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arXiv · 2310.10790

Neuromorphic Place Cells

Zhaoqi Chen·Ralph Etienne-Cummings
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Abstract

A neuromorphic SLAM system shows potential for more efficient implementation than its traditional counterpart. We demonstrate a mixed-mode implementation for spatial encoding neurons including theta cells, vector cells, and place cells. Together, they form a biologically plausible network that could reproduce the localization functionality of place cells. The system consists of a theta chip with 128 units and an FPGA encoding 4 networks for vector cells formation that provides the capability for tracking on a 11 by 11 place cell grid. Experimental results validate the robustness of our model when suffering from 18% standard deviation from mathematical models induced by variations of analog circuits. We provide a foundation for implementing dynamic neuromorphic SLAM systems for nonhomogeneous mapping and inspirations for the formation of spatial cells in biology.

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Zhaoqi Chen, Ralph Etienne-Cummings. 2023-10-16. Neuromorphic Place Cells. https://arxiv.org/abs/2310.10790

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