Decoding movement and laterality from local field potentials in the subthalamic nucleus

Decoding of movement related neural activity is a key process required for brain computer interfaces or bio-feedback. The subthalamic nucleus (STN) is involved in the preparation, execution and imagining of movements. This study therefore aimed to decode subthalamic local field potentials (LFPs) related to movements and its laterality, left or right sided visually cued movements. STN LFPs frequency dependent components were extracted using the wavelet packet transform. The time variant amplitudes of each component were then computed with the Hilbert transform, and then ranked as classification features using a brute-force search approach. Left or right movements compared with rest were sequentially classified using a support vector machine (SVM). With optimised parameters, average correct classification of movement reached 91.5±2.3% and of side (left or right), 74.0±6.4%.