ArticleFrontiers in neuroscience2015
A memristive spiking neuron with firing rate coding.
Article in Frontiers in neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Thermally Activated Negative Differential Resistance VOACS nano · 2025Article
- Artificial transneurons emulate neuronal activity in different areas of brain cortex.Nature communications · 2025Article
- Electrical Control of Magnetic Resonance in Phase Change Materials.Nano letters · 2024Article
- Article
- Microstructure effects on the phase transition behavior of a prototypical quantum material.Scientific reports · 2022Article
- Structural and Parametric Identification of Knowm Memristors.Nanomaterials (Basel, Switzerland) · 2021Article
- Transverse barrier formation by electrical triggering of a metal-to-insulator transition.Nature communications · 2021Article
- Stochastic Memristive Interface for Neural Signal Processing.Sensors (Basel, Switzerland) · 2021Article
- Engineering Spiking Neurons Using Threshold Switching Devices for High-Efficient Neuromorphic Computing.Frontiers in neuroscience · 2021Article
- A spiking and adapting tactile sensor for neuromorphic applications.Scientific reports · 2020Article
- Non-thermal resistive switching in Mott insulator nanowires.Nature communications · 2020Article
- Evidence of Biorealistic Synaptic Behavior in Diffusive Li-based Two-terminal Resistive Switching Devices.Scientific reports · 2020Article
- A caloritronics-based Mott neuristor.Scientific reports · 2020Article
- Giant nonvolatile resistive switching in a Mott oxide and ferroelectric hybrid.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Concept and modelling of memsensors as two terminal devices with enhanced capabilities in neuromorphic engineering.Scientific reports · 2019Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding. This initiated the development of spiking neuron models; one of today's most powerful conceptual tool for the analysis and emulation of neural dynamics. The success of electronic circuit models and their physical realization within silicon field-effect transistor circuits lead to elegant technical approaches. Recently, the spectrum of electronic devices for neural computing has been extended by memristive devices, mainly used to emulate static synaptic functionality. Their capabilities for emulations of neural activity were recently demonstrated using a memristive neuristor circuit, while a memristive neuron circuit has so far been elusive. Here, a spiking neuron model is experimentally realized in a compact circuit comprising memristive and memcapacitive devices based on the strongly correlated electron material vanadium dioxide (VO2) and on the chemical electromigration cell Ag/TiO2-x /Al. The circuit can emulate dynamical spiking patterns in response to an external stimulus including adaptation, which is at the heart of firing rate coding as first observed by E.D. Adrian in 1926.
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