Hemodynamic Response Function (HRF) estimation from functional MRI data
Update March 2018: This package is provided with the hope that it is useful for reproducing the experiments in the papers mentioned below. It is however not actively maintained
This is a Python package that implements several methods for the joint estimation of HRF and activation patterns (aka beta-map) from fMRI (BOLD) signal.
If you use this software, please cite (at least) one of the following papers
"Data-driven HRF estimation for encoding and decoding models", Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion and Alexandre Gramfort. URL: http://hal.inria.fr/hal-00952554/en
"HRF estimation improves sensitivity of fMRI encoding and decoding models", Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion and Alexandre Gramfort. URL: http://hal.inria.fr/hal-00821946/en
.. image:: https://raw.github.com/fabianp/hrf_estimation/master/doc/estimation_natural_images.png :target: http://nbviewer.ipython.org/github/fabianp/hrf_estimation/blob/master/examples/hrf_estimation%20example.ipynb
Installation
hrf_estimation is a pure Python package and can be installed through the Python Package Index (PYPI):
.. code:: bash
pip install -U hrf_estimation
You can also download the source code from the PYPI website <https://pypi.python.org/pypi/hrf_estimation>_
or get the latest sources from github <http://github.com/fabianp/hrf_estimation/>_
Documentation
Documentation and function reference is available at https://pythonhosted.org/hrf_estimation/
Development
The newest version can alway be grabbed from the git repository <http://github.com/fabianp/hrf_estimation>_. Feel free to submit
issues or patches.
Authors
Fabian Pedregosa <http://fa.bianp.net>_ [email protected]
Michael Eickenberg [email protected]
Thanks to
Yaroslav Halchenko, Bug reports