Evidence map›Paper›PMID 39391047›Full record

ArticleIEEE journal of solid-state circuits2024

A 1024-Channel 268 nW/pixel 36×36

MoonHyung Jang, Maddy Hays, Wei-Han Yu, Changuk Lee, Pietro Caragiulo, Athanasios Ramkaj, Pingyu Wang, A J Phillips, Nick Vitale, Pulkit Tandon and 6 more

Abstract read
In one paragraph

Article in IEEE journal of solid-state circuits, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Review
  3. A Framework for Compressive On-Chip Action Potential Recording.IEEE transactions on bio-medical engineering · 2026
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. A 1024-Channel 268 nW/pixel 36×36IEEE journal of solid-state circuits · 2024
    Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

MoonHyung JangDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Maddy HaysDepartment of Bioengineering, Stanford University, CA 94305 USA.
Wei-Han YuInstitute of Microelectronics, University of Macau, Avenida da Universidade, Taipa, Macau, China.
Changuk LeeDepartment of Electrical Engineering and Computer Sciences, University of California Berkeley, CA 94720, USA.
Pietro CaragiuloDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Athanasios RamkajDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Pingyu WangDepartment of Materials Science and Engineering, Stanford University, CA 94305 USA.
A J PhillipsDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Nick VitaleDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Pulkit TandonDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Pumiao YanDepartment of Electrical Engineering, Stanford University, CA 94305 USA.
Pui-In MakInstitute of Microelectronics, University of Macau, Avenida da Universidade, Taipa, Macau, China.
Youngcheol ChaeDepartment of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea.
E J ChichilniskyHansen Experimental Physics Laboratory, Department of Neurosurgery and Ophthalmology, Stanford University, CA 94305 USA.
Boris MurmannDepartment of Electrical Engineering, Stanford University; Department of Electrical & Computer Engineering, University of Hawaii at Mānoa, HI 96822.
Dante G MuratoreDepartment of Microelectronics, Delft University of Technology, Delft, The Netherlands.

Funding

Patterned Electrical Stimulation of the Retina for High-Resolution ProsthesesR01EY021271 · NEI · STANFORD UNIVERSITY · PI EDUARDO CHICHILNISKY · 2011 to 2026
$4.6M
Bi-directional neural interface for probing parallel visual pathwaysR01EY032900 · NEI · STANFORD UNIVERSITY · PI CHICHILNISKY, EDUARDO, COGAN, STUART F · 2021 to 2024
$2.8M
NEI NIH HHS R01 EY021271NEI NIH HHS R01 EY032900
6 · The paper itself

Abstract

This paper presents a data-compressive neural recording IC for single-cell resolution high-bandwidth brain-computer interfaces. 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-based active digital pixels with a global single-slope 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

Indexed as

Brain-computer interface (BCI)brain-machine interface (BMI)compressionmulti-electrode array (MEA)neural interfaceneural recordingpulse-position modulation (PPM)single-cell resolution

Identifiers

PMID39391047
PMCPMC11463976

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.