A High Performance MEG Based BCI Using Single Trial Detection of Human Movement Intention

Abstract

Human volitional movement is orchestrated by dynamic changes in brain activity that can be detected by noninvasive electrophysiological recording using electroencephalography (EEG) or magnetoencephalography (MEG). At least two kinds of movement-related brain activity can be observed: movement–related cortical potentials (MRCP) and event-related desynchronization/ synchronization (ERD/ERS) in the alpha (8-13Hz) and beta frequency band (16-30Hz) as reviewed in [1-3]. Both have been observed prior to movement onset and represent the activation of widespread sensorimotor networks responsible for the preparation and intention to move. Although it may be more difficult to identify premovement activity from the spatial distribu‐ tion of MRCP due to the small amplitude of the signal and the need for signal averaging to enhance the signal-to-noise ratio, changes in oscillatory activity may be detectable even on a single trial basis. Functional mapping studies using EEG and MEG have demonstrated that somatotopical‐ ly restricted motor areas are activated before the actual production of certain limb movements. For example, as assessed by studying movement-related ERD in [4-6], the hand area is activat‐ ed before the production of hand movements whereas the foot area is activated prior to foot movements. Furthermore, there is a consistent lateralization of activation with right hand movements activated by predominantly left sensorimotor cortex whereas left hand move‐ ments are activated by right sensorimotor cortex. If the spatial resolution of the signal is high enough, discrimination of different movement intentions from the spatiotemporal distribution of oscillatory brain activity should be possible on a single trial basis and could be harnessed as a flexible control signal for external devices in the design of brain computer interfaces (BCI).