OHBM 2018: my first remotely-attended conference

Last updated: Tue, 03 Jul 2018 13:58:05 GMT 0 comments

June 14-21 were the OHBM hackathon and annual meeting in Singapore. I did not get the chance to attend in person and instead I've been following the conference on Twitter! Here are a few interesting things I spotted.

Open science at OHBM is booming! ūüéČ Last year, I was happy to see a better integration of open science activities in the main program. This year, it went one step up! The 3-day hackathon was very well attended with over 100 participants and an amazing organization. Throughout the meeting, and in multiple occasions, talks in the open science room attracted a packed audience. And the new "ice cream for open science" looked like a real success.

OHBM 2018 young investigator award went to Daniel Margulies, who was one of the first to introduce the neuroimaging community to hackathons through Brainhacks with Cameron Craddock.

At the PhD/Postdoc SIG mentoring symposium, Lucina Uddin discussed how to fail better and how failures are inevitably part of all successful academic careers. This is so important!

A topic of personal interest for me, as a mother, it looks like more attendees were bringing their children to the congress. I know some conferences provide free childcare (e.g. RailsConf) and this must make the whole conference experience so much different! I am wondering if there anything we could do to make this happen at OHBM?

Of course I've missed up on many things but following the event on Twitter has been much better than I anticipated! Thanks for everyone who tweeted using #OHBM2018. And I hope to see you all next year in Roma!

Sprinting with bio-imagers and how I learnt about NEUBIAS, EuBI, Elixir and tried out myBinder!


May 14-15, I was in Cambridge for a coding sprint jointly organized by bio- and medical- imaging infrastructures. The goal of the sprint was to capitalize on the infrastructure training experiences in order to provide online registries of training materials and create reproducible training environments.


We were a group of about 20 software engineers and research scientists from bio-imaging (microscopy), medical imaging (MRI) and bioinformatics.

The first morning, we introduced ourselves:

For the rest of the sprint we had two working groups:

  • WG1: Curation and vocabulary alignments
  • WG2: Reproducible training sessions using containers

In WG1, we started by representing various examples of training materials using the NEUBIAS model (as used in BISE). The following day, there was further effort to align this with Tess and bioschemas and to incorporate more examples directly in BISE.

On the second day, I joined WG2. I was very happy to find out about myBinder! Give it a GitHub repository with a Jupyter notebook and it will turn it into an interactive notebook hosted online!. We used mybinder at: https://github.com/dwaithe/model-training and further focused on providing a Docker file that could be run locally to launch the course (https://github.com/ac744/model-training). I've also tested it on one of my own repository: Software_Comparison#3!

I very much enjoyed meeting and working with members of the bioimage and bioinformatics communities!

I'd like to thank the organizers Perrine Paul-Gilloteaux from University of Nantes and Gabriella Rustici from the University of Cambridge as well as FLI for support to attend the event.

This event was covered using #trainhackcam on twitter.

OHBM 2017

Last updated: Thu, 21 Jun 2018 12:42:30 GMT 0 comments


June 25th-30th, I attended OHBM 2017 in Vancouver. It has been a very rich and energizing meeting with open science activities being better and better integrated with the main meeting! The 5th OHBM hackathon has been a success and, this year, the program of the open science room was included in the official program booklet. "Neurohackers" were even featured in the closing highlights!

#OHBM2017 Highlights from Pedro Valdez-Sosa: Neurohackers are a great benefit to our organization

screen shot 2017-07-14 at 11 28 31

‚ÄĒ OHBM (@OHBM) 29 juin 2017

Here is my (very) short summary of the congress:

  • Cluster Failure: Why fMRI Inferences for Spatial Extent Have Inflated False-Positive Rates: a follow up by Anders Eklund after his highly discussed paper investigating validity of clusterwise inference. Anders discussed follow up simulations he did in reply to some of the criticism to his paper. In particular, randomisation of events at the subject level. Overall the results hold.

  • Keynote: Threat to valid fMRI inference (Tal Yarkoni): A great keynote packed with panda pictures to illustrate over-generalisation of the results. In particular, Tal presented joint work with Westfall and Nichols on treating stimuli as a random effects.

  • Informatics session: Open Neuroimaging Lab presented by Katja Heuer for collaborative annotations and curation of anatomical neuroimaging data. Comparison of automated meta-analysis in Neurosynth with manually curated from BrainMap presented by Taylor Salo, OpenNeuro presented by Chris Gorgolewski: a new online plateform for data analysis (and data sharing), Mapping of cognitive function in the human cerebellum presented by Jorn Diedrichsen, Performance of Various Brain Atlases for Individual Identification using resting fMRI presented by Andrew Michael and the Brainnetome Atlas presented by Lingzhong Fan.

  • Keynote: Revisiting Wernicke‚Äôs Area (Marsel Mesulam): A great keynote, discussing the role of Wenicke's region and how Wernicke's location has evolved through time.

