Introduction

BDCA for EEG aims to identify discriminating components in the EEG. Each component is represented by a spatial and a temporal activity profile. Ambiguities are resolved using independence across trials.

Read the Tutorial to see how you should tune the parameters.

How to obtain the code

The best way to get the code is this:

Make sure SVN is installed on your machine (why?):

(Mac) To install SVN on a Mac follow steps 1,2,3 given here
(Linux) To install SVN on Linux is very easy using apt-get or find it in the synaptic package manager.
(Windows / Redhat / Solaris) go here

Click the "Source" tab or click here to see exactly how you use SVN to receive the up-to-date source code. It will tell you to run the following command from a terminal:

svn checkout http://bdca.googlecode.com/svn/trunk/ bdca-read-only

the source will then be downloadet to a directory called bdca-read-only under your current directory.

Alternatively, (NOT RECOMMENDED)

Click the "Downloads" tab, and download a release which will NOT be up to date with bug fixes and new features.

Dependencies

The BDCA toolbox relies (currently) on other toolboxes. You need to download and install the following toolboxes in order to use the BDCA toolbox:

IMMOPTIBOX - Get the file: download

Staying up to date with bugfixes and new features

If the source code on this page changes you can get the updates in a simple step:

In a terminal, go to the bdca-read-only directory where the toolbox is located on your machine.
run the following command from the terminal:

svn update

that's it!

References

Dyrholm, M., Christoforou, C., Parra, L. C., ''Bilinear Discriminant Component Analysis'', Journal of Machine Learning Research, 8(May):1097-1111, 2007

Dyrholm, M., Parra, L. C., ''Smooth bilinear classification of EEG'', In proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, New York, August 2006.