Evidence map›Paper›PMID 42045188›Full record

ArticleNature communications2026

Artificial plateau neurons with in-situ spike-malleability for rhythmic quadrupedal locomotion.

Hailiang Wang, Yishu Zhang, Qingao Chai, Qian He, Jiayang Hu, Yongqing Bai, Guanyu Liu, Zongwen Li, Jian Chai, Xin He and 7 more

Abstract read
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

17 authors.

Hailiang WangCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.
Yishu ZhangCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China. zhangyishu@zju.edu.cn.ORCID http://orcid.org/0000-0001-8774-7374
Qingao ChaiCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China.ORCID http://orcid.org/0009-0005-8668-7759
Qian HeCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.ORCID http://orcid.org/0009-0005-8764-2122
Jiayang HuCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.
Yongqing BaiCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.
Guanyu LiuCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.
Zongwen LiCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.
Jian ChaiCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China.
Xin HeZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, Zhejiang, China.ORCID http://orcid.org/0000-0001-7009-2826
Mengze ZhaoState Key Laboratory for Mesoscopic Physics, Frontiers Science Center for Nano-Optoelectronics, School of Physics, Peking University, Beijing, China.
Guodong XueState Key Laboratory for Mesoscopic Physics, Frontiers Science Center for Nano-Optoelectronics, School of Physics, Peking University, Beijing, China.
Kaihui LiuState Key Laboratory for Mesoscopic Physics, Frontiers Science Center for Nano-Optoelectronics, School of Physics, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-8781-2495
Yu FuKey Laboratory of Quantum State Construction and Manipulation, Department of Physics, Renmin University of China, Beijing, China.
Huajin TangCollege of Computer Science and Technology, Zhejiang University, Hangzhou, China. htang@zju.edu.cn.
Yang XuCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China. yangxu-isee@zju.edu.cn.ORCID http://orcid.org/0000-0003-3148-7678
Bin YuCollege of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang, China. yu-bin@zju.edu.cn.ORCID http://orcid.org/0000-0003-0237-6311

Funding

National Natural Science Foundation of China (National Science Foundation of China) DT23F0401Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) LDT23F04011F04
6 · The paper itself

Abstract

Whole-body intelligent locomotion systems face persistent challenges of redundant actuation and poor energy efficiency, limiting real-world deployment. Bio-inspired central pattern generators offer a promising framework for rhythmic control, yet hardware implementations struggle to match the efficiency and adaptability of biological systems. Here, we introduce an in-situ spike-malleable artificial plateau neuron integrating a bistable plateau gate with a transient threshold-switch. The neuron generates amplitude-programmable rhythmic spike bursts, achieving energy-efficient, antagonistic activation of extensors and flexors via a scalable circuit comprising two paired units (plateau gate and threshold-switch). The design leverages distributed encoding for coordinated muscle control, operating at ultra-low energy dissipation (141.37 pJ/spike). An expanded four-unit circuit enhances dynamic spike malleability, enabling parallel processing for multi-joint coordination. On a quadruped robot (Unitree Go2), these distributed circuits directly drive joint-level proportional derivative controllers using the Gaussian-filtered rhythmic spikes, enabling energy-efficient trotting without centralized computation. Critically, the system achieves stable on-ground locomotion and demonstrates adaptive gait transitions in real-world environments. Our approach merges ultra-compact hardware with bio-inspired architecture, advancing neuromorphic systems for energy-efficient autonomous robotics.

Indexed as

LocomotionNeuronsAction PotentialsAnimalsGaitIntelligent SystemsModels, NeurologicalPeriodicityRobotics

Identifiers

PMID42045188
PMCPMC13332192

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.