Percept-Aware Surgical Planning for Visual Cortical Prostheses with Vascular Avoidance

2026-02-27

AI Summary

This study addresses the lack of electrode implantation planning methods for high-density visual cortical prostheses that simultaneously optimize perceptual performance and vascular safety. The authors formulate electrode placement as an anatomically constrained spatial optimization problem, integrating—for the first time—a differentiable forward model of prosthetic vision with explicit constraints for vascular avoidance and gray matter feasibility. This framework enables end-to-end, perception-driven surgical planning and supports collaborative optimization across multiple electrodes. Evaluated on realistic cortical geometries derived from FreeSurfer, the approach substantially outperforms conventional coverage-based strategies in simulated reading and natural image tasks, achieving significantly higher reconstruction fidelity while completely avoiding vascular intrusion.

Technology Category

• Computer Vision: Learning & Optimization for CV
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Cortical visual prostheses aim to restore sight by electrically stimulating neurons in early visual cortex (V1). With the emergence of high-density and flexible neural interfaces, electrode placement within three-dimensional cortex has become a critical surgical planning problem. Existing strategies emphasize visual field coverage and anatomical heuristics but do not directly optimize predicted perceptual outcomes under safety constraints. We present a percept-aware framework for surgical planning of cortical visual prostheses that formulates electrode placement as a constrained optimization problem in anatomical space. Electrode coordinates are treated as learnable parameters and optimized end-to-end using a differentiable forward model of prosthetic vision. The objective minimizes task-level perceptual error while incorporating vascular avoidance and gray matter feasibility constraints. Evaluated on simulated reading and natural image tasks using realistic folded cortical geometry (FreeSurfer fsaverage), percept-aware optimization consistently improves reconstruction fidelity relative to coverage-based placement strategies. Importantly, vascular safety constraints eliminate margin violations while preserving perceptual performance. The framework further enables co-optimization of multi-electrode thread configurations under fixed insertion budgets. These results demonstrate how differentiable percept models can inform anatomically grounded, safety-aware computer-assisted planning for cortical neural interfaces and provide a foundation for optimizing next-generation visual prostheses.

Problem

• cortical visual prostheses
• surgical planning
• perceptual optimization
• vascular avoidance
• electrode placement

Innovation

• percept-aware optimization
• differentiable forward model
• vascular avoidance
• cortical visual prosthesis
• constrained surgical planning