Dongrong Lai
ABSTRACT
Brain-computer interfaces (BCIs) provide a passway to connect the devices and the living brains by transforming the cortical signals to control commands to the devices. The ability of the contralateral primary motor cortex (M1) to represent sequentially changing kinematics has been proposed in previous intracortical BCI papers. However, it's not clear whether the ipsilateral M1 could be used to decode continuous trajectories like the contralateral one and whether the bilateral brain regions had similar levels of decoding performance. To that end, we recorded the single-unit activities from bilateral M1 during the center-out task performed by a monkey and predicted the 2-dimensional (2D) positions by using partial least squares (PLS). Our results revealed that the decoder with neurons recorded from ipsilateral M1 was able to decode continuous positions. When using the overall dataset, bilateral hemispheres showed an even contribution to the prediction. In addition, we found that the decoder using contralateral neurons outperformed that using ipsilateral neurons, which could be attributed to the stronger correlation of neuron pairs within contralateral M1 versus within ipsilateral M1. Our findings support that the movement kinematics are bihemispherically encoded in M1 and that the underlying structure within contralateral M1 may contribute to the outperformance in the prediction. These results improve our understanding of motor control in M1 and implicate the design of cutting-edge BCIs with a more precise prediction strategy.
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Index Terms
- Continuous Decoding of Movement Trajectory During Unimanual Movement Using Bilateral Motor Cortex Signals
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