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Updated: Aug 8, 2025

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
Published on: March 10, 2011
Neural Plasticity in Sensorimotor Brain-Machine Interfaces
Maria C Dadarlat1, Ryan A Canfield2, Amy L Orsborn2,3,4
1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA;
Abstract:
Brain-machine interfaces (BMIs) aim to treat sensorimotor neurological disorders by creating artificial motor and/or sensory pathways. Introducing artificial pathways creates new relationships between sensory input and motor output, which the brain must learn to gain dexterous control. This review highlights the role of learning in BMIs to restore movement and sensation, and discusses how BMI design may influence neural plasticity and performance. The close integration of plasticity in sensory and motor function influences the design of both artificial pathways and will be an essential consideration for bidirectional devices that restore both sensory and motor function.
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