Litcius/Paper detail

A 1024-Channel 268 nW/pixel 36x36 μm<sup>2</sup>/ch Data-Compressive Neural Recording IC for High-Bandwidth Brain-Computer Interfaces

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

202311 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

PixelBandwidth (computing)DigitizationLossy compressionComputer scienceChannel (broadcasting)Data compressionComputer hardwareElectronic engineeringArtificial intelligenceEngineeringTelecommunicationsAdvanced Memory and Neural ComputingNeuroscience and Neural EngineeringNeural Networks and Applications