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| Installed on Linux Boxes. All Graphical tools must be used in the computing room on lws001, lws002, lws004, lws005, lws006 or using a vncserver.glx session (see http://imaging.mrc-cbu.cam.ac.uk/imaging/ImagingComputingDevelopments). |
Installed on Linux Boxes. All Graphical tools must be used in the computing room on lws001, lws002, lws004, lws005, lws006 or using a vncserver.glx session (see http://imaging.mrc-cbu.cam.ac.uk/imaging/ImagingComputingDevelopments). |
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| == CBU Data Screening Tool == Matlab utilities for quality control of your data prior to further processing. More here: DataScreeiningTool |
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| == Applying linear regressors to EEG/MEG data == Matlab tools for applying multiple linear regression to EEG/MEG data. More here: LinearRegression You may want to follow the following AnalysisPath |
== Multiple Linear Regression of EEG/MEG data == Matlab tools for applying multiple linear regression to EEG/MEG data. More here: LinearRegression You may want to follow the following AnalysisPath |
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| == Data Screening Tool == Matlab utilities for quality control of your data prior to further processing. More here: DataScreeiningTool |
MEG Freeware Packages
There are many available; here are some (some comments may reflect ignorance!)
SPM5
Advantages:
- Much experience at CBU, integrated with fMRI analysis
- Matlab, so readable and extendable
- Advanced statistical methods (e.g, for multiple comparisons across space or time),
- Novel variants of the L2-norm approach to the inverse problem
- Group-based analysis (eg in MNI/Talairach space).
Disadvantages:
- Slow graphics
- No ECD for MEG (yet)
Official website: http://www.fil.ion.ucl.ac.uk/spm/
Currently installed on all Linux Boxes (lowest load box selected by spm 5 eeg at linux prompt)
For more details, see here SpmAnalysis
MNE (Minimum Norm Estimates)
Advantages:
- Advanced distributed solution methods (by Matti Hämäläinen, a long-standing expert with strong links to Neuromag)
- Excellent, fast graphics
Linked with Free Surfer http://imaging.mrc-cbu.cam.ac.uk/imaging/FreesurferInformation (advanced software for MRI segmentation, extraction of cortical surfaces, and inflation/normalisation)
- Matlab Toolbox, for exporting and importing data
Disadvantages:
- Compiled code, so difficult to extend
- No ECD for MEG (yet; can visualize xfit ECD)
Official website: http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/sofMNE.php
Installed on Linux Boxes. All Graphical tools must be used in the computing room on lws001, lws002, lws004, lws005, lws006 or using a vncserver.glx session (see http://imaging.mrc-cbu.cam.ac.uk/imaging/ImagingComputingDevelopments).
To do the tutorial use mne_tutorial instead of mne_setup_2.5
Multiple Linear Regression of EEG/MEG data
Matlab tools for applying multiple linear regression to EEG/MEG data. More here: LinearRegression You may want to follow the following AnalysisPath
FieldTrip
Advantages:
- Strong in oscillatory analysis (time-frequency, coherence) and beamformers (eg DICS)
- In Matlab, so easily readable and extendable
Official website: http://www.ru.nl/fcdonders/fieldtrip/
Data Screening Tool
Matlab utilities for quality control of your data prior to further processing. More here: DataScreeiningTool
Yet Others
FIFFACCESS for simply reading FIF data into Matlab, more here: ReadingDataInMatlab
EEGLAB (good for ICA) http://www.sccn.ucsd.edu/eeglab/
Brainstorm (good for forward models) http://neuroimage.usc.edu/brainstorm/
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