tedana is a Python package for denoising multi-echo fMRI data. One project goal is to implement a range of denoising methods (in addition to two ICA-based decision trees under current development), so that users may choose for themselves which to use. At the hackathon, we would like to discuss a decision tree created by @cjl2007 (currently implemented in MATLAB here) and to implement a version of it in Python within tedana.
Skills required to participate
Those with an interest in (and preferably experience with) multi-echo fMRI or decomposition-based denoising (e.g., AROMA) would be able to contribute at a conceptual level. Those with Python coding skills can contribute to the actual implementation of the methods.
Integration
This project will include both a discussion of denoising strategies to apply within tedana and a hacking portion in which we hope to implement one such strategy in Python within tedana. Neuroimagers and computational scientists may be able to contribute to either part of the project.
Extending denoising strategies in tedana
Project Description
tedana is a Python package for denoising multi-echo fMRI data. One project goal is to implement a range of denoising methods (in addition to two ICA-based decision trees under current development), so that users may choose for themselves which to use. At the hackathon, we would like to discuss a decision tree created by @cjl2007 (currently implemented in MATLAB here) and to implement a version of it in Python within tedana.
Skills required to participate
Those with an interest in (and preferably experience with) multi-echo fMRI or decomposition-based denoising (e.g., AROMA) would be able to contribute at a conceptual level. Those with Python coding skills can contribute to the actual implementation of the methods.
Integration
This project will include both a discussion of denoising strategies to apply within tedana and a hacking portion in which we hope to implement one such strategy in Python within tedana. Neuroimagers and computational scientists may be able to contribute to either part of the project.
Preparation material
Here is a walkthrough of tedana’s pipeline.
Link to your GitHub repo
The tedana repository with README and contributing guidelines.
Communication