tedana: TE Dependent ANAlysis
de``pendent ``ana``lysis (``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](https://github.com/me-ica/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 Available from: 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