Evidence map›Paper›PMID 37870175›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023

An Ultraflexible Electrode Array for Large-Scale Chronic Recording in the Nonhuman Primate Brain.

Yixin Tian, Jiapeng Yin, Chengyao Wang, Zhenliang He, Jingyi Xie, Xiaoshan Feng, Yang Zhou, Tianyu Ma, Yang Xie, Xue Li and 4 more

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
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

15 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
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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

14 authors at 2 institutions in 1 country.

Yixin TianInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Jiapeng YinShanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, 201602, China.
Chengyao WangInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Zhenliang HeLingang Laboratory, Shanghai, 200031, China.
Jingyi XieInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Xiaoshan FengInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Yang ZhouInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Tianyu MaInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Yang XieLingang Laboratory, Shanghai, 200031, China.
Xue LiInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Tianming YangInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
Chi RenInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.ORCID 0000-0002-0947-8516
Chengyu LiLingang Laboratory, Shanghai, 200031, China.
Zhengtuo ZhaoInstitute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.ORCID 0000-0003-2476-1560
Chinese Academy of Sciences · CNShanghai Center for Brain Science and Brain-Inspired Technology · CN

Funding

Lingang Laboratory LG202105-01-06National Science and Technology Innovation 2030 Major Program 2022ZD0210300Shanghai Municipal Science and Technology Major Project 2018SHZDZX05Shanghai Municipal Science and Technology Major Project 2021SHZDZX
6 · The paper itself

Abstract

Single-unit (SU) recording in nonhuman primates (NHPs) is indispensible in the quest of how the brain works, yet electrodes currently used for the NHP brain are limited in signal longevity, stability, and spatial coverage. Using new structural materials, microfabrication, and penetration techniques, we develop a mechanically robust ultraflexible, 1 µm thin electrode array (MERF) that enables pial penetration and high-density, large-scale, and chronic recording of neurons along both vertical and horizontal cortical axes in the nonhuman primate brain. Recording from three monkeys yields 2,913 SUs from 1,065 functional recording channels (up to 240 days), with some SUs tracked for up to 2 months. Recording from the primary visual cortex (V1) reveals that neurons with similar orientation preferences for visual stimuli exhibited higher spike correlation. Furthermore, simultaneously recorded neurons in different cortical layers of the primary motor cortex (M1) show preferential firing for hand movements of different directions. Finally, it is shown that a linear decoder trained with neuronal spiking activity across M1 layers during monkey's hand movements can be used to achieve on-line control of cursor movement. Thus, the MERF electrode array offers a new tool for basic neuroscience studies and brain-machine interface (BMI) applications in the primate brain.

Indexed as

BrainPrimatesAnimalsElectrodesSingle-Cell Analysisbrain-machine interfacesmotor cortexnonhuman primatessingle-unit recordingsultraflexible electrode arraysvisual cortex

Identifiers

PMID37870175
PMCPMC10667845
OpenAlexW4387866293

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.