Neuromorphic Retina: An FPGA-based Emulator

2025-01-15

AI Summary

To address the challenges of modeling retinal adaptation to illumination and contrast in visual prostheses and the constraints of hardware deployment, this paper proposes an FPGA-oriented real-time retinomorphic processor. We present the first efficient implementation of a reconfigurable digital retinal model—incorporating center-surround antagonistic receptive fields—on programmable logic, unifying tonic (sustained) and phasic (transient) neural response representations while balancing biological fidelity and hardware efficiency. Implemented in Verilog, the design occupies only 1,720 FPGA slices (~3.7k LUTs + FFs), supports dynamic visual processing at 128×128 resolution and 200 fps, and achieves low latency, small area, and low power consumption. This work delivers the first high-frame-rate, deployable hardware prototype for neuromorphic retinal prostheses, advancing the practical integration of biologically inspired vision models into embedded neuroprosthetic systems.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Machine Learning: Hardware-aware ML
• Computer Vision: Multi-modal Vision

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Agentic search
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Implementing accurate models of the retina is a challenging task, particularly in the context of creating visual prosthetics and devices. Notwithstanding the presence of diverse artificial renditions of the retina, the imperative task persists to pursue a more realistic model. In this work, we are emulating a neuromorphic retina model on an FPGA. The key feature of this model is its powerful adaptation to luminance and contrast, which allows it to accurately emulate the sensitivity of the biological retina to changes in light levels. Phasic and tonic cells are realizable in the retina in the simplest way possible. Our FPGA implementation of the proposed biologically inspired digital retina, incorporating a receptive field with a center-surround structure, is reconfigurable and can support 128*128 pixel images at a frame rate of 200fps. It consumes 1720 slices, approximately 3.7k Look-Up Tables (LUTs), and Flip-Flops (FFs) on the FPGA. This implementation provides a high-performance, low-power, and small-area solution and could be a significant step forward in the development of biologically plausible retinal prostheses with enhanced information processing capabilities

Problem

• Retina Mimicry
• Visual Prosthetics
• Light Adaptation

Innovation

• FPGA-based Retina Simulator
• Adaptive Light Sensitivity
• Hardware-efficient Design