A 1024-Channel 268-nW/Pixel 36 × 36 µm2/ Channel Data-Compressive Neural Recording IC for High-Bandwidth Brain–Computer Interfaces

Moonhyung Jang*, Maddy Hays, Changuk Lee, Pietro Caragiulo, Athanasios T. Ramkaj, Pingyu Wang, Nicholas Vitale, Pulkit Tandon, Dante G. Muratore, More Authors

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)
13 Downloads (Pure)

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× 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 × 32 array) with a pixel pitch of 36 µm that can be directly matched to a high-density micro-electrode array (MEA). The pixel achieves 7.4-µVrms 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 × 36 µm2) and the highest energy efficiency among the state-of-the-art neural recording ICs published to date.

Original languageEnglish
Pages (from-to)1123-1136
Number of pages14
JournalIEEE Journal of Solid-State Circuits
Volume59
Issue number4
DOIs
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Brain–computer interface (BCI)
  • brain–machine interface (BMI)
  • compression
  • multi-electrode array
  • neural interface
  • neural recording
  • pulse-position modulation (PPM)
  • single-cell resolution

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