physiopy: open development solutions for physiology in MRI

The physiopy contributors:

Daniel Alcalá, Apoorva Ayyagari, Katie Bottenhorn, Molly Bright, César Caballero-Gaudes, Inés Chavarría, Vicente Ferrer, Soichi Hayashi, Vittorio Iacovella, François Lespinasse, Ross Markello, Stefano Moia, Robert Oostenveld, David Romero-Bascones, Taylor Salo, Rachael Stickland, Eneko Uruñuela, Merel van der Thiel, & Kristina Zvolanek.

physiopy

MRI-related physiology is still a niche  → we need more researchers and clinicians to become interested in the topic. Sharing physiological data following the concepts of Open (Science) Data could improve the exposition of this topic

*Open Source Software Development is the idea of developing a software publicly, sharing it from the beginning of the development, fostering a democratic community of contributors in support of the project, using version control and software testing.

One aim of physiopy is to ease this process using a Community driven, BIDS-based, Open Development* approach.

physiopy

physiopy's main aims translate into three core components:

  1. A BIDSificator, phys2bids
  2. (Pre)processing tools for physiological data based on BIDS
  3. A documentation that introduces users to the world of physiological data

Improving physiopy's documentation

Project 1: Improve physiopy's documentation

Skills required:

  • None!                                            

Skills recommended:

  • git/Github
  • MarkDown
  • reStructuredText                         

Skills acquired:

  • git/Github [basic]
  • MarkDown
  • physiologial denoising techniques

BIDSifying physiological data: phys2bids

physiopy/phys2bids is our flagship repository, introduced in December 2019.

Its aim is reorganising physiological recordings into BIDS format, and it supports AcqKnowledge (BIOPAC) and Labchart (ADInstruments) files.

Project 2: Extend support for filetypes in phys2bids (Siemens MRI data)

Skills required:

  • python [basics]              

Skills recommended:

  • git/Github
  • Continuous Integration

Skills acquired:

  • git/Github          
  • Continuous Integration
  • physio data interaction

Denoising fMRI data: phys2denoise

physiopy/phys2denoise is our second repository, introduced in May 2020.

Its aim is creating denoising regressors for fMRI from physiological recordings.

Project 3: Write testing functions for phys2denoise

Skills required:

  • python [basics]              

Skills recommended:

  • git/Github                       
  • pytest

Skills acquired:

  • git/Github          
  • Continuous Integration
  • pytest

Preprocess physio data: peakdet

physiopy/peakdet was "donated" by its maintaner, Ross Markello, and is currently maintained by physiopy.

Its aim is denoising physiological data and detect peaks in the signal.

Project 4: Improve peakdet's GUI

Skills required:

  • python
  • matplotlib GUI development

Skills recommended:

  • git/Github                                 
  • pytest

Skills acquired:

  • git/Github          
  • Continuous Integration          
  • pytest

physiopy

Bonus project: Design logos!

physiopy

phys2bids

Credit to Daniel Alcala'

Join us over Mattermost and/or Gathertown!

Mattermost channel: ~physiopy

GitHub: https://github.com/physiopy

That's all folks!

Thanks to...

... the physiopy contributors

... the tedana community!

...you for the (sustained) attention!