.. _sphx_glr_auto_workshop_01_meg:




FACE dataset
^^^^^^^^^^^^

These examples demonstrate how to process 1 participant of the |FACE| dataset from |Wakeman_Henson|. The data consist of simultaneous MEG/EEG recordings
from 19 healthy participants performing a visual recognition task. Subjects were presented images of famous, unfamiliar and scrambled faces.
Each subject participated in 6 runs, each 7.5 min in duration.

.. |FACE| raw:: html
        
        <a href="https://openneuro.org/datasets/ds000117/versions/1.0.4" target="_blank">FACE</a>

.. |Wakeman_Henson| raw:: html
        
        <a href="https://www.nature.com/articles/sdata20151" target="_blank">Wakeman and
 Henson (2015)</a>

Here, we focus only on MEG data and use :func:`~ephypype.pipelines.create_pipeline_preproc_meeg` to preprocess the MEG raw data and :func:`~ephypype.pipelines.create_pipeline_source_reconstruction` to perform source reconstruction of time-locked event-related fields.



.. raw:: html

    <div class="sphx-glr-thumbnails">


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This workflow runs the `Nipype &lt;http://nipype.readthedocs.io/en/latest/#&gt;`_ Interface wrapping ...">

.. only:: html

  .. image:: /auto_workshop/01_meg/images/thumb/sphx_glr_01-run-smri_reconall_thumb.png
    :alt: 01. Freesurfer anatomical pipeline

  :ref:`sphx_glr_auto_workshop_01_meg_01-run-smri_reconall.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">01. Freesurfer anatomical pipeline</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="02. Preprocess MEG data">

.. only:: html

  .. image:: /auto_workshop/01_meg/images/thumb/sphx_glr_plot_01_meg_preprocessing_thumb.png
    :alt: 02. Preprocess MEG data

  :ref:`sphx_glr_auto_workshop_01_meg_plot_01_meg_preprocessing.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">02. Preprocess MEG data</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="The first node of the workflow (:ref:`concat_event`) **extracts the events** from stimulus chan...">

.. only:: html

  .. image:: /auto_workshop/01_meg/images/thumb/sphx_glr_plot_02_events_inverse_stc_thumb.png
    :alt: 03. Compute inverse solution

  :ref:`sphx_glr_auto_workshop_01_meg_plot_02_events_inverse_stc.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">03. Compute inverse solution</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Group average of dSPM solutions obtained by plot_events_inverse for the contrast between both t...">

.. only:: html

  .. image:: /auto_workshop/01_meg/images/thumb/sphx_glr_plot_03_stc_thumb.png
    :alt: 04. Plot contrast

  :ref:`sphx_glr_auto_workshop_01_meg_plot_03_stc.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">04. Plot contrast</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="04. Preprocess MEG data and compute inverse solution">

.. only:: html

  .. image:: /auto_workshop/01_meg/images/thumb/sphx_glr_plot_04-preprocessing_inverse_thumb.png
    :alt: 04. Preprocess MEG data and compute inverse solution

  :ref:`sphx_glr_auto_workshop_01_meg_plot_04-preprocessing_inverse.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">04. Preprocess MEG data and compute inverse solution</div>
    </div>


.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_workshop/01_meg/01-run-smri_reconall
   /auto_workshop/01_meg/plot_01_meg_preprocessing
   /auto_workshop/01_meg/plot_02_events_inverse_stc
   /auto_workshop/01_meg/plot_03_stc
   /auto_workshop/01_meg/plot_04-preprocessing_inverse