  • Mentorship: The brand new mentorship program organised by OHBM Student & Postdoc SIG also ran a session with career advice, including Mathew Abrams from INCF and Cameron Craddock on first grants.

  • Demos (open science room): Many demos happened in the open science room throughout the congress, including: power tools for fMRI: neuropower by Joke Durnez and fmripower by Jeannette Mumford, BIDS presented by Cyril Pernet, NeuroVault by Chris Gorgolewski, Preprocessed Connectomes Project by Cameron Craddock and FMRIPREP by Oscar Esteban.

  • and much more!

See the #OHBM2017 on twitter and the OHBM blog for more discussions.

Mozilla Open Leadership Training

Last updated: Sun, 03 Sep 2017 12:48:41 GMT 0 comments

From March to June, I participated in the 3rd round of the Open Leadership Training organised by Mozilla. This 12-week online training provides working open best practices as well as mentorship form the Mozilla community. I applied to join the 3rd cohort of open project leads in response to this call. This was a great experience and I would encourage everyone to apply for the next round!

Applications for Open Leadership Training round 4 are now open!

At the end of the program I was interviews by Abby Cabunoc Mayes, who is lead developer at Mozilla and runs the open leadership training. The interview is available on Medium and copied below.


Practical Approaches for Reproducing Studies

#mozsprint 2017 Interview Series

Camille (@cmaumet) is a Research Fellow at the Oxford Big Data Institute, focusing on open research and best statistical practices for meta-analyses. Camille was selected to join our current cohort of Mozilla Open Leaders for her work furthering open research practices and passion for open science. Earlier this month, Camille brought her project ‚ÄėEasy fMRI Reporting‚Äô, which she started when she was at the University of Warwick, to Mozilla‚Äôs Global Sprint (#mozsprint). I interviewed Camille to learn more about her experience at #mozsprint, her project ‚ÄėEasy fMRI Reporting‚Äô and how you can help.

What is Easy fMRI Reporting?

‚ÄėEasy fMRI reporting‚Äô is an online curriculum that describes practical approaches to perform reproducible studies in the context of functional Magnetic Resonance Imaging (fMRI) research. Our motto is:

‚ÄúPractical solutions to follow open science best practices in fMRI research. Learn how to comply with transparency best practices with little overhead!‚ÄĚ

What is functional Magnetic Resonance Imaging (fMRI)?

fMRI is an imaging method that provides information on how the brain works. One application is to try and understand which parts of the brain are active for a given task. For instance, I might ask you to move your right hand while you are lying in the MRI scanner in order to found out which part of your brain is responding while you are doing this simple task.

Why did you start ‚ÄėEasy fMRI Reporting‚Äô?

Scientific communities, and in particular the brain imaging community, are increasingly calling for more transparent research practices. But in practice complying with accepted best practices can prove difficult and time consuming. Fortunately a number of tools and standards are now available in the fMRI community to make our research more transparent! ‚ÄėEasy fMRI reporting‚Äô describes current practical solutions to share data and code in support of the publication of an fMRI study and provides step-by-step recipes for different levels of data and code sharing.

Why is data and code sharing important for fMRI studies?

An fMRI acquisition generates a series of brain images and researcher have to apply a set of mathematical methods (or ‚Äúpipeline‚ÄĚ) in order to outline active brain regions. For example, an fMRI pipeline typically includes an alignment step to correct for the effect of motion. Even if we are not aware of it, everyone tends to slightly move their head while in the scanner. For a group analysis (when we try to study brain activations across a group of participants), the pipeline also includes a transformation that puts all the individual brains in a common space (as our brains are all different!). There are many choices that are made along the analysis of fMRI data and two researchers might not necessarily agree on what is the best pipeline for a given dataset. ‚ÄúReporting‚ÄĚ is the action by which researchers share all the details about the pipeline (usually as code) and the data they used. I think that sharing all those details is essential in order to fully understand the generalisability of the findings. But it is also an excellent opportunity to work more collaboratively and to build stronger results as data and code can be reused by new studies.

What are you most proud of accomplishing at #mozsprint?

At #mozsprint, I got very nice feedback on how to improve the ‚Äúvision statement‚ÄĚ of the project. Being able to communicate the overall idea of a project in 1 or 2 simple sentences is particularly important but I find writing up those 2 sentences quite challenging! By getting feedback from contributors that were not involved in creation of the project, I had the chance to improve the vision statement much more efficiently.

This #mozsprint, I also got the chance to reuse an existing lesson template that was created and shared by Neurohackweek and that derived from a template by the Software Carpentry. After benefiting from those resources to build the first version of the ‚Äėeasy fMRI reporting‚Äô website, I was, in turn, able to suggest a couple of edits back to the main project, which is great!

Looking back at where you were when you joined the Mozilla Open Leaders cohort, are you where you expected to be? What have you learned in this process?

