, work-life balance, and mental health

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

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

Women in Neuroscience

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

CARE Principles
for Indigenous
Data Governance

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

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

cascad
the first certification
agency for scientific
code & data
<figure><img src="image_111.png" /></figure>

Public-nEUro

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

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

OMEGA

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

The Open MEG
Archive (OMEGA)

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

ARTEM-IS

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

DISSEMINATION

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

Data sharing

FAIR (Findable, Accessible, Interoperable, Reusable)

* Standardize data with rich metadata, and share it under persistent identifiers on public repositories and a license

* Publish Data Descriptors

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

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

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

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

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

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

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

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

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

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

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

Paper publication

Publish with openness and reproducibility in mind

* Follow best practices

* Publish on preprint servers and/or open access journals

bioRxiv
medRxiv

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

NeuroLibre

CODE OCEAN

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

PsycArXiv

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

OSF PREPRINTS

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

Open Research Europe

<figure><img src="image_133.png" /></figure>

Code sharing

FAIR for reproducible analysis

* Document code and share it on public repositories + license

* Use version control

* Use containers

cascad

git

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

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

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

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

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

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

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

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

CO
CODE OCEAN

zenodo

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

GIN

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

Beyond publication

Disseminate scientific results to the broader scientific community and to the society in general

* Conferences, workshops, mass media, social networks

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

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

brainhack.org

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

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

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

Derived data sharing

FAIR derived data and results

* Share results of analyses in an interoperable and understandable way, so they are reusable and reproducible

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

NEUROVAULT

<figure><img src="image_150.png" /></figure>

brainlife

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

OSF

EBRAINS

zenodo

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

Inclusive, diverse
community research

Open resources and welcoming spaces, diversity of ideas and approaches

* Equity, diversity and inclusivity

* Impact on careers, work-life balance, and mental health

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

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

Women in Neuroscience

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

CARE Principles
for Indigenous
Data Governance

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

cascad
the first certification
agency for scientific
code & data
https://www.cascad.tech/

Niso et al. (2022) Open and reproducible neuroimaging: From study inception to publication. *NeuroImage*. https://doi.org/10.1016/j.neuroimage.2022.119623 - https://oreoni.github.io/index.html
Artemis

English (US)

study_id

Design and sample

Hardware

Acquisition

Preprocessing

Measurement

Channel choice

Visualization

Other

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

Home

ARTEMIS readme

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

ARTEM-IS

Agreed Reporting Template for EEG Methodology -
International Standard: template for event-related
potentials (ERP)

The goal of the ARTEM-IS is to use insights derived from systematic reviews to create human-friendly, machine-readable templates for documenting the methodological details of an EEG study or pipeline. The template for reporting ERP methodology before you is a pilot project of ARTEM-IS, based on which other subfields of EEG may follow.

https://remi-gau.github.io/artemis_checklist/#/
Artemis

English (US)

study_id

Design and sample

Hardware

Acquisition

Preprocessing

Measurement

Channel choice

Visualization

Other

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

Home

ARTEMIS readme

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

ARTEM-IS

Agreed Reporting Template for EEG Methodology -
International Standard: template for event-related
potentials (ERP)

The goal of the ARTEM-IS is to use insights derived from systematic reviews to create human-friendly, machine-readable templates for documenting the methodological details of an EEG study or pipeline. The template for reporting ERP methodology before you is a pilot project of ARTEM-IS, based on which other subfields of EEG may follow.
<figure><img src="image_170.png" /></figure>

Où que nous en soyons sur le chemin de la science ouverte, il existe des outils qui facilitent la tâche et la rendent plus reproductible.

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

Vous n'êtes pas seul(e) !
Vous êtes entouré(e) de personnes ravies de vous aider
au sein de vos communautés.

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

L'erreur est humaine !
Autocorrigez les bugs et
vérifiez leur impact.

<figure><img src="image_173.png" /></figure>

Image credit: icons made by Freepik, VectorPortal, SBTS2018 on www.flaticon.com
<figure><img src="image_159.png" /></figure>

Où que nous en soyons sur le chemin de la science ouverte, il existe des outils qui facilitent la tâche et la rendent plus reproductible.

