Real-time control of a robot arm using simultaneously recorded neurons
in the motor cortex
John K. Chapin1, Karen A. Moxon1, Ronald S. Markowitz1
& Miguel A. L. Nicolelis2
1
Department of Neurobiology and Anatomy, MCP Hahnemann
School of Medicine, Philadelphia, Pennsylvania
19129, USA
2
Department of Neurobiology, Duke University Medical
Center, Durham, North Carolina 27710,
USA
Correspondence should be addressed to John K. Chapin chapinj@mcphu.edu
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.
