Dear colleagues,

We are happy to advertise the new Statistical Parametric Mapping
MEG/EEG course presented by the Wellcome Trust Centre for
Neuroimaging. The course will take place on Monday 10th May –
Wednesday 12th May 2010 at the Wellcome Trust Centre for Neuroimaging
in London.

This newly established course will present instruction on the analysis
of EEG and MEG data.  The first two days will combine theoretical
presentations with practical demonstrations of the different data
analysis methods implemented in SPM.  On the last day participants
will have the opportunity to work on SPM tutorial data sets under the
supervision of the course faculty.  We also invite students to bring
their own data for analysis.  The course will cover (1) data
pre-processing, (2) statistical analysis of sensor-space maps using
GLMs and Random Field theory, (3) source reconstruction and (4)
Dynamic Causal Modelling for EEG/MEG. The course will be followed by
the long-established three-day course on ‘SPM for fMRI’ so it is
possible to attend both courses.

The course is suitable for beginners and more advanced users. We
advise students to gain at least some minimal familiarity with the
methodology, for example, from reading introductory articles available
from the SPM web page or by following data analysis examples in the
SPM manual.

The detailed schedule and booking forms can be found at
http://www.ion.ucl.ac.uk/articles/events/SPM . For further details and
registration please contact Jean Reynolds ([log in to unmask]).


With best wishes,

Vladimir Litvak Ph.D.
Senior Research Associate
Wellcome Trust Centre for Neuroimaging
--------------------------------------------------------------------------------------------------

SPM (http://www.fil.ion.ucl.ac.uk/spm/) is a free and open-source
Matlab toolbox in which many widely used methods for the analysis of
PET and fMRI data; and for computational neuroanatomy were originally
developed. In the recent years SPM has been extended to include M/EEG
analysis and, in the most recent version, SPM8, extensive changes have
made the software more stable, generic and accessible to researchers
with data from wide range of recording systems.

In addition to standard M/EEG pre-processing we presently offer three
main analysis tools: (1) statistical analysis of scalp maps,
time-frequency images and volumetric 3D source reconstruction images
based on the general linear model with correction for multiple
comparisons using random field theory (2) Bayesian M/EEG source
reconstruction including support for group studies, simultaneous EEG
and MEG and fMRI priors (3) Dynamic Causal Modelling (DCM) an approach
combining neural modelling with data analysis for which there are
several variants dealing with evoked responses, steady state responses
(power spectra and cross-spectra), induced responses and phase
coupling.

SPM8 is integrated with the Fieldtrip toolbox
(http://www.ru.nl/neuroimaging/fieldtrip/) making it possible for
users to combine a variety of standard analysis methods with the new
methods implemented in SPM and build custom analysis tools using
powerful GUI and batching tools.