  Neural activity in the visual cortex of blind humans persists in the absence
of visual stimuli. However, little is known about the preservation of visual
representation capacity in these cortical regions, which could have significant
implications for neural interfaces such as visual prostheses. In this work, we
present a series of analyses on the shared representations between evoked
neural activity in the primary visual cortex (V1) of a blind human with an
intracortical visual prosthesis, and latent visual representations computed in
deep neural networks (DNNs). In the absence of natural visual input, we examine
two alternative forms of inducing neural activity: electrical stimulation and
mental imagery. We first quantitatively demonstrate that latent DNN activations
are aligned with neural activity measured in blind V1. On average, DNNs with
higher ImageNet accuracy or higher sighted primate neural predictivity are more
predictive of blind V1 activity. We further probe blind V1 alignment in
ResNet-50 and propose a proof-of-concept approach towards interpretability of
blind V1 neurons. The results of these studies suggest the presence of some
form of natural visual processing in blind V1 during electrically evoked visual
perception and present unique directions in mechanistically understanding and
interfacing with blind V1.
