Projects

Click the buttons below to filter the projects you may want to join.

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All Git level: 0 none Git level: 1 commit push Git level: 2 branches PRs Git level: 3 continuous integration Hub australasia aus Hub donostia esp Hub marseille fra Hub montreal can Hub toronto can Hub vanderbilt usa behavioral DWI ECG ECOG EEG eye tracking fMRI MEG MRI PET C++ containerization documentation html css Java Julia Matlab Python R shell scripting Unix command line Skills: comfortable Skills: expert Skills: familiar coding methods data management documentation method development pipeline development visualisation AFNI ANTs BIDS Brainstorm Datalad DIPY FieldTrip fMRIPrep Freesurfer FSL Jupyter MNE MRtrix Nipype SPM connectome data visualisation deep learning ICA machine learning MR methodologies neural decoding neural networks PCA physiology reproducible scientific methods single neuron models statistical modelling systems neuroscience

Analyzing Numerical Stability in Linear Registration

This project explores the numerical reliability of the FSL FLIRT linear registration tool. We aim to investigate how …

 Project URL MRI documentation Python documentation reproducible scientific methods Git level: 0 none C++ FSL Hub montreal can

behapy: A behavioural neuroscience analysis package for Python

Studies using optic fibres to record real-time fluorescent biosensors in-vivo are now commonplace, yet despite an increasing …

 Project URL Git level: 1 commit push Git level: 2 branches PRs documentation Python documentation BIDS pipeline development Jupyter systems neuroscience Git level: 0 none method development visualisation Hub australasia aus behavioral data management statistical modelling

Bughunt and Revitalization of JavaScript Behavioural Libraries

Behavioural instruments on the web are essential for data collection, both in the laboratory and at home with participants. There …

 Project URL Git level: 1 commit push Git level: 2 branches PRs documentation documentation Git level: 0 none html css method development behavioral containerization Hub montreal can Java

Clustintime: a toolbox for spatio-temporal clustering of fMRI data

  • What are you doing, for whom, and why? This project is a toolbox that allows researchers in neuroimage to apply clustering …

 Project URL Git level: 2 branches PRs fMRI MRI documentation Python coding methods documentation pipeline development machine learning method development visualisation data visualisation Hub donostia esp

Deriving Resting State Networks and Observing their Behavior Across Age

Since their discovery, resting state networks have elucidated our understanding of cognitive function such as emotion processing, …

 Project URL fMRI MRI documentation coding methods documentation Git level: 0 none ICA AFNI FSL Matlab MR methodologies shell scripting Hub vanderbilt usa

fMRI-EEG Preprocessing QA

We are working on developing a QA pipeline for simultaneously collected fMRI-EEG data so that the user can determine whether the …

 Project URL Git level: 1 commit push fMRI MRI documentation Python documentation pipeline development Git level: 0 none EEG Brainstorm connectome AFNI ANTs FSL SPM Matlab Unix command line shell scripting Hub vanderbilt usa

Launchcontainers: A Python tool for launching containerized analysis on HPC

Launchcontainers is a Python-based program built to automatically launch containerlized MRI processing pipelines. This program …

 Project URL Git level: 1 commit push Git level: 2 branches PRs DWI fMRI MRI documentation Python Skills: familiar coding methods documentation BIDS reproducible scientific methods Hub donostia esp

NARPS Open Pipelines - A codebase to study variability of fMRI analysis workflows

The goal of the NARPS Open Pipelines project is to create a codebase reproducing the 70 pipelines of the NARPS study …

 Project URL Git level: 1 commit push Git level: 2 branches PRs fMRI MRI documentation Python documentation BIDS reproducible scientific methods pipeline development Git level: 0 none statistical modelling AFNI ANTs fMRIPrep FSL Nipype SPM Datalad Hub marseille fra

Neurobagel

Neurobagel is a tool ecosystem that allows researchers to easily annotate their dataset (both phenotypic and imaging attributes) …

 Project URL Git level: 1 commit push Git level: 2 branches PRs DWI fMRI MRI documentation Python Skills: familiar coding methods documentation BIDS reproducible scientific methods Git level: 0 none method development EEG behavioral data management Datalad Unix command line Hub montreal can

NeuroLibre reproducible preprints

  • To bring preprints to life by creating a publishing workflow that can seamlessly integrate narrative and executable content.
  • Our …

 Project URL Git level: 2 branches PRs documentation Python documentation reproducible scientific methods html css R containerization Unix command line Hub montreal can

Neuronal Spiking Ensembles: Dynamics of Representational Geometry

What are the meaningful changes in the brain with experience, that allows for adaptive behavior? When we look at the coordinated …

 Project URL Git level: 2 branches PRs documentation Python coding methods documentation pipeline development Jupyter machine learning PCA visualisation data visualisation behavioral neural decoding single neuron models Hub vanderbilt usa

phys2CVR: a BIDS-compliant python toolbox to compute cerebrovascular reacitvity mapping

phys2cvr is a python toolbox that aims at offering various approaches to compute cerebrovascular mapping, starting from at least a …

