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<!DOCTYPE html>
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<div class="section" id="documentation">
<h1>Documentation<a class="headerlink" href="#documentation" title="Permalink to this headline">¶</a></h1>
<p>PyHRF is a set of tools for within-subject fMRI data analysis, focused on the
characterization of the <strong>hemodynamics</strong>.</p>
<p>Within the chain of fMRI data processing, these tools provide alternatives to
the classical within-subject GLM fitting procedure. The inputs are preprocessed
images (except spatial smoothing) and the outputs are the contrast maps and the
HRF estimates.</p>
<p>The package is mainly written in Python and provides the implementation of the
two following methods:</p>
<ul class="simple">
<li><strong>The joint-detection estimation (JDE)</strong> approach, which divides the brain
into functionally homogeneous regions and provides one HRF estimate per
region as well as response levels specific to each voxel and each
experimental condition. This method embeds a temporal regularization on the
estimated HRFs and an adaptive spatial regularization on the response levels.</li>
<li><strong>The Regularized Finite Impulse Response (RFIR)</strong> approach, which provides
HRF estimates for each voxel and experimental conditions. This method embeds
a temporal regularization on the HRF shapes, but proceeds independently
across voxels (no spatial model). See <a class="reference internal" href="introduction.html#introduction"><span class="std std-ref">Introduction</span></a> for a more detailed
overview.</li>
</ul>
<p>To cite PyHRF and get a comprehensive description, please refer to:</p>
<blockquote>
<div>Vincent, T., Badillo, S., Risser, L., Chaari, L., Bakhous, C., Forbes, F., &
Ciuciu, P. (2014). <em>Flexible multivariate hemodynamics fMRI data analyses and
simulations with PyHRF</em>. Frontiers in Neuroscience, 8. <a class="reference external" href="https://doi.org/10.3389/fnins.2014.00067">https://doi.org/10.3389/fnins.2014.00067</a></div></blockquote>
<div class="section" id="site-content">
<h2>Site content<a class="headerlink" href="#site-content" title="Permalink to this headline">¶</a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="introduction.html">Introduction</a><ul>
<li class="toctree-l2"><a class="reference internal" href="introduction.html#scientific-issues">Scientific issues</a></li>
<li class="toctree-l2"><a class="reference internal" href="introduction.html#package-overview">Package overview</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="installation.html">Installation</a><ul>
<li class="toctree-l2"><a class="reference internal" href="installation.html#requirements-dependencies">Requirements / Dependencies</a></li>
<li class="toctree-l2"><a class="reference internal" href="installation.html#linux-installation">Linux Installation</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="manual.html">Manual</a><ul>
<li class="toctree-l2"><a class="reference internal" href="manual/vem_analysis.html">1. Variational (VEM) analysis</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/visualizer.html">2. Visualization tools</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/paradigm.html">3. File format specification</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/multiprocessing_computation.html">4. Multicore computing</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/commands.html">5. PyHRF commands</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/parcellation_mask.html">6. Parcellation mask</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/pyhrf_configuration.html">7. Configuration</a></li>
<li class="toctree-l2"><a class="reference internal" href="manual/developer.html">8. Developer documentation</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference external" href="http://pyhrf.readthedocs.io">API Reference</a></li>
<li class="toctree-l1"><a class="reference external" href="http://pyhrf.readthedocs.io/en/latest/changelog.html">Changelog</a></li>
</ul>
</div>
</div>
<div class="section" id="licence-and-authors">
<h2>Licence and authors<a class="headerlink" href="#licence-and-authors" title="Permalink to this headline">¶</a></h2>
<p>PyHRF is currently under the <a class="reference external" href="http://www.cecill.info">CeCILL licence version 2</a>.
Originally developed by the former <a class="reference external" href="http://www.lnao.fr">LNAO</a> (Neurospin, CEA),
pyHRF is now entering (since Sep 2014) in a new era under the joint
collaboration of the the <a class="reference external" href="http://parietal.inria.fr/">Parietal team</a> (Inria Saclay)
and the <a class="reference external" href="http://mistis.inrialpes.fr/">MISTIS team</a> (Inria Rhones-Alpes).</p>
<p>People who have significantly contributed to the development are
(by chronological order): Thomas Vincent<sup>(1,3)</sup>,
Philippe Ciuciu<sup>(1,2)</sup>, Lotfi Chaari<sup>(3)</sup>,
Solveig Badillo<sup>(1,2)</sup>, Christine Bakhous<sup>(3)</sup>,
Aina Frau-Pascual<sup>(2,3)</sup>, Thomas Perret<sup>(3)</sup>, and
Jaime Arias<sup>(3)</sup>.</p>
<ol class="arabic simple">
<li>CEA/DRF/I2BM/NeuroSpin, Gif-Sur-Yvette, France</li>
<li>Inria/CEA Parietal, Gif-Sur-Yvette, France</li>
<li>Inria, MISTIS, Grenoble, France</li>
</ol>
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