You've got an idea for a project?
In a pure Brainhack style, participants are encouraged to propose collaborative projects to be developed by small teams onsite during the event. We would like attendees to sign up for some projects, aiming to promote the active collaboration among our participants. Of course, projects are optional (both proposing and taking part in them). So, don’t worry if you prefer to just follow the regular sessions as scheduled in the program. Remember that the project development and the other sessions will happen in parallel.
The projects can focus on a technique, or on multimodal imaging. They can be about data acquisition as much as analysis, or even just data visualization. It's also possible to write a tutorial or documentation for a library/program, or even to replicate a paper (or dockerize it!).
To know more about projects carried out in previous editions, check the general Brainhack website here.
Given space limitations, the current edition will host up to a maximum of three project development teams. For this reason, we invite you to submit your project beforehand on this website, specifically below. Yet, before submitting, please check that your project involves original research (has not been done yet!) and it is feasible for the duration of our event!
The projects to be developed will be chosen on the first day of the Brainhack, giving preference to those that are pre-submitted. Note that activities carried out in Brainhack Donostia 2019 can result in materials available beyond the current event.
Plotly based toolbox for fMRI data visualization and exploratory analysis
Plotly offers open source graphing library for python and JS that can be used to create captivating interacting plots, which features can be exploited in the visualization and exploratory analysis of fMRI data. In this project, we propose to (a) create a fully explorable 3D plot for maps visualization to be embedded in presentations, inspired by a plotly.py example by Emilia Petrisor, and (b) use this 3D plot, combined with a 2D timeseries plot, to deploy a tool for graphical explorative analysis in methods such as Co-Activation Pattern Analysis. Co-Activation Pattern Analysis is a widely used method for dynamic Functional Connectivity Analysis, based on the selection of Critical Timepoints (CTP) in a signal. CTP are selected using an arbitrary threshold to individuate the peaks of a Region of Interest timeseries. In order to improve the selection of signal of interest and discard noise, it is possible to discard CTPs based on other measures (e.g. Framewise Displacement). A GUI based exploration of the data might not only be useful for plotting and selecting CTPs, but it could also help investigating the relationship between CTPs and signal of interest. The toolbox will be developed in python and, depending on the time, in JS. The development of the project should take place on Tuesday the 7th.