Music versus motor imagery for BCI systems a study using fMRI and EEG: Preliminary results

Abstract

The development of brain-computer interfaces (BCIs) for disabled patients is currently a growing field of research. Most BCI systems are based on electroencephalography (EEG) signals, and within this group, systems using motor imagery (MI) are amongst the most flexible. However, for stroke patients, the motor areas of the brain are not always available for use in these types of devices. The aim of this work was to evaluate a set of imagery-based cognitive tasks (right-hand MI versus music imagery, with rest or “blank” periods in between), using functional Magnetic Resonance Imaging (fMRI) and EEG. Eleven healthy subjects (control group) and four stroke patients were evaluated with fMRI, and nine of the healthy subjects also underwent an EEG test. The fMRI results for the control group showed specific and statistically differentiable activation patterns for motor versus music imagery (t-test, p <; 0.001). For stroke patients the fMRI results showed a very large variability, with no common activation pattern for either of the imagery tasks. Corroborating this fact, EEG results concerning feature selection for minimizing the classification error (using the Davies-Bouldin index) have also found no common activation pattern, although a well-defined set of meaningful electrodes and frequencies was found for some subjects. In terms of classification performance using EEG data, this work has detected a group of subjects with classifier rate of success up to 60%, which is promising in view of the cognitive complexity of the adopted tasks.