tedana
Analysis of echo-time dependent fMRI data
Outline
- Introduction to multi-echo fMRI
- Multi-echo fMRI for noise removal
- tedana: the software
- tedana: the community
- Challenges developing tedana
- Contributing to tedana
Single-echo fMRI
What is multi-echo fMRI
Signal decay
Assuming a mono-exponential decay model:
s(x,t,TEk)=S0(x,t)e−R2∗(x,t)⋅TEk
Describing S0(t) and R2∗(t) in terms of relative changes w.r.t. their average values:
s(t,TEk)=sˉ(TEk)⋅(1+Sˉ0ΔS0(t))⋅e−ΔR2∗(t)⋅TEk
Signal percentage changes w.r.t. the mean of the signal:
y(t,TEk)=Δρ(t)−ΔR2∗(t)⋅TEk
Separating T2∗ and S0
Most common denoising approaches for multi-echo fMRI
Denoising to actively separate T2∗ and S0
- Based on ICA: ME-ICA 1,2 and tedana 3
- Multi-Echo Paradigm Free Mapping 4 (available in AFNI and pySPFM)
- Other methods
Denoising with ICA
- Fit signal decay
- Optimal combination of echoes
- PCA to remove thermal noise
- Decomposition into independent components (ICA)
- Classification of components into BOLD-like (accepted) and non BOLD-like (rejected)
- Denoising
Benefits of denoising with ICA
tedana: the software
Elizabeth DuPre started tedana in May 2018 to advance ME-ICA by Prantik Kundu
Approx. 20 contributors from various countries and institutions
Monthly developer calls, a periodic newsletter, active issue board & code updates
tedana: the software
Install:
pip install tedana
Use from the command line:
tedana -d echo_1.nii.gz echo_2.nii.gz echo_3.nii.gz echo_4.nii.gz -e 12 28 44 60 -
Or from a Python session:
from tedana import workflows
workflows.tedana_workflow(
data_files,
echo_times,
out_dir=out_dir,
mask=mask_file,
prefix="sub-04570_task-rest_space-scanner",
fittype="curvefit",
tedpca="mdl",
verbose=True,
)
tedana: the software
Check out the Juggling with data session on Thursday at 12:00 UTC for more on these.
tedana: the community
- tedana
- maPCA
- Rica
- Multi-echo Jupyter Book
- Curated lists of multi-echo posters from OHBM
- Other works-in-progress
tedana: the community
- tedana
- maPCA
- Rica
- Multi-echo Jupyter Book
- Curated lists of multi-echo posters from OHBM
- Other works-in-progress
tedana: the community
- tedana
- maPCA
- Rica
- Multi-echo Jupyter Book
- Curated lists of multi-echo posters from OHBM
- Other works-in-progress
tedana: the community
- tedana
- maPCA
- Rica
- Multi-echo Jupyter Book
- Curated lists of multi-echo posters from OHBM
- Other works-in-progress
tedana: the community
- tedana
- maPCA
- Rica
- Multi-echo Jupyter Book
- Curated lists of multi-echo posters from OHBM
- Other works-in-progress
tedana: the community
- tedana
- maPCA
- Rica
- Multi-echo Jupyter Book
- Curated lists of multi-echo posters from OHBM
- Other works-in-progress
Challenges developing tedana
Expertise required: software engineering, MRI physics, math/statistics, neuroscience, data visualization, project management, community management…
👉 No one in the team has all of these!
Challenges developing tedana
Neuroimaging grad students and postdocs are rarely software engineers, but their code needs to survive beyond their period of contribution
👉 Documentation and testing are very important
Challenges developing tedana
Too big for informal governance, but too small for most documented open source governance models
Leadership and Governance
- Improvements prompted & guided by Kirstie Whitaker
- Acknowledge contributors’ leadership & minimize administrative burden
- Grow community, strive for consensus, have a path for decision making
- Support openness in both code and decision making
- A steering committee for project-wide steering, and focused roles for code-focused tasks
- Code of conduct and enforcement policy (luckily, never used)
Contributing to tedana
- Code contributions
- New ideas for data processing and visualization
- Documentation & education
- Questions that can help us identify gaps in the code or documentation
- Sharing (or processing your own) datasets to help with validation and testing
- Join monthly call!
Discussions are open
Thursday at 12:00 UTC
Learn how to denoise your multi-echo fMRI data using tedana at the Juggling with data session at MRI Together
