ArticleNature communications2018
Spike-timing-dependent plasticity learning of coincidence detection with passively integrated memristive circuits.
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 38 papers.
What it found
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Who cites it
38 citing papers in PubMed.
- Irregular and bursty neuronal firing extend spike-timing dependent plasticity window to behavioral timescales.iScience · 2026Article
- Analog Synaptic Plasticity in 2D Layered Material Iontronic Memtransistors for Brain-Inspired Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Epitaxial BiAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Polymer-Based Linear and Symmetric Artificial Synaptic Memristors for Accurate and Reliable Neuromorphic Computing Applications.Nanomaterials (Basel, Switzerland) · 2026Review
- NeoHebbian synapses to accelerate online training of neuromorphic hardware.Scientific reports · 2026Article
- Topological hysteretic winding for temporal anti-lasing.Nature communications · 2025Article
- Amorphous boron nitride: synthesis, properties and device application.Nano convergence · 2025Review
- IGZO-Based Electronic Device Application: Advancements in Gas Sensor, Logic Circuit, Biosensor, Neuromorphic Device, and Photodetector Technologies.Micromachines · 2025Review
- The precision principle: driving biological self-organization.Frontiers in network physiology · 2025Article
- Optimization strategy of the emerging memristors: From material preparation to device applications.iScience · 2024Review
- Synaptic Response of Fluidic Nanopores: The Connection of Potentiation with Hysteresis.Chemphyschem : a European journal of chemical physics and physical chemistry · 2024Article
- An emergent attractor network in a passive resistive switching circuit.Nature communications · 2024Article
- Ultra-low power carbon nanotube/porphyrin synaptic arrays for persistent photoconductivity and neuromorphic computing.Nature communications · 2024Article
- Hardware implementation of memristor-based artificial neural networks.Nature communications · 2024Review
- Recent Advances in In-Memory Computing: Exploring Memristor and Memtransistor Arrays with 2D Materials.Nano-micro letters · 2024Review
- A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing.Nature communications · 2023Article
- Emerging memristive neurons for neuromorphic computing and sensing.Science and technology of advanced materials · 2023Review
- Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse.Nature communications · 2022Article
- Memory-inspired spiking hyperdimensional network for robust online learning.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spiking neural networks, the most realistic artificial representation of biological nervous systems, are promising due to their inherent local training rules that enable low-overhead online learning, and energy-efficient information encoding. Their downside is more demanding functionality of the artificial synapses, notably including spike-timing-dependent plasticity, which makes their compact efficient hardware implementation challenging with conventional device technologies. Recent work showed that memristors are excellent candidates for artificial synapses, although reports of even simple neuromorphic systems are still very rare. In this study, we experimentally demonstrate coincidence detection using a spiking neural network, implemented with passively integrated metal-oxide memristive synapses connected to an analogue leaky-integrate-and-fire silicon neuron. By employing spike-timing-dependent plasticity learning, the network is able to robustly detect the coincidence by selectively increasing the synaptic efficacies corresponding to the synchronized inputs. Not surprisingly, our results indicate that device-to-device variation is the main challenge towards realization of more complex spiking networks.
Identifiers
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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.