Evidence map›Paper›PMID 40593563›Full record

ArticleNature communications2025

Experimental demonstration of third-order memristor-based artificial sensory nervous system for neuro-inspired robotics.

See-On Park, Hakcheon Jeong, Seokho Seo, Youna Kwon, Jongwon Lee, Shinhyun Choi

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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

6 authors.

See-On ParkSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID http://orcid.org/0000-0002-4273-4438
Hakcheon JeongSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID http://orcid.org/0000-0003-1654-825X
Seokho SeoSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID http://orcid.org/0000-0001-9134-9379
Youna KwonNano Convergence Technology Division, National Nanofab Center (NNFC), Daejeon, Republic of Korea.
Jongwon LeeDepartment of Semiconductor Convergence, Chungnam National University, Daejeon, Republic of Korea. jwlee80@cnu.ac.kr.ORCID http://orcid.org/0000-0002-2114-8982
Shinhyun ChoiSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. shinhyun@kaist.ac.kr.ORCID http://orcid.org/0000-0002-5852-3360

Funding

National Research Foundation of Korea (NRF) 2020R1C1C1007464National Research Foundation of Korea (NRF) 2022M3F3A2A01072851National Research Foundation of Korea (NRF) 2022M3I7A2078273National Research Foundation of Korea (NRF) RS-2024-00401234
6 · The paper itself

Abstract

The sensory nervous system in animals enables the perception of external stimuli. Developing an artificial sensory nervous system has been widely conducted to realize neuro-inspired robots capable of effectively responding to external stimuli. However, it remains challenging to develop artificial sensory nervous systems that possess sophisticated biological functions, such as habituation and sensitization, enabling efficient responses without bulky peripheral circuitry. Here, we introduce a memristor device with third-order switching complexity, emulating an artificial synapse that inherently possesses habituation and sensitization properties. Incorporating an additional resistive switching TiO

Indexed as

RoboticsAnimalsBiomimetics

Identifiers

PMID40593563
PMCPMC12215477

What OpenQuestion holds

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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.