Projects

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All Git level: 0 none Git level: 1 commit push Git level: 2 branches PRs Git level: 3 continuous integration behavioral DWI ECG ECOG EEG eye tracking fMRI fNIRS MEG MRI PET TDCS TMS C++ containerization documentation html css Java Javascript Julia Matlab none Python R shell scripting Unix command line Web Skills: comfortable Skills: expert Skills: familiar Skills: none coding methods data management documentation method development pipeline development tutorial recording visualisation AFNI ANTs BIDS Brainstorm CPAC Datalad DIPY FieldTrip fMRIPrep Freesurfer FSL Jupyter MNE MRtrix Nipype NWB SPM Bayesian approaches causality connectome data visualisation deep learning diffusion diversity inclusivity equality EEG EventRelatedResponseModelling EEG source modelling

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AEDAPT - A multi-platform virtual desktop environment with fully-preinstalled software for reproducible EEG/MEG/MRI data analysis

What are you doing, for whom, and why? AEDAPT provides a containerised data analysis graphical environment (based on Neurodesk; …

 Project URL containerization documentation physiology neural networks shell scripting pipeline development Freesurfer Jupyter hypothesis testing FieldTrip SPM data visualisation Skills: familiar ICA statistical modelling BIDS Matlab coding methods Brainstorm tutorial recording neural encoding reproducible scientific methods ECG Datalad MNE Python systems neuroscience Unix command line PCA EEG source modelling documentation neural decoding eye tracking connectome ECOG Nipype TMS diffusion TDCS EEG MRI Git level: 2 branches PRs behavioral EEG EventRelatedResponseModelling MEG visualisation html css

Agreed Reporting Template for EEG Methodology - International Standard (ARTEM-IS): web-app and terminology lexicon

In the EEG ‘Garden of Forking Paths,’ most research reports do not have enough detail to know which path has been …

 Project URL Git level: 0 none Java documentation physiology Skills: familiar BIDS coding methods reproducible scientific methods Git level: 1 commit push documentation EEG Git level: 2 branches PRs Git level: 3 continuous integration EEG EventRelatedResponseModelling

archivotron: a python suite for naming and organizing data

  • What are you doing, for whom, and why?

We are building a suite of python tools to help people generate BIDS or similar datasets …

 Project URL documentation data management BIDS Python documentation Git level: 2 branches PRs

Aroma

documentation Jupyter Skills: familiar ICA FSL fMRIPrep Python documentation MRI fMRI

Automatic plosive detection and VOT extraction using the Plosion index

Jupyter Python

Benchmark denoising strategies on fMRIPrep processed outputs

The project is a continuation of load_confounds. The aim is to evaluate the impact of denoising strategy on functional …

 Project URL documentation pipeline development Jupyter data visualisation BIDS coding methods fMRIPrep Python documentation connectome MRI Git level: 2 branches PRs fMRI visualisation

BIDS-ephys: let’s BIDSify your animal electrophysiology data

We are working on an extension proposal so that BIDS (a standardized data structure described here) can support …

 Project URL Julia documentation physiology data management Skills: expert BIDS Python documentation

Brainfeed: a tool for domain experts to find recent and relevant public discourse on topics they are familiar with

Brainfeed is a proposed tool that is aimed at scientists to keep track of active and relevant public discussions on topics that …

 Project URL Git level: 0 none documentation data management Skills: familiar Skills: expert Python Git level: 1 commit push documentation html css

Brainharmonic - Generating music from brain signal data using deep learning

This project aims to develop a tool to generate music from brain signals using deep learning models. There has been a lot of work …

 Project URL documentation data management pipeline development machine learning Freesurfer deep learning coding methods information theory method development fMRIPrep Python Git level: 1 commit push documentation EEG MRI Git level: 2 branches PRs fMRI

Build your personal website with GitHub

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Classification of Mild Cognitive Impairment(MCI) with machine learning models

- What are you doing, for whom, and why?

Recent research has discovered that the subregions of hippocampus and medial temporal …

 Project URL documentation MR methodologies machine learning Freesurfer Jupyter SPM data visualisation deep learning statistical modelling coding methods FSL method development R Python AFNI documentation PET MRI Git level: 2 branches PRs visualisation

Continuous testing of neuroimaging results across pipelines and datasets

  • What are you doing, for whom, and why? Neuroimaging results are sensitive to variations in processing pipelines, contributing to …

 Project URL containerization documentation Freesurfer ANTs SPM Skills: familiar coding methods FSL reproducible scientific methods Datalad Python AFNI documentation Git level: 2 branches PRs

