BrainHeart: an integrated open-source software tool for studying heart-brain interactions
Project Description: Recent research has again begun to emphasize the close relationship between the temporal dynamics of heart-rate and blood-pressure with brain dynamics. The study of cardiovascular dynamics and brain dynamics uses a set of conceptually highly inter-related algorithms and software tools, that have yet to be brought together to take advantage of each other. Many projects currently use closed-source commercial software since the existing open-source software is not easy to use or poorly documented. This project aims to implement software to jointly analyze brain and heart dynamics and integrate this software with existing packages as well as existing open datasets. A web platform will also be set up to facilitate web-based analysis.
The expectation in this proposal is to use the GSoC INCF template, set out a plan for how to develop algorithms that will connect the study of brain and heart dynamics, develop a toolbox that packages these algorithms, and uses it on existing open datasets of brain and heart activity including the LEMON dataset, the Human Connectome Project, etc. The proposal preparation therefore involves researching both datasets and algorithms, and proposing how connect them together via a package acting on a Compute-canada based web platform (the details can be filled in later). A good proposal answers the questions, what do you propose to do and why, how will it be done, why are you the person to do it, and why is it feasible.
A Google search for areas like brain-heart interactions, brain-heart interconnectome etc. will yield useful pointers to explore further. There are several open-source packages for heart-rate variability metrics, incrporating them into open-EEG packages like brainstorm or mne-python, and developing tools to connect brain activity and heart-activity measures is an option.
This is a new project, that this GSoC contributor will start from scratch, with help and mentorship from us. We have had good success in the past with such an approach, with successful projects going on to second and third years for additional development, and contributors from one year joining in as mentors for the following year. Additional questions are welcome via Neurostars.
Pre-requisites: Fluency in Python/MATLAB. Familiarity with signal-processing algorithms and data-science/statistics. Familiarity with Slurm and working with clusters preferred. Basic web-development skills or interest in learning them will be useful.
Tech keywords: Oscillations, brain heart interactions, health AI, time-series analysis, online portals No planned longer absences