Citing ConfUSIus¶
If you use ConfUSIus in your research, please cite it using the following reference:
Le Meur-Diebolt, S., & Cybis Pereira, F. (2026). ConfUSIus (v0.3.0). Zenodo. https://doi.org/10.5281/zenodo.18611124
Or in BibTeX format:
@software{confusius,
author = {Le Meur-Diebolt, Samuel and Cybis Pereira, Felipe},
title = {ConfUSIus},
year = {2026},
publisher = {Zenodo},
version = {v0.3.0},
doi = {10.5281/zenodo.18611124},
url = {https://doi.org/10.5281/zenodo.18611124}
}
Third-Party Libraries¶
ConfUSIus stands on the shoulders of giants. It is built on top of many excellent open-source projects, without which it could not exist. If you use the features listed below, please consider citing the corresponding projects to support these efforts.
BrainGlobe¶
The atlas module uses the BrainGlobe Atlas
API to interface with neuroanatomical atlases. If you use the
atlas features in your research, please also cite BrainGlobe:
Claudi, F., Petrucco, L., Tyson, A. L., Branco, T., Margrie, T. W., & Portugues, R. (2020). BrainGlobe Atlas API: a common interface for neuroanatomical atlases. Journal of Open Source Software, 5(54), 2668. https://doi.org/10.21105/joss.02668
Or in BibTeX format:
@article{brainglobe,
author = {Claudi, Federico and Petrucco, Luigi and Tyson, Adam L. and
Branco, Tiago and Margrie, Troy W. and Portugues, Ruben},
title = {{BrainGlobe} {Atlas} {API}: a common interface for neuroanatomical atlases},
journal = {Journal of Open Source Software},
year = {2020},
volume = {5},
number = {54},
pages = {2668},
doi = {10.21105/joss.02668},
url = {https://doi.org/10.21105/joss.02668}
}
Napari¶
The ConfUSIus GUI is built on top of napari, a powerful multi-dimensional image viewer for Python. If you use the ConfUSIus GUI in your research, please also cite napari:
napari contributors (2019). napari: a multi-dimensional image viewer for Python. Zenodo. https://doi.org/10.5281/zenodo.3555620
Or in BibTeX format:
@software{napari,
author = {{napari contributors}},
title = {napari: a multi-dimensional image viewer for {Python}},
year = {2019},
publisher = {Zenodo},
doi = {10.5281/zenodo.3555620},
url = {https://doi.org/10.5281/zenodo.3555620}
}
Nilearn¶
The signal, glm, and
connectivity modules contain code derived from
Nilearn. If you use these modules in your research, please
also cite Nilearn:
Nilearn contributors (2023). Nilearn. Zenodo. https://doi.org/10.5281/zenodo.8397156
Or in BibTeX format:
@software{nilearn,
author = {{Nilearn contributors}},
title = {Nilearn},
year = {2023},
publisher = {Zenodo},
doi = {10.5281/zenodo.8397156},
url = {https://doi.org/10.5281/zenodo.8397156}
}
SimpleITK¶
The registration module uses
SimpleITK for image registration and resampling. If you use the
registration features in your research, please also cite SimpleITK:
Beare, R., Lowekamp, B., & Yaniv, Z. (2018). Image Segmentation, Registration and Characterization in R with SimpleITK. Journal of Statistical Software, 86(8), 1–35. https://doi.org/10.18637/jss.v086.i08
Or in BibTeX format:
@article{simpleitk,
author = {Beare, Richard and Lowekamp, Bradley and Yaniv, Ziv},
title = {Image Segmentation, Registration and Characterization in {R} with {SimpleITK}},
journal = {Journal of Statistical Software},
year = {2018},
volume = {86},
number = {8},
pages = {1--35},
doi = {10.18637/jss.v086.i08},
url = {https://doi.org/10.18637/jss.v086.i08}
}
Datasets¶
Nunez-Elizalde et al. (2022)¶
The fetch_nunez_elizalde_2022
function provides an fUSI-BIDS conversion of this dataset. If you use it, please cite:
Nunez-Elizalde, A. O., Krumin, M., Reddy, C. B., Montaldo, G., Urban, A., Harris, K. D., & Carandini, M. (2022). Neural correlates of blood flow measured by ultrasound. Neuron, 110(10), 1631–1640.e4. https://doi.org/10.1016/j.neuron.2022.02.012
Or in BibTeX format:
@article{nunez-elizalde_neural_2022,
title = {Neural correlates of blood flow measured by ultrasound},
volume = {110},
issn = {08966273},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0896627322001775},
doi = {10.1016/j.neuron.2022.02.012},
language = {en},
number = {10},
journal = {Neuron},
author = {Nunez-Elizalde, Anwar O. and Krumin, Michael and Reddy, Charu Bai and
Montaldo, Gabriel and Urban, Alan and Harris, Kenneth D. and Carandini, Matteo},
month = may,
year = {2022},
pages = {1631--1640.e4},
}
License: CC BY 4.0.
