12 citations · 36 across the 6 of their papers we have counts for
3 papers · 1 filter
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses
Jacob Granley, Tristan Fauvel, Matthew Chalk +1
Neuroprostheses show potential in restoring lost sensory function and enhancing human capabilities, but the sensations produced by current devices often seem unnatural or distorted…
Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture
Galen Pogoncheff, Jacob Granley, Michael Beyeler
Convolutional neural networks (CNNs) have recently emerged as promising models of the ventral visual stream, despite their lack of biological specificity. While current state-of-th…
Adapting Brain-Like Neural Networks for Modeling Cortical Visual Prostheses
Jacob Granley, Alexander Riedel, Michael Beyeler
Cortical prostheses are devices implanted in the visual cortex that attempt to restore lost vision by electrically stimulating neurons. Currently, the vision provided by these devi…