Evidence map›Paper›PMID 35208323›Full record

ArticleMicromachines2022

Flexible Neural Probes with Optical Artifact-Suppressing Modification and Biofriendly Polypeptide Coating.

Minghao Wang, Ye Fan, Lili Li, Fei Wen, Bangbang Guo, Minyi Jin, Jiahui Xu, Yuhao Zhou, Xiaoyang Kang, Bowen Ji and 2 more

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 12 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

12 authors at 3 institutions in 1 country.

Minghao WangWenzhou Institute of Hangzhou Dianzi University, Wenzhou 310012, China.ORCID 0000-0003-0220-515X
Ye FanWenzhou Institute of Hangzhou Dianzi University, Wenzhou 310012, China.
Lili LiMOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 311101, China.
Fei WenMOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 311101, China.
Bangbang GuoMOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 311101, China.
Minyi JinMOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 311101, China.
Jiahui XuMOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 311101, China.
Yuhao ZhouThe Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China.
Xiaoyang KangLaboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, Fudan University, 220 Handan Rd., Yangpu District, Shanghai 200433, China.
Bowen JiThe Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China.ORCID 0000-0002-2655-4840
Yuhua ChengWenzhou Institute of Hangzhou Dianzi University, Wenzhou 310012, China.
Gaofeng WangMOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 311101, China.ORCID 0000-0001-8599-7249
Hangzhou Dianzi University · CNNorthwestern Polytechnical University · CNFudan University · CN

Funding

China Postdoctoral Science Foundation 2020TQ0246, 2021M692638Fundamental Research Funds for the Provincial Universities of Zhejiang GK199900X001National Key R&D Program of China 2018YFE0120000National Natural Science Foundation of China 62104056National Natural Science Foundation of China 62141409Shanghai Sailing Program 21YF1451000the Fundamental Research Funds for the Central Universities 31020200QD013Zhejiang Provincial Key Research & Development Project 2019C04003Zhejiang Provincial Natural Science Foundation of China LQ21F010010
6 · The paper itself

Abstract

The advent of optogenetics provides a well-targeted tool to manipulate neurons because of its high time resolution and cell-type specificity. Recently, closed-loop neural manipulation techniques consisting of optical stimulation and electrical recording have been widely used. However, metal microelectrodes exposed to light radiation could generate photoelectric noise, thus causing loss or distortion of neural signal in recording channels. Meanwhile, the biocompatibility of neural probes remains to be improved. Here, five kinds of neural interface materials are deposited on flexible polyimide-based neural probes and illuminated with a series of blue laser pulses to study their electrochemical performance and photoelectric noises for single-unit recording. The results show that the modifications can not only improve the electrochemical performance, but can also reduce the photoelectric artifacts. In particular, the double-layer composite consisting of platinum-black and conductive polymer has the best comprehensive performance. Thus, a layer of polypeptide is deposited on the entire surface of the double-layer modified neural probes to further improve their biocompatibility. The results show that the biocompatible polypeptide coating has little effect on the electrochemical performance of the neural probe, and it may serve as a drug carrier due to its special micromorphology.

Indexed as

electrochemical modificationneural interfaceneural probephotoelectric noisepolypeptide

Identifiers

PMID35208323
PMCPMC8877708
OpenAlexW4210412969

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.