ReviewScience and technology of advanced materials2023
Emerging memristive neurons for neuromorphic computing and sensing.
Review in Science and technology of advanced materials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Toward Intelligent Sensing Systems: Non-Equilibrium Materials as Platforms for AI-Enabled Autonomous Discovery.Sensors (Basel, Switzerland) · 2026Article
- Heterosynaptic Memtransistors Based on Switching Operation Mechanism Using Designed Organic/Inorganic Heterostructures for Neuromorphic Electronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Edge-of-chaos operation and persistent dynamics for neuromorphic meminductor computing.Scientific reports · 2025Article
- Additive Manufacturing of Neuromorphic Systems.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Gallium Oxide Memristors: A Review of Resistive Switching Devices and Emerging Applications.Nanomaterials (Basel, Switzerland) · 2025Review
- Memristor-Based Spiking Neuromorphic Systems Toward Brain-Inspired Perception and Computing.Nanomaterials (Basel, Switzerland) · 2025Review
- Memristor Emulator Circuits: Recent Advances in Design Methodologies, Healthcare Applications, and Future Prospects.Micromachines · 2025Review
- Neuromorphic algorithms for brain implants: a review.Frontiers in neuroscience · 2025Review
- Understanding the Resistive Switching Behaviors of Top Electrode (Au, Cu, and Al)-Dependent TiOACS omega · 2024Article
- Harnessing Quantum Capacitance in 2D Material/Molecular Layer Junctions for Novel Electronic Device Functionality.Nanomaterials (Basel, Switzerland) · 2024Article
- Imperfect chimera and synchronization in a hybrid adaptive conductance based exponential integrate and fire neuron model.Cognitive neurodynamics · 2024Article
- Interfacial Resistive Switching of Niobium-Titanium Anodic Memristors with Self-Rectifying Capabilities.Nanomaterials (Basel, Switzerland) · 2024Article
- From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?Brain sciences · 2023Review
- Foreword to the focus issue: materials and technologies for memristors and neuromorphic devices.Science and technology of advanced materials · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inspired by the principles of the biological nervous system, neuromorphic engineering has brought a promising alternative approach to intelligence computing with high energy efficiency and low consumption. As pivotal components of neuromorphic system, artificial spiking neurons are powerful information processing units and can achieve highly complex nonlinear computations. By leveraging the switching dynamic characteristics of memristive device, memristive neurons show rich spiking behaviors with simple circuit. This report reviews the memristive neurons and their applications in neuromorphic sensing and computing systems. The switching mechanisms that endow memristive devices with rich dynamics and nonlinearity are highlighted, and subsequently various nonlinear spiking neuron behaviors emulated in these memristive devices are reviewed. Then, recent development is introduced on neuromorphic system with memristive neurons for sensing and computing. Finally, we discuss challenges and outlooks of the memristive neurons toward high-performance neuromorphic hardware systems and provide an insightful perspective for the development of interactive neuromorphic electronic systems.
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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.