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ePoster
CORTICAL CONTROL OF A FORELIMB PROSTHESIS IN MICE
Edouard Ferrandand 5 co-authors
NeuroPSI
FENS Forum 2026 (2026)
Barcelona, Spain
Board PS01-07AM-403
Presentation
Date TBA
Board: PS01-07AM-403
Event Information
Poster Board
PS01-07AM-403
Poster
View posterAbstract
Robotic upper-limb prostheses aim to restore the autonomy of paralyzed patients and amputees. So far, advances in this field have relied on monkey pre-clinical and human clinical research.
Here, we report on the direct brain control by mice of a miniature mouse forelimb prosthesis (panel A). We show that mice implanted with a cortical, microelectrode-based brain-machine interface can learn to control the prosthesis via neuronal operant conditioning, and solve a water collection task in a 2-dimensional and up to a 3-dimensional space (panel B). As they learned this task, the mice shaped increasingly consistent prosthesis movements that led to rewards, thanks to coordinated patterns of neuronal activity across the several control dimensions.
Beyond the demonstration of unexpected cognitive and motor control abilities in mice, we anticipate that this preclinical model of upper-limb prosthesis control will be a tool to address several of the most pressing issues in prosthetics controlled by brain-machine interfaces.
Here, we report on the direct brain control by mice of a miniature mouse forelimb prosthesis (panel A). We show that mice implanted with a cortical, microelectrode-based brain-machine interface can learn to control the prosthesis via neuronal operant conditioning, and solve a water collection task in a 2-dimensional and up to a 3-dimensional space (panel B). As they learned this task, the mice shaped increasingly consistent prosthesis movements that led to rewards, thanks to coordinated patterns of neuronal activity across the several control dimensions.
Beyond the demonstration of unexpected cognitive and motor control abilities in mice, we anticipate that this preclinical model of upper-limb prosthesis control will be a tool to address several of the most pressing issues in prosthetics controlled by brain-machine interfaces.
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