tedana: TE Dependent ANAlysis
tedana)is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI) data.
tedana originally came about as a part of the ME-ICA pipeline, although it has since diverged.
An important distinction is that while the ME-ICA pipeline originally performed both pre-processing and TE-dependent analysis of multi-echo fMRI data,
tedana now assumes that you’re working with data which has been previously preprocessed.
For a summary of multi-echo fMRI, which is the imaging technique
tedana builds on,
visit Multi-echo fMRI.
For a detailed procedure of how
tedana analyzes the data from multi-echo fMRI,
visit Processing pipeline details.
When using tedana, please include the following citations:
tedana This link is for the most recent version of the code and that page has links to DOIs for older versions. To support reproducibility, please cite the version you used: https://doi.org/10.5281/zenodo.1250561
2. DuPre, E. M., Salo, T., Ahmed, Z., Bandettini, P. A., Bottenhorn, K. L., Caballero-Gaudes, C., Dowdle, L. T., Gonzalez-Castillo, J., Heunis, S., Kundu, P., Laird, A. R., Markello, R., Markiewicz, C. J., Moia, S., Staden, I., Teves, J. B., Uruñuela, E., Vaziri-Pashkam, M., Whitaker, K., & Handwerker, D. A. (2021). TE-dependent analysis of multi-echo fMRI with tedana. Journal of Open Source Software, 6(66), 3669. doi:10.21105/joss.03669.
3. Kundu, P., Inati, S. J., Evans, J. W., Luh, W. M., & Bandettini, P. A. (2011). Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI. NeuroImage, 60, 1759-1770.
4. Kundu, P., Brenowitz, N. D., Voon, V., Worbe, Y., Vértes, P. E., Inati, S. J., Saad, Z. S., Bandettini, P. A., & Bullmore, E. T. (2013). Integrated strategy for improving functional connectivity mapping using multiecho fMRI. Proceedings of the National Academy of Sciences, 110, 16187-16192.
Alternatively, you can automatically compile relevant citations by running your
tedana code with duecredit. For example, if you plan to run a script using
tedana (in this case,
python -m duecredit tedana_script.py
You can also learn more about why citing software is important.
tedana is licensed under GNU Lesser General Public License version 2.1.
- About multi-echo fMRI
- Using tedana from the command line
- tedana’s denoising approach
- Outputs of tedana
- [tedana] How do I use tedana with fMRIPrepped data?
- [tedana] ICA has failed to converge.
- [tedana] I think that some BOLD ICA components have been misclassified as noise.
- [tedana] Why isn’t v3.2 of the component selection algorithm supported in
- [tedana] What is the warning about
- [ME-fMRI] Does multi-echo fMRI require more radio frequency pulses?
- [ME-fMRI] Can I combine multiband (simultaneous multislice) with multi-echo fMRI?
- Support and communication
- Contributing to tedana
- The tedana roadmap
tedana.workflows: Common workflows
tedana.decay: Modeling signal decay across echoes
tedana.combine: Combining time series across echoes
tedana.decomposition: Data decomposition
tedana.metrics: Computing TE-dependence metrics
tedana.selection: Component selection
tedana.gscontrol: Global signal control
tedana.io: Reading and writing data
tedana.stats: Statistical functions
tedana.utils: Utility functions