Evidence map›Paper›PMID 33837210›Full record

ArticleNature communications2021

A biomimetic neural encoder for spiking neural network.

Shiva Subbulakshmi Radhakrishnan, Amritanand Sebastian, Aaryan Oberoi, Sarbashis Das, Saptarshi Das

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Low-Latency Visuotactile Neuron Using Self-Oscillating Memristor.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Advances in Metal Halide Perovskite Memristors: A Review from a Co-Design Perspective.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  12. Emerging 2D Ferroelectric Devices for In-Sensor and In-Memory Computing.Advanced materials (Deerfield Beach, Fla.) · 2025
    Review
  13. Article
  14. All-Ferroelectric Spiking Neural Networks via Morphotropic Phase Boundary Neurons.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  15. Brain-Inspired Architecture for Spiking Neural Networks.Biomimetics (Basel, Switzerland) · 2024
    Article
  16. Toward Practical Single-Molecule/Atom Switches.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  17. Article
  18. Review
  19. Artificial sensory system based on memristive devices.Exploration (Beijing, China) · 2024
    Review
  20. 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

5 authors.

Shiva Subbulakshmi RadhakrishnanDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-1136-7425
Amritanand SebastianDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-4558-0013
Aaryan OberoiDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-1001-2198
Sarbashis DasDepartment of Electrical Engineering, Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-4553-5693
Saptarshi DasDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, USA. sud70@psu.edu.ORCID 0000-0002-0188-945X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting biologically plausible neurons that offer faster inference, lower energy expenditure, and event-driven information processing capabilities. However, implementation of SNNs in future neuromorphic hardware requires hardware encoders analogous to the sensory neurons, which convert external/internal stimulus into spike trains based on specific neural algorithm along with inherent stochasticity. Unfortunately, conventional solid-state transducers are inadequate for this purpose necessitating the development of neural encoders to serve the growing need of neuromorphic computing. Here, we demonstrate a biomimetic device based on a dual gated MoS

Indexed as

Biomimetic MaterialsNeural Networks, ComputerTransistors, ElectronicAction PotentialsAlgorithmsBiomimeticsDatasets as TopicHumansNerve NetSensory Receptor CellsVisual Cortex

Identifiers

PMID33837210
PMCPMC8035177

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.