Data Driven Spiking Neural Network Optimization in Julia

 Project URL Git level: 0 none Julia documentation physiology neural networks single neuron models data visualisation coding methods method development reproducible scientific methods Python Git level: 1 commit push documentation connectome Git level: 2 branches PRs Git level: 3 continuous integration visualisation

EyetrackPrep: an automatic tool to pre-process eye-tracking data (fixation, blinks, saccades, micro-saccade, pursuit, pupillometry)

Description: This project aims at providing to the eye-tracking research community a standardized software allowing the automatic …

 Project URL Git level: 0 none documentation data management Jupyter data visualisation BIDS method development Python Git level: 1 commit push documentation eye tracking Git level: 2 branches PRs visualisation

Fast Tractography Streamline Search

Create a repository for a Fast tractography / streamline search method. And develop useful scripts / methods.

 Project URL documentation tractography DIPY method development DWI Python Git level: 1 commit push documentation connectome diffusion C++

Going beyond pairwise interactions by digging into Higher-Order Interactions

Modern theories suggest that cognitive functions emerge from the dynamic coordination of neural activity over large-scale and …

 Project URL documentation Skills: familiar Matlab coding methods information theory Python Git level: 1 commit push documentation

Implement Cross Frequency Coupling Analysis in EEG as Consciousness Alteration Biomarker

Jupyter Skills: familiar Skills: expert Matlab MNE Python EEG

Macapype: external pipeline

tractography BIDS Python Nipype diffusion MRI

NeuroDesk - A flexible, scalable, and easy to use data analysis environment for reproducible neuroimaging

  • What are you doing, for whom, and why? Neurodesk provides a containerised data analysis environment to facilitate reproducible …

 Project URL Git level: 0 none Java containerization documentation MR methodologies data management shell scripting pipeline development CPAC Freesurfer Jupyter tractography ANTs FieldTrip SPM data visualisation BIDS coding methods DIPY NWB Brainstorm MRtrix FSL method development DWI reproducible scientific methods Datalad fMRIPrep MNE Python Unix command line AFNI Git level: 1 commit push EEG source modelling documentation ECOG Nipype diffusion PET EEG MRI Git level: 2 branches PRs Git level: 3 continuous integration EEG EventRelatedResponseModelling fMRI MEG visualisation html css

NiiVue: minimal, modular, fast WebGL visualization

  • Popular tools like AFNI, FreeSurfer, FSL, SPM use legacy visualization methods.
  • MRIcroGL and Surfice leverage modern graphics …

 Project URL Git level: 0 none Java documentation Freesurfer SPM data visualisation FSL DWI Python AFNI Git level: 1 commit push documentation PET MRI fMRI visualisation Javascript

Niviz: Configurable quality control image generation and rating

The process of QCing is universally boring, terrible and inefficient.

Java documentation data visualisation BIDS coding methods DWI fMRIPrep Python Git level: 1 commit push documentation Nipype MRI Git level: 2 branches PRs fMRI visualisation html css Javascript

Nobrainer and Nobrainer-Zoo: A 3D Deep Learning based Image Analysis Framework and model repository

Nobrainer is a deep learning toolbox for 3D neuroimaging data analysis. It includes many deep learning tools including data …

 Project URL documentation MR methodologies data management diversity inclusivity equality data visualisation deep learning coding methods tutorial recording Datalad Python Git level: 1 commit push documentation MRI visualisation html css

Non-invasive brain stimulation BIDS proposal

FieldTrip BIDS Matlab DWI ECG Python fNIRS ECOG TMS PET TDCS EEG MRI fMRI MEG

Physiological Signal Classification

Julia physiology Matlab R ECG Python

Physiopy: open development solutions for physiology in MRI

documentation physiology BIDS Python documentation MRI fMRI

Tools for MRI diffusion in human and non-human primates

There are many pipelines for processing diffusion MRI data (diffuse, qsiprep, mrtrix pipelines, FSL pipelines, dipy, Designer, …

 Project URL Git level: 0 none containerization documentation MR methodologies shell scripting pipeline development Freesurfer Jupyter tractography data visualisation Skills: expert coding methods DIPY MRtrix FSL DWI reproducible scientific methods Python Unix command line Git level: 1 commit push documentation connectome Nipype diffusion MRI visualisation

Universal data load for neural networks

MNE Python Nipype EEG MRI fMRI

Using Explainable Artificial Intelligence (XAI) to create a real-time closed-loop stimulation

  • What are you doing, for whom, and why?

Like similar work in other fields (e.g., computer vision, ML, etc.) on established …

 Project URL Git level: 0 none documentation pipeline development data visualisation Python documentation EEG MRI behavioral fMRI visualisation

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 2021 Project Gallery, please follow these steps:

  1. Register with an event listed in the Brainhack Global 2021 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 2021 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 2021 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.