bioRxivBioengineeringPreprint
Within-Subject Optogenetic Model Reveals Spatiotemporal Cortical Reorganization in Artificial Vision
Xurong Gao, Wenjie Ren, Baisong Zhang, Yueqian Zhou, Guangda Hu, Yuchen XuiD, Chengpeng ChaiiD, Chuanqing WangiD, Yong Zou, Lifeng Wang, Yun-Hsuan CheniD, Jie YangiD, Mohamad SawaniD
Abstract
Visual prostheses can elicit simple percepts such as letter forms through dynamically patterned stimulation, yet naturalistic dynamic vision remains out of reach despite hardware fully capable of high-resolution temporal control. This persistent gap suggests the bottleneck lies in how artificial input is represented by the cortex itself. A fundamental question remains unresolved: when artificial vision bypasses natural retinal encoding, what is lost in cortical representation? We address this question in this paper using a retinal optogenetic mouse model that isolates the consequence of bypassing retinal encoding while preserving downstream pathways. Using within-subject V1 cortex electrophysiology and CNN-based decoding under identical dynamic stimuli, we reveal dissociable, dimension-specific gaps. Temporally, artificial vision bypassed the frequency-dependent compression imposed by natural vision, extending stimulus-locked entrainment bandwidth. Spatially, direction-selective representations underwent systematic remapping, with disrupted phase organization and reduced encoding regularity. These findings show that bypassing natural retinal encoding reorganizes cortical representation along dissociable spatiotemporal dimensions, establishing a within-subject framework that renders such structural divergences easy to locate and quantifiable.
- organism: mouse
- assay: electrophysiology
- research focus: cell type annotation
- approach: experimental assay
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Beyond retinotopy: exploiting native visual representations in cortical neuroprostheses for vision loss remediation
Luca Baroni, Martin Picek, … Ján Antolík·bioRxiv·Nov 3, 2025
- Decoding natural scenes from patterned optogenetic responses in mouse visual cortex
Shanshan Jia, Tianyu Xin, … Ya-tang Li·bioRxiv·Sep 28, 2026
- Cortical visual prosthesis: a detailed large-scale simulation study
Ján Antolík, Quentin Sabatier, … Ryad Benjamin Benosman·bioRxiv·Apr 18, 2019
- Pulse trains to percepts: A virtual patient describing the perceptual effects of human visual cortical stimulation
Ione Fine, Geoffrey M. Boynton·bioRxiv·Mar 18, 2023
- Image modifications reduce differences in natural-image encoding by retinal ganglion cells between natural and optogenetic stimulation
Varsha Ramakrishna, Tim Gollisch·bioRxiv·Jun 29, 2026
- Simulation of visual perception and learning with a retinal prosthesis
James R. Golden, Cordelia R. Erickson-Davis, … E. J. Chichilnisky·Journal of Neural EngineeringPeer-reviewed·Nov 20, 2018