Using High-Frequency Local Field Potentials From Multicortex to Decode Reaching and Grasping Movements in Monkey

Abstract

Intracortical brain–machine interfaces (iBMIs) hold the promise to restore communication and movement ability of paralyzed people. Recent studies showed that local field potentials (LFPs) could be a reliable neural signal for movement intention decoding in iBMIs. However, previous studies investigated primarily on low-frequency LFPs, while the LFPs used were recorded from only one or two cortices. The aim of this paper is to investigate the potential of high-frequency LFPs (200–300 Hz) from multicortex in movement intention decoding. In this paper, LFPs were recorded via microelectrode arrays chronically implanted into the primary motor cortex (M1), somatosensory cortex (S1), and posterior parietal cortex of two monkeys while they were trained to perform 3-D reaching and grasping movements. The wavelet packet transform (WPT) method was used to extract the time and frequency information of the high-frequency LFP signals and the node energy of the WPT coefficients was selected as the features. After feature reduction by the principal component analysis, a support vector machine decoder was used to classify discrete reaching positions and grasping postures. Our results indicate that high decoding accuracy can be achieved by the high-frequency LFPs with WPT method and this kind of LFPs could serve as useful signals in iBMIs for movement intention decoding. Moreover, better and more robust decoding performance can be achieved by LFPs from multicortex than single-cortex.