Title: NeuroDesk - A flexible, scalable, and easy to use data analysis environment for reproducible neuroimaging
Project lead: Steffen Bollmann, @sbollmann_mri
Project collaborators: Aswin Narayanan Oren Civier @OrenCivier Christopher Nolan @cnolanAU Jakub Kaczmarzyk @JakubKaczmarzyk Martin Grignard @grignard_martin MEJ Campbell @MegaEJ_Campbell Thom Shaw @thomcat992 Tom Johnstone @itjohnstone
Registered Brainhack Global 2020 Event: https://brainhack-ankara.github.io/
Project Description: Installing neuroimaging software is hard. Running neuroimaging software on Windows, Mac and HPCs is difficult. Moving analyses between platforms is a pain. Reproducing an analysis stack on a different computer is almost impossible. We are attempting to help with this and we are building an analysis environment for Neuroimaging with the goal to make it very easy to run a variety of neuroimaging tools on any operating system. The project aims to make reproducible and scalable neuroimaging analysis as easy as possible. With this we are not just helping beginners to get access to the tools they need without waiting for their administrators to compile them, but we are also aiming to build good habits by making it easy to document and control software versions, and we enable power users to quickly scale up their analyses and run identical software on a variety of compute platforms.
All skill levels can work on our project, from improving the documentation, testing or adding their favourite tool, working on the underlying container infrastructure or developing CI and CD to make our workflows as robust and easy as possible.
Link to project repository/sources: https://github.com/NeuroDesk
Goals for Brainhack Global 2020: Easy:
Medium:
Hard:
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Project labels
Type of project: #coding_methods, #data_management, #documentation, #method_development, #pipeline_development, tutorial_recording, visualization
Project development status: 0_concept_no_content, 1_basic structure, #2_releases_existing
Topic of the projet: Bayesian_approaches, causality, connectome, data_visualisation, deep_learning, diffusion, diversity_inclusivity_equality, EEG_EventRelatedResponseModelling, EEG_source_modelling, Granger_causality, hypothesis_testing, ICA, information_theory, machine_learning, #MR_methodologies, neural_decoding, neural_encoding, neural_networks, PCA, physiology, reinforcement_learning, #reproducible_scientific_methods, single_neuron_models, statistical_modelling, systems_neuroscience, tractography
Tools used in the project: #AFNI, #ANTs, #BIDS, Brainstorm, CPAC, #Datalad, DIPY, FieldTrip, #fMRIPrep, #Freesurfer, #FSL, Jupyter, MNE, #MRtrix, #Nipype, NWB, #SPM
Tools skill level required to enter the project (more than one possible): #comfortable, #expert, #familiar, #no_skills_required
Programming language used in the project: #no_programming_involved, C++, #containerization, #documentation, Java, Julia, Matlab, #Python, R, #shell_scripting, #Unix_command_line, #Web, #workflows
Modalities involved in the project (if any): behavioral, #DWI, ECG, ECOG, #EEG, eye_tracking, #fMRI, fNIRS, #MEG, #MRI, PET, TDCS, TMS
Git skills reuired to enter the project (more than one possible): #0_no_git_skills, #1_commit_push, #2_branches_PRs, #3_continuous_integration
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