 Project URL Git level: 2 branches PRs fMRI MRI documentation Python documentation BIDS pipeline development physiology Hub donostia esp

Physiological derivatives BIDS proposal

Physiopy is a community dedicated to developing solutions for handling physiological data acquired in neuroimaging setups. …

 Project URL documentation documentation BIDS physiology Git level: 0 none data management Hub vanderbilt usa

PhysioQA

We are working on creating a model that can classify physiological data (respiratory + cardiac) that is associated with fMRI data, …

 Project URL Git level: 1 commit push Git level: 2 branches PRs fMRI MRI documentation Python Skills: familiar documentation pipeline development Jupyter deep learning machine learning physiology Git level: 0 none method development visualisation data visualisation Brainstorm connectome Matlab Skills: expert Hub vanderbilt usa

Psy2R: Developing an R package for better inference in multivariate statistical analysis

We consistently use massive data sets across neuroscience and psychology. The routine gathering of big data requires that we are …

Git level: 1 commit push DWI fMRI MRI documentation coding methods documentation reproducible scientific methods method development EEG Hub australasia aus behavioral ECOG eye tracking MEG PET C++ R data management statistical modelling

reviewer2go - a LLM AI review bot

  • We are working on using a large language model to develop prompts to provide a structured review and parameter extraction of a …

 Project URL Git level: 1 commit push documentation Python documentation reproducible scientific methods Hub montreal can

Tedana: TE-dependent analysis

  • What are you doing, for whom, and why?
  • What makes your project special and exciting?
  • How to get started?
  • Where to find key …

 Project URL fMRI MRI documentation Python documentation Git level: 0 none html css method development ICA PCA Hub donostia esp

The evolution of Nipype into Pydra

Nipype is a Python library that provides a uniform interface to existing neuroimaging software and facilitates interaction …

 Project URL Git level: 1 commit push Git level: 2 branches PRs DWI fMRI MRI documentation Python Skills: familiar documentation reproducible scientific methods pipeline development method development Git level: 3 continuous integration Skills: comfortable AFNI ANTs DIPY FieldTrip fMRIPrep Freesurfer FSL MNE MRtrix Nipype SPM

The TAPAS PhysIO Toolbox for Physiological Noise Modeling in fMRI

TL;DR: Watch the videos on PhysIO and MACS to learn about these 2 toolboxes that we are trying to integrate and make more …

 Project URL Git level: 1 commit push fMRI MRI documentation documentation BIDS pipeline development physiology method development visualisation data visualisation statistical modelling SPM ECG Matlab Skills: expert MR methodologies Hub toronto can

Why a centralised project submission?

As the Brainhack Global team, we aim to :

  • create a (de)centralized collaborative working platform,
  • facilitate & increase across-site collaborations and interactions,
  • give more visibility to the projects run under Brainhack Global,
  • encourage sharing ideas, experiences and knowledge across parties,
  • to remove barriers and allow contributions by researchers from all origins and disciplines.

Given that many events in this year Brainhack Global might be in part run virtually, a common platform for project submission and listing will allow you to submit your initial project call to gather interests from researchers from all Brainhack Global event locations.

Submitting a project

Please read our Guidelines for Leading and Attending to Brainhack Projects to get more ideas about:

  • how to design your project and what to expect from a Brainhack experience,
  • how to lead a project,
  • how to be an attendee of a project.

The ideal project should convey ideas with respect to the development of tools, methodologies, guidelines and begets to brainstorming new ideas that would facilitate the implementation of open science practices in neuroscience and create more opportunities for collaborative work and information exchange within the community.

How does it work?

In order to submit a project to the Brainhack Global 2023 Project Gallery, please follow these steps:

  1. Register with an event listed in the Brainhack Global 2023 Events .
  2. Create a GitHub account.
  3. Use our project submission form and fill in the necessary/required information as requested.

Project submission form

What happens next?

Once you have submitted your project, a reviewer will check the information in your issue. They may request some changes if deemed necessary.

Once the review completed the project will be marked as status:web_ready and will be listed on the Brainhack Global 2023 Projects page after a short delay. A subpage dedicated to your own project will be automatically created.

Matching projects with participants

The Brainhack Global team will try to match event attendees to projects across the globe based the expertise/skill sets that attendees want to acquire and those the projects are looking for. Once the attendee registrations are completed, our matching algorithm will be run based on the information provided by the attendees during registration. The attendees will then receive an email listing the best fitting projects for their expertise and interests.

Of course, the project attendees decide to join is ultimately their own. They could either go with the suggested options or they could choose among the other projects listed in the Brainhack Global 2023 Projects page.

Please be aware that, at the very early stage of the interactions, attendees might just want to contact you for more information to make sure that the project is a good fit to the aims they want to achieve from a Brainhack. Therefore, please make sure that you welcome all attentions and explain your project with care and guide them as necessary.