Journal article
Danny da Costa, Lukas Kornemann, R. Goebel, M. Senden
bioRxiv, 2023
bioRxiv, 2023
Semantic Scholar
DOI
Cite
Cite
APA
Click to copy
da Costa, D., Kornemann, L., Goebel, R., & Senden, M. (2023). Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling. BioRxiv.
Chicago/Turabian
Click to copy
Costa, Danny da, Lukas Kornemann, R. Goebel, and M. Senden. “Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling.” bioRxiv (2023).
MLA
Click to copy
da Costa, Danny, et al. “Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling.” BioRxiv, 2023.
BibTeX Click to copy
@article{danny2023a,
title = {Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling},
year = {2023},
journal = {bioRxiv},
author = {da Costa, Danny and Kornemann, Lukas and Goebel, R. and Senden, M.}
}
Abstract
Primate visual cortex exhibits key organizational principles: Cortical magnification, eccentricity-dependent receptive field size and spatial frequency tuning as well as radial bias. We provide compelling evidence that these principles arise from the interplay of the non-uniform distribution of retinal ganglion cells (RGCs), and a quasi-uniform convergence rate from the retina to the cortex. We show that convolutional neural networks (CNNs) outfitted with a retinal sampling layer, which resamples images according to retinal ganglion cell density, develop these organizational principles. Surprisingly, our results indicate that radial bias is spatial-frequency dependent and only manifests for high spatial frequencies. For low spatial frequencies, the bias shifts towards orthogonal orientations. These findings introduce a novel hypothesis about the origin of radial bias. Quasi-uniform convergence limits the range of spatial frequencies (in retinal space) that can be resolved, while retinal sampling determines the spatial frequency content throughout the retina.