== MEG MasterClass ==
The MEG Master Class tutorial series combines theoretical discussions with practical sessions on many aspects of MEG data analysis using SPM. Working from the [javascript:void(0);/*1240485543728*/ SPM example pathway ]each processing step is split into a small two hour practical. See links below for individual session notes and worksheets.

Please note that these sessions do not cover max filtering of the data set - this can be done as shown at the start of the SPM example pathway script and more details on the processing options are available here.

=== Session 1. Pre-processing ===
 * Importing raw FIF data Into Matlab.
 * Spliting in Mags, Grads and EEG data sets.
 * Reading the Trigger line and extracting the triggers and response codes (also see here).
 * Epoching.
 * Resynching to a new starting point.
 * Filtering.
 * Artefact rejection.
 * Contrasts.
 * Grand averaging.
 * Inspecting the results - topographies, line plots, meg_viewdata.
=== Session 2. 3D Sensor SPM's ===
3D sensor SPMs can be used for a sensor level analysis and as a guide to establish critical time windows to analyse further.

 * Generating the files.
 * Computing the anova.
 * Interpreting the results.
=== Session 3. Catch up session - THEORETICAL ===
 * When to take the RMS.
 * How are bad channels dealt with.
 * Things to be careful about when you have very uneven trial numbers across conditions (e.g. in an MMN expt).
=== Session 4. Using ICA for artefact rejection ===
 * How and why to use ICA.
 * Implementing ICA to extract eye blinks, eye movements and cardiac signals.
=== Session 5. Source reconstuction - THEORETICAL ===
 * Forward model, choice of inverse solution and associated parameters.