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fMRIPrep/rodents: Analysis-grade BOLD fMRI data of rats

This tool adapts fMRIPrep to the use-case of rodent preclinical imaging -- because MRI is some times done on species other than the homo sapiens. At the moment, only rats are fully-supported. However, the vision is to generalize the preprocessing to other rodents, starting with mice.

https://circleci.com/gh/nipreps/fmriprep-rodents/tree/master.svg?style=shield

About

Development was initiated by (soon-to-be) Dr. E. MacNicol in a research visit to the Poldrack lab at Stanford University. Currently, it is maintained by the NiPreps community.

https://github.com/oesteban/fmriprep/raw/38a63e9504ab67812b63813c5fe9af882109408e/docs/_static/fmriprep-workflow-all.png

fMRIPrep is a functional magnetic resonance imaging (fMRI) data preprocessing pipeline. fMRIPrep/rodents adapts the original pipeline to work on rodents. The software is designed to provide an easily accessible interface, and the pipeline is robust to variations in scan acquisition protocols. This is possible with the adoption of BIDS (Brain Imaging Data Structure), which allows the tool to implement such a design. In practice, fMRIPrep (and fMRIPrep/rodents) require minimal user input and provide interpretable, comprehensive visual reports. fMRIPrep/rodents performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skullstripping etc.) providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state fMRI, graph theory measures, surface or volume-based statistics, etc.

Note

fMRIPrep performs minimal preprocessing. Here we define 'minimal preprocessing' as motion correction, field unwarping, normalization, bias field correction, and brain extraction. See the workflows section of our documentation for more details.

The fMRIPrep/rodents pipeline uses a combination of tools from well-known neuroimaging packages, including FSL_, ANTs_, and AFNI_.

Principles

fMRIPrep is built around three principles:

  1. Robustness - The pipeline adapts the preprocessing steps depending on the input dataset and should provide results as good as possible independently of scanner make, scanning parameters or presence of additional correction scans (such as fieldmaps).
  2. Ease of use - Thanks to dependence on the BIDS standard, manual parameter input is reduced to a minimum, allowing the pipeline to run in an automatic fashion.
  3. "Glass box" philosophy - Automation should not mean that one should not visually inspect the results or understand the methods. Thus, fMRIPrep provides visual reports for each subject, detailing the accuracy of the most important processing steps. This, combined with the documentation, can help researchers to understand the process and decide which subjects should be kept for the group level analysis.

Limitations

We count as limitations those inherited from the upstream project, *fMRIPrep*, in addition to:

  1. Mice are not yet supported, although the infrastructure is all set for quickly extending the support. In particular, the processing of mice imaging will require the inclusion of a suitable mice template on the TemplateFlow Archive.

Acknowledgements

Please acknowledge this work using the citation boilerplate that fMRIPrep includes in the visual report generated for every subject processed.