Second summer training project collaboration between INCF and Mathworks

MathWorks is an inaugural member of the INCF Industry Advisory Council (IAC), which serves as an advisory body to the governing bodies of INCF by providing input on the strategic directions and activities of the network. The IAC works to increase the link between INCF members working in industry and academia, and promotes INCF within the business sector with interests in neuroinformatics. Read more about the IAC here.

Training and education of early career “neuroinformaticians” is a major focus for the INCF, and it’s also an area prioritized by many IAC members, including MathWorks. Towards this goal, Mathworks and INCF held a pilot round last summer of engaging current or recently graduated students as trainees to work on MATLAB neuroscience toolboxes. Four trainees worked with mentors from the toolboxes Automatic Analysis, EEGLAB, FieldTrip and MatNWB (read more in last year’s report).

Building on this success, the pilot was expanded in 2022 as the MATLAB Community Toolbox Training Projects program. Interested mentors listed their MATLAB community toolbox and project concepts. Interested trainees indicated their preferences, and ultimately met and matched with their mentors & projects. 

This year, six new mentees - Evgenia Kaurunus, Agah Karakuzu, Stefan Dvoretskii, Johanna Bayer, Alex Estrada and Marielle Darwin - worked with mentors from several community-developed MATLAB toolboxes for neuroscience:

• FIT/GIFT (mentors:  Cyrus Eierud and Vince Calhoun) The FIT and GIFT toolboxes are used to do independent component analysis and blind source separation of group (and single subject) functional magnetic resonance imaging (fMRI) data.
• GraFT (mentors: Adam Charles and Gal Mishne) The GraFT (Graph-Filtered Temporal) toolbox uses dictionary learning to extract signals from spatio-temporal calcium imaging data.  
• NDI (mentor: Stephen Van Hooser) The Neuroscience Data Interface (NDI) is a cross-platform interface standard for reading neuroscience data and storing the results of analyses.
• NWB (mentors: Vijay Iyer and Ueli Rutishauser). The MatNWB toolbox is a Matlab interface for reading and writing electrophysiology data in the Neurodata Without Borders (NWB) 2.x file format, a standard endorsed by INCF. 
• qMRLab (mentor: Mathieu Bourdreau) The Quantitative MRI Lab (qMRLab) is open-source software for quantitative magnetic resonance (MR)  image analysis, intended to make data fitting, simulation and protocol optimization as easy as possible for a myriad of different quantitative models.
• Tapas/PhysIO (mentor: Lars Kasper) The Tapas PhysIO toolbox uses peripheral measures of respiration and cardiac pulsation to do model-based physiological noise correction of functional magnetic resonance imaging (fMRI) data. The toolbox is easy to use with SPM, and its output files can be incorporated into any major neuroimaging analysis package.

All projects this year used GitHub as a platform and each of the trainees worked towards one or more pull requests containing their code contributions. Many of these pull requests have been incorporated into the main code branches for the MATLAB community toolbox, meaning their training experiences have translated into real-world impacts for a public codebase that is used by a large community of neuroscience researchers.