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- W4387242005 abstract "Brain-inspired neuromorphic computing is currently being investigated for effective artificial intelligence (AI) systems. The development of artificial neurons and synapses is imperative to creating efficient computational biomimetic networks. Here we propose the minimal configuration of an effective iontronic spiking neuron based on a conical nanofluidic pore ionic diode. The conductance is composed of a Boltzmann open channel probability and a blocking inactivation function, forming the structure of a memristor. The presence of a negative resistance and the combination of activation–deactivation dynamics cause a Hopf bifurcation. Using the characteristic frequencies of small perturbation impedance spectroscopy, we discuss the conditions of spiking, in which the system enters a limit cycle oscillation. We arrive at the conclusion that an excitable neuron-like system can be made with a single active channel instead of the more complex combination of multiple channels that occurs in the Hodgkin–Huxley neuron model." @default.
- W4387242005 created "2023-10-03" @default.
- W4387242005 creator A5085306500 @default.
- W4387242005 date "2023-10-02" @default.
- W4387242005 modified "2023-10-14" @default.
- W4387242005 title "Iontronic Nanopore Model for Artificial Neurons: The Requisites of Spiking" @default.
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- W4387242005 doi "https://doi.org/10.1021/acs.jpclett.3c02562" @default.
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