Movement decoding based on spatial filtering in invasive recordings

Interest in decoding movement with invasive recordings? In our last manuscript we show how we can serve from the spatial filtering approaches to improve movement decoding in invasive neurophysiology. Applied to movement decoding for adaptive Deep Brain Stimulation Devices, the pipeline takes cortical and/or subcortical recordings to extract features and train a regression model based on supervised and linear algorithms. Spatial features have the potential to improve the decoding as compared to using single electrodes. If you want to know more, read our publication: https://www.sciencedirect.com/science/article/abs/pii/S0014488622002862 

The code is available on GitHub: https://github.com/Brain-Modulation-Lab/Paper_SpatialPatternsMovementDecoding