Movement decoding from cortical and subcortical oscillations based on spatial filtering in patients with Parkinson's disease

VICTORIA PETERSON; TIMON MERK; WITOLD LIPSKI; ANDREA A. KÜHN; VADIM NIKULIN; WOLF-JULIAN NEUMANN; MARK RICHARSON

Conferencia; International DBS Conference 2020; 2020

In this work we have shown for the first time that spatial filtering approaches can be used for real-time compatible voluntary movement decoding from invasive ECoG and STN LFP data in patients with Parkinson?s disease. The SPoC approach extracts neuronal sources by using spatial information distributed over different channels to find the component most correlated with the target variable of interest. Exploring optimized multivariate decoding methods for clinical symptoms and movement is important for the next generation of intelligent clinical brain computer interfaces.