We develop methods for choosing stimulation patterns that produce a desired percept or neural response, using predictive models, optimization, and feedback from the user or the brain.
Topic
Machine Learning
Researchers Interested in This Topic
Publications
Deep learning-based control of electrically evoked activity in human visual cortex
We developed a data-driven neural control framework for a visual cortical prosthesis in a blind human, showing that deep learning can synthesize efficient, stable stimulation patterns that reliably evoke percepts and outperform conventional calibration methods.
Pehuén Moure*(co-first author) 
Jacob Granley*(co-first author) Fabrizio Grani*(co-first author) Leili Soo Antonio Lozano Rocio López-Peco Adrián Villamarin-Ortiz Cristina Soto-Sánchez Shih-Chii Liu†(co-last author) 
Michael Beyeler†(co-last author) 
Eduardo Fernández†(co-last author)
Neuron 114:1-15
