Evidence map›Paper›PMID 42209470›Full record

ArticleNature communications2026

Homeostatic dendritic neuron based on co-integrated volatile and non-volatile memristors for neuromorphic processing.

Licheng Zhang, Teng Zhang, Pek Jun Tiw, Xulei Wu, Yuqi Su, Yuchao Yang

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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Licheng ZhangNew Cornerstone Science Laboratory, Guangdong Provincial Key Laboratory of In-Memory Computing Chips, School of Electronic and Computer Engineering, Shenzhen Graduate School, Peking University, Shenzhen, China.
Teng ZhangNew Cornerstone Science Laboratory, Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, China.ORCID http://orcid.org/0000-0003-2011-5940
Pek Jun TiwNew Cornerstone Science Laboratory, Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-7302-9467
Xulei WuNew Cornerstone Science Laboratory, Guangdong Provincial Key Laboratory of In-Memory Computing Chips, School of Electronic and Computer Engineering, Shenzhen Graduate School, Peking University, Shenzhen, China.
Yuqi SuNew Cornerstone Science Laboratory, Guangdong Provincial Key Laboratory of In-Memory Computing Chips, School of Electronic and Computer Engineering, Shenzhen Graduate School, Peking University, Shenzhen, China.
Yuchao YangNew Cornerstone Science Laboratory, Guangdong Provincial Key Laboratory of In-Memory Computing Chips, School of Electronic and Computer Engineering, Shenzhen Graduate School, Peking University, Shenzhen, China. yuchaoyang@pku.edu.cn.ORCID http://orcid.org/0000-0003-4674-4059

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuromorphic systems offer energy-efficient solutions for temporal signal processing by emulating the dynamics and heterogeneity of biological neural circuits. However, conventional approaches face challenges in adaptive regulation and in capturing multi-timescale temporal features. Here, we present a bio-inspired neuromorphic hardware system that integrates homeostatic neurons with programmable dendritic structures. Utilizing the threshold-switching characteristics of VO

Indexed as

DendritesHomeostasisNeural Networks, ComputerNeuronsSignal Processing, Computer-AssistedAction PotentialsModels, Neurological

Identifiers

PMID42209470
PMCPMC13388921

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.