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bioRxiv · 10.1101/2025.03.19.642627

Differential modulation of movement speed with state-dependent deep brain stimulation in Parkinson's disease

Abstract

Subthalamic deep brain stimulation (STN-DBS) provides unprecedented spatiotemporal precision for the treatment of Parkinsons disease (PD), allowing for direct real-time state-specific adjustments. Inspired by findings from optogenetic stimulation in mice, we hypothesized that STN-DBS effects on movement speed depend on ongoing movement kinematics that patients exhibit during stimulation. To investigate this hypothesis, we implemented a motor state-dependent closed-loop neurostimulation algorithm, adapting DBS burst delivery to ongoing movement speed in 24 PD patients. We found a stronger anti-bradykinetic effect, raising movement speed to the level of healthy controls, when STN-DBS was applied during fast but not slow movements, while only stimulating 5% of overall movement time. To study underlying brain circuits and neurophysiological mechanisms, we investigated the behavioral effects with MRI connectomics and motor cortex electrocorticography. Finally, we demonstrate that machine learning-based brain signal decoding can be used to predict continuous movement speed for fully embedded state-dependent closed-loop algorithms. Our findings provide novel insights into the state-dependency of invasive neuromodulation, which could inspire advanced state-dependent neurostimulation algorithms for brain disorders.

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BibTeXRIS

Cavallo, A., Köhler, R. M., Busch, J. L., Habets, J. G. V., Merk, T., Zvarova, P., Vanhoecke, J., Binns, T. S., Al-Fatly, B., de Almeida Marcelino, A. L., Darcy, N., Schneider, G.-H., Krause, P., Horn, A., Faust, K., Herz, D. M., Yttri, E., Cagnan, H., Kühn, A. A., Neumann, W.-J.. 2025-03-19. Differential modulation of movement speed with state-dependent deep brain stimulation in Parkinson's disease. https://doi.org/10.1101/2025.03.19.642627

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