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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. | 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);/*1240485681043*/ SPM example pathway] each processing step is split into a small two hour practical. See links below for individual session notes and worksheets. |
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);/*1240485681043*/ 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.