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

Vous n'êtes pas seul(e) !
Vous êtes entouré(e) de personnes ravies de vous aider
au sein de vos communautés.

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

L'erreur est humaine !
Autocorrigez les bugs et
vérifiez leur impact.

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

Image credit: icons made by Freepik, VectorPortal, SBTS2018 on www.flaticon.com
<figure><img src="image_174.png" /></figure>

COLLECTION
PASSEPORT POUR
LA SCIENCE OUVERTE

https://www.ouvrirlascience.fr/category/ressources/

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

Recherche reproductible : principes méthodologiques pour une science transparente

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

Inria

<figure><img src="image_177.png" /></figure>

41016

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

Ouvert à l'inscription

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

Reproducible Research II: Practices and tools for managing computations and...

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

Inria

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

41023

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

Starting on May 16, 2024

Réseau français pluridisciplinaire de recherche reproductible

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

RR
FR

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

FR Reproducible
Research network

https://www.recherche-reproductible.fr/

Mailing-liste, actualités, GT, ressources

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

3ème journées du réseau de recherche reproductible
Avril 2025 à Lyon – La Doua –
<figure><img src="image_163.png" /></figure>

COLLECTION
PASSEPORT POUR
LA SCIENCE OUVERTE

https://www.ouvrirlascience.fr/category/ressources/

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

Réseau français pluridisciplinaire de recherche reproductible

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

RR
FR

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

FR Reproducible
Research network

https://www.recherche-reproductible.fr/

Mailing-liste, actualités, GT, ressources

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

3ème journées du réseau de recherche reproductible
Avril 2025 à Lyon – La Doua –
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Ce travail a uniquement été rendu possible grâce à l'aide de :

Olivier Bertrand, précédent directeur du CRNL (2011-2023)

Laurent Bezin, directeur du CRNL & l'équipe de direction du CRNL (2024-...)

Le groupe Science Ouverte du CRNL : Pierre-Emmanuel Aguera, Olivier Bertrand, Laurent Bezin, Anne Cheylus, Justine Épinat-Duclos, Alexandra Fargeot, Gaëlle Leroux, Guillaume Sescousse*.

Les groupes de réflexion du CRNL :

sur l'intégrité scientifique animé par Fabien Chauveau, Nicolas Fourcaud-Trocmé, Nicolas Grimault, Nicola Kuczewski*,

sur la méthodologie animé par Alexandra Corneyllie & Françoise Lecaignard*,

sur la neuro-imagerie animé par Justine Épinat-Duclos, Isabelle Faillenot, Gaëlle Leroux*,

sur la science et le climat animé par Marion Delous & Guillaume Sescousse*.

Les groupes de travail du CRNL :

sur le libre accès,

les plans de gestion des données,

les cahiers de laboratoire électroniques.
<figure><img src="image_168.png" /></figure>

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

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

Ce travail a uniquement été rendu possible grâce à l'aide de :

Olivier Bertrand, précédent directeur du CRNL (2011-2023)

Laurent Bezin, directeur du CRNL & l'équipe de direction du CRNL (2024-...)

Le groupe Science Ouverte du CRNL : Pierre-Emmanuel Aguera, Olivier Bertrand, Laurent Bezin, Anne Cheylus, Justine Épinat-Duclos, Alexandra Fargeot, Gaëlle Leroux, Guillaume Sescousse*.

Les groupes de réflexion du CRNL :

sur l'intégrité scientifique animé par Fabien Chauveau, Nicolas Fourcaud-Trocmé, Nicolas Grimault, Nicola Kuczewski*,

sur la méthodologie animé par Alexandra Corneyllie & Françoise Lecaignard*,

sur la neuro-imagerie animé par Justine Épinat-Duclos, Isabelle Faillenot, Gaëlle Leroux*,

sur la science et le climat animé par Marion Delous & Guillaume Sescousse*.

Les groupes de travail du CRNL :

sur le libre accès,

les plans de gestion des données,

les cahiers de laboratoire électroniques.