Data set I ‹motor imagery in ECoG recordings, session-to-session transfer›

Data set provided by University of Tübingen, Germany, Dept. of Computer Engineering (Prof. Rosenstiel) and Institute of Medical Psychology and Behavioral Neurobiology (Niels Birbaumer), and
Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany (Bernhard Schölkopf), and
Universität Bonn, Germany, Dept. of Epileptology (Prof. Elger)

Correspondence to Michael Schröder 〈schroedm@informatik.uni-tuebingen.de〉

The Thrill

The design of a classifier for a BCI system is very challenging when a classifier that was trained on the first day shall classify data recorded during following days (if possible, without retraining): the patient might be in a different state concerning motivation, fatigue etc. so that his brain will show different electrical activity. In addition, the recording system might have undergone slight changes concerning electrode positions and impedances. Our data set reflects this sitation: training data and test data were recorded from the same subject and with the same task, but on two different days with about 1 week in between. Learn on the data of the first session and do your best on the data of the second session!

Experiment

During the BCI experiment, a subject had to perform imagined movements of either the left small finger or the tongue. The time series of the electrical brain activity was picked up during these trials using a 8x8 ECoG platinum electrode grid which was placed on the contralateral (right) motor cortex. The grid was assumed to cover the right motor cortex completely, but due to its size (approx. 8x8cm) it partly covered also surrounding cortex areas. All recordings were performed with a sampling rate of 1000Hz. After amplification the recorded potentials were stored as microvolt values. Every trial consisted of either an imagined tongue or an imagined finger movement and was recorded for 3 seconds duration. To avoid visually evoked potentials being reflected by the data, the recording intervals started 0.5 seconds after the visual cue had ended.

Format of the Data

The labeled training data (from the first session) is stored as a zipped matlab file called Competition_train.mat.gz. Use this data to train your classification algorithms. It consists of two parts: The unlabeled test data is also stored as a zipped matlab file called Competition_test.mat.gz. It contains 100 trials of brain activity in matrix X (3D format is the same as described above) but it contains no labels Y.

Your Task

Please try to correctly classify the test data set (100 trials). Provide a list of the labels (-1/1) of these 100 trials in either ascii or matlab format. Send your labels by email to 〈schroedm@informatik.uni-tuebingen.de〉 with the subject "SOLUTION BCI COMPETITION".

Performance criterion

How many of the labels you provided match the true labels of the test set?

Reference

You can use our data set for your own publications, if you please cite us:

[ BCI Competition III ]