Litcius/Paper detail

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

MoonHyung Jang, M.T. Hays, Wei-Han Yu, Changuk Lee, P. Caragiulo, Athanasios T. Ramkaj, Pingyu Wang, AJ Phillips, Nicholas Vitale, Pulkit Tandon, Pumiao Yan, Pui‐In Mak, Youngcheol Chae, E. J. Chichilnisky, Boris Murmann, Dante G. Muratore

2023IEEE Journal of Solid-State Circuits18 citationsDOIOpen Access PDF

Abstract

This article presents a data-compressive neural recording IC for single-cell resolution high-bandwidth brain–computer interfaces (BCIs). The IC features wired-OR lossy compression during digitization, thus preventing data deluge and massive data movement. By discarding unwanted baseline samples of the neural signals, the output data rate is reduced by 146 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> on average while allowing the reconstruction of spike samples. The recording array consists of pulse-position modulation (PPM)-based active digital pixels (ADPs) with a global single-slope (SS) analog-to-digital conversion scheme, which enables a low-power and compact pixel design with significantly simple routing and low array readout energy. Fabricated in a 28-nm CMOS process, the neural recording IC features 1024 channels (i.e., 32 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 32 array) with a pixel pitch of 36 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> that can be directly matched to a high-density micro-electrode array (MEA). The pixel achieves 7.4- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{V}_{\text {rms}}$ </tex-math></inline-formula> input-referred noise with a −3-dB bandwidth of 300 Hz–5 kHz while consuming only 268 nW from a single 1-V supply. The IC achieves the smallest area per channel (36 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 36 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text {m}^{{2}}$ </tex-math></inline-formula> ) and the highest energy efficiency among the state-of-the-art neural recording ICs published to date.

Topics & Concepts

Channel (broadcasting)Bandwidth (computing)PixelComputer scienceMaterials scienceArtificial intelligenceTelecommunicationsEEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringAdvanced Memory and Neural Computing