Papers
3
Total Citations
36
H-Index
3
About
Dorian Goueytes is a neuroscientist at the forefront of closed-loop brain-machine interfaces (BMIs), with a focus on integrating sensory feedback to restore autonomy for patients with paralysis or amputation. His research centers on developing intracortical BMIs that combine real-time neural decoding with patterned optogenetic or electrical cortical stimulation, enabling bidirectional communication between the brain and prosthetic devices. Goueytes’s most cited work, "A fast intracortical brain–machine interface with patterned optogenetic feedback" (2018, 26 citations), demonstrates how distributed cortical microstimulations can deliver rich, intuitive feedback to users, significantly improving prosthesis control. In subsequent studies, including "Learning in a closed-loop brain-machine interface with distributed optogenetic cortical feedback" (2022, 6 citations) and "Control of a robotic prosthesis simulation by a closed-loop intracortical brain-machine interface" (2019, 4 citations), he has shown that mice can learn to manipulate a virtual or simulated robotic arm using only neural activity and artificial feedback. Goueytes’s contributions are notable for bridging fundamental neuroscience with translational engineering, offering a pathway toward more natural, dexterous prostheses. His work underscores the critical role of closed-loop feedback in achieving real-world BMI functionality, making him a rising figure in neuroprosthetics.
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