Evidence map›Paper›PMID 40817187›Full record

ArticleNature nanotechnology2025

High-order dynamics in an ultra-adaptive neuromorphic vision device.

Jiayi Xu, Biyi Jiang, Weizhen Wang, Zhifeng Guo, Junsen Gao, Xinyan Hu, Jingkai Qin, Liang Ran, Longyang Lin, Songhua Cai and 2 more

Abstract read
In one paragraph

Article in Nature nanotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Low-Latency Visuotactile Neuron Using Self-Oscillating Memristor.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Materials and System Design for Self-Decision Bioelectronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  11. Devices, Functions, and Applications of Artificial Neuromorphic Visual Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

12 authors.

Jiayi Xu *School of Microelectronics, Southern University of Science and Technology, Shenzhen, China.
Biyi Jiang *School of Microelectronics, Southern University of Science and Technology, Shenzhen, China.
Weizhen Wang *Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China.ORCID http://orcid.org/0009-0009-6655-1589
Zhifeng GuoSchool of Microelectronics, Southern University of Science and Technology, Shenzhen, China.
Junsen GaoSchool of Microelectronics, Southern University of Science and Technology, Shenzhen, China.
Xinyan HuSchool of Microelectronics, Southern University of Science and Technology, Shenzhen, China.
Jingkai QinSchool of Integrated Circuits, Harbin Institute of Technology (Shenzhen), Shenzhen, China.ORCID http://orcid.org/0000-0002-0737-3614
Liang RanBeijing Pixelcore Technology Co. Ltd, Beijing, China.
Longyang LinSchool of Microelectronics, Southern University of Science and Technology, Shenzhen, China.ORCID http://orcid.org/0000-0002-4702-737X
Songhua CaiDepartment of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China. songhua.cai@polyu.edu.hk.ORCID http://orcid.org/0000-0003-3839-2030
Yida LiSchool of Microelectronics, Southern University of Science and Technology, Shenzhen, China. liyd3@sustech.edu.cn.ORCID http://orcid.org/0000-0002-5675-582X
Feichi ZhouSchool of Microelectronics, Southern University of Science and Technology, Shenzhen, China. zhoufc@sustech.edu.cn.ORCID http://orcid.org/0000-0001-7756-1082

Funding

National Natural Science Foundation of China (National Science Foundation of China) 62104091, 52273246National Natural Science Foundation of China (National Science Foundation of China) 62174074
6 · The paper itself

Abstract

Neuromorphic hardware for artificial general vision intelligence holds the potential to match and surpass biological visual systems by processing complex visual dynamics with high adaptability and efficiency. However, current implementations rely on multiple complementary metal-oxide-semiconductor or neuromorphic elements, leading to significant area and power inefficiencies and system complexity. This is owing to a key challenge that no single electronic device, to our knowledge, has yet been demonstrated that can integrate retina-like and cortex-like spiking and graded neuronal dynamics operable across both optical and electrical domains. Here we report a single ultra-adaptive neuromorphic vision device (I

Indexed as

Artificial IntelligenceNeuronsVision, OcularEquipment DesignHumansNanotechnologyNeural Networks, ComputerSemiconductors

Identifiers

PMID40817187
PMCPMC12534183

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.