A Tantalum Disulfide Charge-Density-Wave Stochastic Artificial Neuron for Emulating Neural Statistical Properties

Abstract

Artificial neuronal devices that functionally resemble biological neurons are important toward realizing advanced brain emulation and for building bioinspired electronic systems. In this Communication, the stochastic behaviors of a neuronal oscillator based on the charge-density-wave (CDW) phase transition of a 1T-TaS2 thin film are reported, and the capability of this neuronal oscillator to generate spike trains with statistical features closely matching those of biological neurons is demonstrated. The stochastic behaviors of the neuronal device result from the melt-quench-induced reconfiguration of CDW domains during each oscillation cycle. Owing to the stochasticity, numerous key features of the Hodgkin-Huxley description of neurons can be realized in this compact two-terminal neuronal oscillator. A statistical analysis of the spike train generated by the artificial neuron indicates that it resembles the neurons in the superior olivary complex of a mammalian nervous system, in terms of its interspike interval distribution, the time-correlation of spiking behavior, and its response to acoustic stimuli.

Artificial Neuronal Devices Based on Emerging Materials: Neuronal Dynamics and Applications

“…More detailed investigations reveal the firing activity of memristive and IMT neurons possessing intrinsic stochasticity and chaotic dynamics. [ 17b,39,41,44 ] The stochasticity originates from the filament residue or the rearrangement of crystal domains. [ 17b,45 ] The threshold voltages of switching are not fixed but have cycle‐to‐cycle variations, as shown in Figure a.…”

Neuro-inspired electronic skin for robots

“…Such a design can emulate almost all the spiking features discovered in biological neurons including tonic and phasic spiking, tonic and phasic bursting, frequency adaptation (Figure 3C) (83), thus can be used to realize a neural system with rich neural dynamics. It is also possible to implement a neuron circuit with only one phase change device (84)(85)(86), although in this case the spiking signal generated cannot fully mimic the biological spiking features. Overall, the phase change device-based design offers the lowest hardware complexity (Figure 3F).…”

Configurable NbOx Memristors as Artificial Synapses or Neurons Achieved by Regulating the Forming Compliance Current for the Spiking Neural Network

“…[13][14][15][16] Recently, multiple types of biological synaptic plasticity are realized by using resistiveswitching (RS) memristors, [17][18][19] and various biological neuronal functions have been achieved based on threshold-switching (TS) memristors. [20][21][22] However, most of the reported memristors exhibit only RS or TS properties. If the switching properties of a memristor can be configured after the fabrication, the fabrication process of neuromorphic chip will be greatly simplified and the integration scale greatly enhanced.…”