Evidence map›Paper›PMID 35002602›Full record

ArticleFrontiers in neuroscience2021

Carbon-Based Fiber Materials as Implantable Depth Neural Electrodes.

Xuefeng Fu, Gen Li, Yutao Niu, Jingcao Xu, Puxin Wang, Zhaoxiao Zhou, Ziming Ye, Xiaojun Liu, Zheng Xu, Ziqian Yang and 7 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 19 citations in OpenAlex.

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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

17 authors at 3 institutions in 1 country.

Xuefeng FuDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Gen LiDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Yutao NiuSchool of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei, China.
Jingcao XuSchool of Materials Science and Engineering, Peking University, Beijing, China.
Puxin WangDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Zhaoxiao ZhouDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Ziming YeSchool of Materials Science and Engineering, Peking University, Beijing, China.
Xiaojun LiuDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Zheng XuDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Ziqian YangDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Yongyi ZhangSchool of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei, China.
Ting LeiSchool of Materials Science and Engineering, Peking University, Beijing, China.
Baogui ZhangBrainnetome Center, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China.
Qingwen LiSchool of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei, China.
Anyuan CaoSchool of Materials Science and Engineering, Peking University, Beijing, China.
Tianzai JiangBrainnetome Center, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China.
Xiaojie DuanDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
Peking University · CNChinese Academy of Sciences · CNSuzhou Institute of Nano-tech and Nano-bionics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Implantable brain electrophysiology electrodes are valuable tools in both fundamental and applied neuroscience due to their ability to record neural activity with high spatiotemporal resolution from shallow and deep brain regions. Their use has been hindered, however, by the challenges in achieving chronically stable operations. Furthermore, implantable depth neural electrodes can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. Minimizing inflammatory responses and associated gliosis formation, and improving the durability and stability of the electrode insulation layers are critical to achieve long-term stable neural recording and stimulation. Combining electrophysiological measurements with simultaneous whole-brain imaging techniques, such as magnetic resonance imaging (MRI), provides a useful solution to alleviate the challenge in scalability of implantable depth electrodes. In recent years, various carbon-based materials have been used to fabricate flexible neural depth electrodes with reduced inflammatory responses and MRI-compatible electrodes, which allows structural and functional MRI mapping of the whole brain without obstructing any brain regions around the electrodes. Here, we conducted a systematic comparative evaluation on the electrochemical properties, mechanical properties, and MRI compatibility of different kinds of carbon-based fiber materials, including carbon nanotube fibers, graphene fibers, and carbon fibers. We also developed a strategy to improve the stability of the electrode insulation without sacrificing the flexibility of the implantable depth electrodes by sandwiching an inorganic barrier layer inside the polymer insulation film. These studies provide us with important insights into choosing the most suitable materials for next-generation implantable depth electrodes with unique capabilities for applications in both fundamental and translational neuroscience research.

Indexed as

biocompatibilitybrain activity mappingcarbon nanomaterialsmulti-modal neural interfacingsoft bioelectronics

Identifiers

PMID35002602
PMCPMC8730365
OpenAlexW4200487041

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.