Representation and decoding of bilateral arm motor imagery using unilateral cerebral LFP signals - Lin, Jiafan; Lai, Dongrong; Wan, Zijun; Feng, Linqing; Zhu, Junming; Zhang, Jianmin; Wang, Yueming; Xu, Kedi (Frontiers in Human Neuroscience, 2023)
In the field of upper limb brain computer interfaces (BCIs), the researches focusing on bilateral decoding mostly based on the neural signals from two cerebral hemispheres. In addition, most studies used spikes for decoding. Here we examined the representation and decoding of different laterality and regions arm motor imagery in unilateral motor cortex based on local field potentials (LFPs). The LFP signals were recorded from a 96-channel Utah microelectrode array implanted in the left primary motor cortex of a paralyzed participant. There were 7 kinds of tasks: rest, left, right and bilateral elbow and wrist flexion. We performed time-frequency analysis on the LFP signals and analyzed the representation and decoding of different tasks using the energy of different frequency bands. The frequency range of <8 Hz and >38 Hz showed power enhancement, whereas 8-38 Hz showed power suppression in time-frequency spectrograms while performing motor imagery. There were significant differences in average energy between tasks, and movement region and laterality were represented in two dimensions. The 135-300 Hz band signal had the highest decoding accuracy among all frequency bands and the contralateral and bilateral signals had more similar single-channel energy activation patterns and larger signal correlation. The results showed that unilateral LFP signals had different energy representations for bilateral motor imagery on the average energy and single-channel energy levels, and different tasks could be decoded. These proved the feasibility of multilateral BCI based on the unilateral LFP signal to broaden the application of BCI technology. Trial Registration: Chinese Clinical Trial Registry ChiCTR2100050705; https://www.chictr.org.cn/showproj.aspx?proj=130829.