ArticleNature communications2018
Biological plausibility and stochasticity in scalable VO
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers.
What it found
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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.
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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.
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Who cites it
118 citing papers in PubMed.
- Temporally Correlated Stochastic Spiking Neural Networks Enabled by 2D Ferroelectric Synapse-Neuron Integration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Noise-Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency-Selective Time-Series Signal Encoding.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Viscoelastic nanomechanical devices for neuromorphic information processing.Science advances · 2026Article
- A Reconfigurable Memristive Spiking Neuron Enabling Advanced Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Instability-driven electrohydrodynamic neurons for probabilistic computing.Nature communications · 2026Article
- Multifunctional electrochemical memory stabilized by phase coexistence.Science advances · 2026Article
- Spiking without Resets: Continuous Integrate-and-Fire Dynamics in Neuronal Circuits.The journal of physical chemistry letters · 2026Article
- Diffusive memristors in the edge of chaos.Nature communications · 2026Article
- Volatile self-selective memristive neuron for millisecond-latency neuromorphic object detection at the edge.Nature communications · 2026Article
- An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing.Journal of the American Chemical Society · 2026Article
- Self-Oscillatory Neuron-like Devices for Unconventional Computing Applications.Chemical reviews · 2026Review
- Neuromorphic Near-Sensor and In-Sensor Computing Enabled by Next-Generation Material-Based Sensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Printed MoSNature nanotechnology · 2026Article
- Printed devices turn neuromorphic.Nature nanotechnology · 2026Article
- Explicit electrothermal LLP VOScientific reports · 2026Article
- Advances in Gel-Based Electrolyte-Gated Flexible Visual Synapses for Neuromorphic Vision Systems.Gels (Basel, Switzerland) · 2026Review
- Accelerating spiking neural networks with photonic reconfigurable devices.Nature communications · 2026Article
- Monolithic cell-on-memristor architecture enables wafer-scale integration of oscillatory chemoreceptors for bio-realistic gustatory chips.Nature materials · 2026Article
- Bridged artificial neurons based on memristor circuit for spiking propagation network and coincidence detection.iScience · 2026Article
- Near field optical visualization of the nanoscale phase percolation dynamics of a VONature communications · 2026Article
58 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuromorphic networks of artificial neurons and synapses can solve computationally hard problems with energy efficiencies unattainable for von Neumann architectures. For image processing, silicon neuromorphic processors outperform graphic processing units in energy efficiency by a large margin, but deliver much lower chip-scale throughput. The performance-efficiency dilemma for silicon processors may not be overcome by Moore's law scaling of silicon transistors. Scalable and biomimetic active memristor neurons and passive memristor synapses form a self-sufficient basis for a transistorless neural network. However, previous demonstrations of memristor neurons only showed simple integrate-and-fire behaviors and did not reveal the rich dynamics and computational complexity of biological neurons. Here we report that neurons built with nanoscale vanadium dioxide active memristors possess all three classes of excitability and most of the known biological neuronal dynamics, and are intrinsically stochastic. With the favorable size and power scaling, there is a path toward an all-memristor neuromorphic cortical computer.
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Registered trials
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.