Cybis Pereira et al. (2026)¶
The fetch_cybis_pereira_2026
function provides an fUSI-BIDS conversion of this dataset. If you use it, please cite:
Cybis Pereira, F., Castedo, S. H., Meur-Diebolt, S. L., Ialy-Radio, N., Bhattacharya, S., Ferrier, J., Osmanski, B. F., Cocco, S., Monasson, R., Pezet, S., & Tanter, M. (2026). A vascular code for speed in the spatial navigation system. Cell Reports, 45(1). https://doi.org/10.1016/j.celrep.2025.116791
Or in BibTeX format:
@article{cybispereiraVascularCodeSpeed2026,
title = {A Vascular Code for Speed in the Spatial Navigation System},
author = {Cybis Pereira, Felipe and Castedo, Sebastian H. and {Meur-Diebolt}, Samuel Le and {Ialy-Radio}, Nathalie and Bhattacharya, Soumee and Ferrier, Jeremy and Osmanski, Bruno F{\'e}lix and Cocco, Simona and Monasson, Remi and Pezet, Sophie and Tanter, Micka{\"e}l},
year = 2026,
month = jan,
journal = {Cell Reports},
volume = {45},
number = {1},
publisher = {Elsevier},
issn = {2211-1247},
doi = {10.1016/j.celrep.2025.116791},
urldate = {2025-12-30},
langid = {english},
keywords = {animal speed,cerebral blood volume,continuous attractor network,CP: neuroscience,freely moving,functional ultrasound imaging,hippocampus,locomotion,path integration,spatial navigation},
}
License: CC BY 4.0.
Templates¶
Huang et al. (2025)¶
The fetch_template_huang_2025
function provides a vascular mouse template derived from OpenfUSAnalyzer. If you use
this template in your research, please cite:
Huang, Y.-A., Lambert, T., Verbeyst, D., Fitzgerald, N. E., Grillet, M., Brunner, C., Montaldo, G., Vanduffel, W., & Urban, A. (2025). OfUSA: OpenfUS Analyzer, a versatile open-source framework for the analysis and visualization of functional ultrasound imaging data across animal models. bioRxiv. https://doi.org/10.1101/2025.09.16.676515
Or in BibTeX format:
@misc{huang_ofusa:_2025,
title = {OfUSA: OpenfUS Analyzer, a versatile open-source framework for the analysis and
visualization of functional ultrasound imaging data across animal models},
copyright = {http://creativecommons.org/licenses/by-nc/4.0/},
shorttitle = {OfUSA},
url = {http://biorxiv.org/lookup/doi/10.1101/2025.09.16.676515},
doi = {10.1101/2025.09.16.676515},
language = {en},
author = {Huang, Yun-An and Lambert, Théo and Verbeyst, Damon and Fitzgerald, Nora Eilis and
Grillet, Micheline and Brunner, Clément and Montaldo, Gabriel and
Vanduffel, Wim and Urban, Alan},
month = sep,
year = {2025},
}
License: CC BY-NC-SA 4.0.
Pepe, Mariani et al. (2026)¶
The fetch_template_pepe_mariani_2026
function provides a mouse fUSI template derived from Pepe, Mariani et al. (2026). If you use
this template in your research, please also cite the corresponding article:
Pepe, C., Mariani, J.-C., Urosevic, M., Gini, S., Stuefer, A., Ricci, F., Galbusera, A., Iurilli, G., & Gozzi, A. (2026). Structural and dynamic embedding of the mouse functional connectome revealed by functional ultrasound imaging (fUSI). bioRxiv. https://doi.org/10.64898/2026.02.05.704055
Or in BibTeX format:
@article{pepe2026fusi,
author = {Pepe, Chiara and Mariani, Jean-Charles and Urosevic, Mila and Gini, Silvia and
Stuefer, Alexia and Ricci, Fabio and Galbusera, Alberto and Iurilli, Giuliano and
Gozzi, Alessandro},
title = {Structural and dynamic embedding of the mouse functional connectome revealed by
functional ultrasound imaging ({fUSI})},
journal = {bioRxiv},
year = {2026},
publisher = {Cold Spring Harbor Laboratory},
doi = {10.64898/2026.02.05.704055},
url = {https://doi.org/10.64898/2026.02.05.704055}
}
License: CC BY 4.0.