[Eeglabnews] EEGLAB v5.01beta

[arno]

A major new release of the EEGLAB environment, version 5.01beta, is now
available at http://sccn.ucsd.edu/eeglab/. The new release includes a new
large set of functions (ICACLUST) for finding and manipulating clusters of
similar independent components of brainwave activity, allowing statistical
analysis of large EEG and MEG studies that include data from multiple
subjects, tasks, conditions, and/or subject groups. The release also
includes a large number of function enhancements and fixes. The book
length tutorial has also been revised for accuracy and readability

New features

EEGLAB v5.0b introduces a new supervening Matlab data structure, the
STUDY, which is saved to disk as an EEGLAB 'studyset.' EEGLAB studysets
organize any number of datasets indexed by subject, condition, session,
and subject group. The EEGLAB main menu has been expanded to include
operations performed directly on studies - loading, saving, etc.  

The first set of functions operating directly on studysets, implemented in
v5.0b, is a large set of functions for finding and manipulating clusters 
of similar independent data components across datasets comprising a study. 

DIPFIT2 by Robert Oostenveld and Arnaud Delorme. DIPFIT2 performs component
dipole modeling on a boundary element model (BEM) of a standard (MNI) head. 
Dipole coordinates are translated to Tailairach coordinates for use with 
Tailairach atlases or daemons. New functions allow co-registering of measured 
electrode locations to the standard head model, or plotting of component 
dipole locations within Tailairach normalized individual subject MR head images.

A new EEG dataset structure field, 'EEG.chantype', allows users to 
distinguish the types of channels included in their data. Channel
types may be used to compute ICA on subsets of channels.
 
V5.01b also includes small upgrades and bug fixes for a larger number of EEGLAB 
functions, thanks to contributions and suggestions from many users. 

These new features are summarized in more detail at http://sccn.ucsd.edu/eeglab/eeglab5.0b.html
A more complete list of changes is available online at http://sccn.ucsd.edu/eeglab/revisions.html.

The transition from this beta release to a full release (in a few weeks) will 
benefit from feedback and suggestions from beta release users. Please send 
information about any bugs you encounter, or concerning any suggested 
improvements to eeglab at sccn.ucsd.edu.

Arnaud Delorme
Toby Fernsler
Scott Makeig

Swartz Center for Computational Neuroscience
Institute for Neural Computation, UCSD
http://sccn.ucsd.edu/