By joining the Mozilla Open Leaders Cohort, I learned that building a community is a lot about make it easy to enter and participate. From creating easy tasks to conveying the goal of the project in a couple of short sentences all those simple steps make a difference!

How can others help you continue the work on Easy fMRI Reporting?

‚ÄėEasy fMRI reporting‚Äô is looking for all sort of contributions! Please check out the open issues in our GitHub repository. For example, we are currently looking for designers to improve the website and create a logo, for data scientists to provide feedback on their experience sharing code and/or data and for tool developers interested in creating a lesson to showcase their tool. Other ideas? Please get in touch!

Is there anything else you’d like to add?

Yes, I want to thank Demitri Muna for his support and advice throughout this project. I very much enjoyed discussing with him how data sharing is done in the astronomy community! And finally, I would also like to include a link to the Mozilla GitHub repository template that are very useful to start up a new project: https://github.com/acabunoc/mozsprint-repo-template!

EPSRC ICT Early Career Researchers Workshop

Last updated: Fri, 14 Jul 2017 11:15:59 GMT 0 comments

On February 16th-17th, I went to Sheffield to attend an early career workshop organised by the Information and communication technologies (ICT) theme of the Engineering and Physical Sciences Research Council (EPSRC). The aim of the workshop was to present the research council strategy and provide guidance for grant applications.

During this 1.5 day meeting, time was divided between presentations, discussions and plenty of breaks. This was was a very positive experience, I did appreciate the opportunity to meet with other young researchers and discuss their experience. Some useful links are included below.

EPSRC Introduction & Strategy by Liam Blackwell, EPSRC ICT Theme lead

  • Balancing capabilities: overview of the research areas covered by EPSRC and how these are planned to evolve in the future. Researchers are encouraged to read the research area rationales.
  • Cross-ICT priorities: A number of theme that are prioritised over all applications.

The Peer review process by Zoe Brown, Portfolio Manager EPSRC ICT Theme

EPSRC ICT Fellowships by Netta Cohen, University of Leeds, Pietro Olivieto, University of Sheffield & Adan Luqmani, Portfolio Manager EPSRC ICT Theme

Impact and public engagement by Alan Winfield, University of West of England/Bristol Robotics & Sarah Newman, ICT Theme EPSRC

  • 10 tips for academic blogging.
  • Public engagement can take various forms: participation in ‚ÄúScience caf√©‚ÄĚ, blogging (e.g. about a paper), website describing the research project,...

I would like to thank my department (WMG) and the Wellcome Trust for their support.


More informations: EPSRC Blog post on the event, Slides, ICT theme website, EPSRC website, EPSRC ICT workshop call, #icterc.

Switch between two versions of FSL

Last updated: Mon, 20 Feb 2017 14:06:26 GMT 0 comments

Most of the times we can rely on a single version of FSL. But recently I have been developing an update for FEAT (more info here), and needed to temporary switch between:

  1. FSL 5.0.9 (installed on my system);
  2. the patched FSL I was working on.

This short snippet allows to switch between the main FSL installation (available by default) and the development FSL version (available at /Users/cmaumet/Softs/external/fsl_patched):

export FSLDIR=/Users/cmaumet/Softs/external/fsl_patched
. ${FSLDIR}/etc/fslconf/fsl.sh

How to create a pip package?

Last updated: Fri, 06 Jul 2018 15:01:09 GMT 0 comments

In this first post you will find quick references to the commands needed to share your package through Pypi.

Pypi, available at https://pypi.python.org, is the official repository for Python packages. Packages available on Pypi can be installed very easily using pip install <package_name>.

Registering your package and first upload

To make your Python package available on Pypi, you will need to:

  1. Create configuration files (including setup.py, setup.cfg) for your project, cf. https://packaging.python.org/distributing/#configuring-your-project for a full list.
  2. Build your package
python setup.py sdist
python setup.py bdist_wheel
  1. Register your project and upload to Pypi test server
python setup.py register -r https://testpypi.python.org/pypi
twine upload -r pypitest dist/*
  1. Check that the install works fine from Pypi test server
pip install -i https://testpypi.python.org/pypi <PACKAGE_NAME>
  1. Upload your package to Pypi!
twine upload -r pypi dist/*

Releasing a new version

To make a new version of your package available:

  1. Delete any previous built
rm -rf dist
rm -rf build
rm -rf *.egg-info
  1. Rebuild your package
python setup.py sdist
python setup.py bdist_wheel
  1. Send to Pypi test server and check the installation
twine upload -r pypitest dist/*
pip install -i https://testpypi.python.org/simple <PACKAGE_NAME>
  1. Upload to Pypi!
twine upload -r pypi dist/*

For more information, the official documentation (with examples) is available at: https://packaging.python.org/distributing

Edited on 06/07/2018: replacing '/pypi' by '/simple' when installing from pypi test.