Leili Soo

The paper models phosphenes elicited by intracortical stimulation in human V1, showing that electrode stimulation can produce varied shapes due to activation of multiple locations.

This paper develops a deep learning framework to control neural activity in the human visual cortex using a neuroprosthesis, achieving better performance than conventional methods.

This study shows that reducing the distance between visual stimuli decreases behavioral performance and SSVEP amplitudes, linking cortical suppression to visual crowding.

This study uses Bayesian optimization to find optimal stimulation patterns for cortical neuroprosthetics, improving phosphene perception quality through patient feedback.