A python package for Paradigm Free Mapping (3dPFM and 3dMEPFM).

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  • License: GNU Library or Lesser General Public License (LGPL) (GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software...)
  • Author: Eneko Uruñuela
  • Requires: Python >=3.8
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pySPFM

The Python version of AFNI's 3dPFM and 3dMEPFM with some extra features like the addition of a spatial regularization similar to the one used by Total Activation.

Latest Version PyPI - Python Version DOI License CircleCI Documentation Status codecov Code style: black pre-commit

References

  • Caballero-Gaudes, C., Moia, S., Panwar, P., Bandettini, P. A., & Gonzalez-Castillo, J. (2019). A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping. NeuroImage, 202, 116081–116081. https://doi.org/10.1016/j.neuroimage.2019.116081
  • Caballero Gaudes, C., Petridou, N., Francis, S. T., Dryden, I. L., & Gowland, P. A. (2013). Paradigm free mapping with sparse regression automatically detects single-trial functional magnetic resonance imaging blood oxygenation level dependent responses. Human Brain Mapping. https://doi.org/10.1002/hbm.21452
  • Gaudes, C. C., Ville, D. V. D., Petridou, N., Lazeyras, F., & Gowland, P. (2011). Paradigm-free mapping with morphological component analysis: Getting most out of fMRI data. Wavelets and Sparsity XIV, 8138, 81381K. https://doi.org/10.1117/12.893920
  • Karahanoǧlu, F. I., Caballero-Gaudes, C., Lazeyras, F., & Van De Ville, D. (2013). Total activation: FMRI deconvolution through spatio-temporal regularization. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.01.067
  • Uruñuela, E., Bolton, T. A. W., Van De Ville, D., & Caballero-Gaudes, C. (2021). Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at Work. ArXiv:2107.12026 [q-Bio]. http://arxiv.org/abs/2107.12026

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