MoonHyung Jang; Wei-Han Yu; Changuk Lee; M.T. Hays; Pingyu Wang; Nick Vitale; Pulkit Tandon; Pumiao Yan; Pui‐In Mak; Youngcheol Chae; E. J. Chichilnisky; Boris Murmann; Dante G. Muratore · 2023
Paper
This paper presents a neural recording IC featuring lossy compression during digitization, thus preventing data deluge and enabling a compact active digital pixel design. The wired-OR-based compression discards unwanted baseline samples while allowing the reconstruction of spike samples. The IC features a 32x32 MEA with $36 \mu m$ pixel pitch and consumes 268nW per pixel from a single 1V supply. It achieves $9.8 \mu V_{RMS}$ input-referred noise and 0.3-5kHz bandwidth, resulting in NEF/PEF of 3.7/14.1.
Analysis
This paper introduces a novel neural recording integrated circuit (IC) designed for high-bandwidth brain-computer interfaces, employing data compression during digitization to manage data volume.
Discovery
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