Evidence map›Paper›PMID 33036975›Full record

ArticleScience advances2020

Multichannel parallel processing of neural signals in memristor arrays.

Zhengwu Liu, Jianshi Tang, Bin Gao, Xinyi Li, Peng Yao, Yudeng Lin, Dingkun Liu, Bo Hong, He Qian, Huaqiang Wu

Abstract read
In one paragraph

Article in Science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
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  5. Article
  6. Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
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  8. Article
  9. Article
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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

10 authors.

Zhengwu LiuInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.ORCID 0000-0001-7968-9469
Jianshi TangInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China. jtang@tsinghua.edu.cn wuhq@tsinghua.edu.cn.ORCID 0000-0001-8369-0067
Bin GaoInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.ORCID 0000-0002-2417-983X
Xinyi LiInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.ORCID 0000-0003-1264-6258
Peng YaoInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.ORCID 0000-0003-0172-4310
Yudeng LinInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.ORCID 0000-0002-0013-6245
Dingkun LiuDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.ORCID 0000-0002-1262-8458
Bo HongDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.ORCID 0000-0003-2900-6791
He QianInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.
Huaqiang WuInstitute of Microelectronics, Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China. jtang@tsinghua.edu.cn wuhq@tsinghua.edu.cn.ORCID 0000-0001-8359-7997

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fully implantable neural interfaces with massive recording channels bring the gospel to patients with motor or speech function loss. As the number of recording channels rapidly increases, conventional complementary metal-oxide semiconductor (CMOS) chips for neural signal processing face severe challenges on parallelism scalability, computational cost, and power consumption. In this work, we propose a previously unexplored approach for parallel processing of multichannel neural signals in memristor arrays, taking advantage of their rich dynamic characteristics. The critical information of neural signal waveform is extracted and encoded in the memristor conductance modulation. A signal segmentation scheme is developed to adapt to device variations. To verify the fidelity of the processed results, seizure prediction is further demonstrated, with high accuracy above 95% and also more than 1000× improvement in power efficiency compared with CMOS counterparts. This work suggests that memristor arrays could be a promising multichannel signal processing module for future implantable neural interfaces.

Identifiers

PMID33036975
PMCPMC7546699

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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.