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Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex

Abstract

To determine whether simultaneously recorded motor cortex neurons can be used for real-time device control, rats were trained to position a robot arm to obtain water by pressing a lever. Mathematical transformations, including neural networks, converted multineuron signals into 'neuronal population functions' that accurately predicted lever trajectory. Next, these functions were electronically converted into real-time signals for robot arm control. After switching to this 'neurorobotic' mode, 4 of 6 animals (those with >25 task-related neurons) routinely used these brain-derived signals to position the robot arm and obtain water. With continued training in neurorobotic mode, the animals' lever movement diminished or stopped. These results suggest a possible means for movement restoration in paralysis patients.

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Figure 1: Experimental protocol.
Figure 2: Color-coded peri-event population response plot shows activity of 46 simultaneously recorded neurons in the MI cortex and VL thalamus of rat 1, averaged around the onsets of 44 pressing movements.
Figure 3: Categories of recorded neurons.
Figure 5: Premovement NP activity predicts lever movement.
Figure 6: Neurorobotic mode.
Figure 4: Comparison of modes of movement 'coding' in lever-movement/robot-arm mode.

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Acknowledgements

This work was supported by NIH contract NS62352, ONR grant N00014-98-1-0679 and NIH grant NS26722 to J.K.C.

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Correspondence to John K. Chapin.

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Chapin, J., Moxon, K., Markowitz, R. et al. Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex. Nat Neurosci 2, 664–670 (1999). https://doi.org/10.1038/10223

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