Evidence map›Paper›PMID 42669703›Full record

ArticleNature communications2026

Spinal-inspired artificial tactile interneuron with high-order burst spiking for intelligent edge interfaces.

Fanfan Li, Zhanglu Yan, Jiayi Mao, Guolei Liu, Huihui Ren, Bangbang Qin, Zhongfang Zhang, Haiyue Zhang, Yiyang Shen, Zeqi Zheng and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Fanfan Li *School of Materials Science and Engineering, Zhejiang University, Hangzhou, China.
Zhanglu Yan *School of Computing, National University of Singapore, Singapore, Singapore.
Jiayi MaoZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Guolei LiuZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Huihui RenSchool of Materials Science and Engineering, Zhejiang University, Hangzhou, China.
Bangbang QinZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Zhongfang ZhangZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Haiyue ZhangZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Yiyang ShenZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Zeqi ZhengDepartment of Artificial Intelligence, School of Engineering, Westlake University, Hangzhou, China.
Weilong FengZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Dingwei LiZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.
Yingjie TangZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China.ORCID 0000-0002-6062-8807
Saisai WangWestlake Institute for Optoelectronics, Westlake University, Hangzhou, China.
Yaochu JinDepartment of Artificial Intelligence, School of Engineering, Westlake University, Hangzhou, China.ORCID 0000-0003-1100-0631
Tao LuoInstitute of High Performance Computing, Agency for Science, Technology and Research, Singapore, Singapore.
Weng-Fai WongSchool of Computing, National University of Singapore, Singapore, Singapore.
Hong WangKey Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an, China. hongwang@xidian.edu.cn.ORCID 0000-0002-0213-3523
Bowen ZhuZhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, China. zhubowen@westlake.edu.cn.ORCID 0000-0001-7534-9723

Funding

National Natural Science Foundation of China (National Science Foundation of China) 92464105, 62574169, 62504208Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) LQKWL26F0401, D25F020001
6 · The paper itself

Abstract

Human tactile perception relies on hierarchical processing, where inputs entering the nervous system are fused by interneurons for sparse multimodal encoding, and the integrated signals are sent to the brain to generate perception. Replicating this pathway from primary sensory inputs to higher-order neural processing, which efficiently transforms signals into coherent representations of the external environment, is essential for artificial tactile systems. Here we present artificial multimodal interneuron (AMINs) by integrating strain, pressure, and temperature sensors with NbO

Indexed as

InterneuronsTouchTouch PerceptionAction PotentialsHumansModels, Neurological

Identifiers

PMID42669703
PMCPMC13526877

What OpenQuestion holds

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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.