Simplified calcium signaling cascade for synaptic plasticity.

We propose a model for synaptic plasticity based on a calcium signaling cascade. The model simplifies the full signaling pathways from a calcium influx to the phosphorylation (potentiation) and dephosphorylation (depression) of glutamate receptors that are gated by fictive C1 and C2 catalysts, respectively. This model is based on tangible chemical reactions, including fictive catalysts, for long-term plasticity rather than the conceptual theories commonplace in various models, such as preset thresholds of calcium concentration.

Artificial Neural Network for Response Inference of a Nonvolatile Resistance-Switch Array.

An artificial neural network was utilized in the behavior inference of a random crossbar array (10 × 9 or 28 × 27 in size) of nonvolatile binary resistance-switches (in a high resistance state (HRS) or low resistance state (LRS)) in response to a randomly applied voltage array. The employed artificial neural network was a multilayer perceptron (MLP) with leaky rectified linear units. This MLP was trained with 500,000 or 1,000,000 examples.

Chameleonic electrochemical metallization cells: dual-layer solid electrolyte-inducing various switching behaviours.

We present 'unusual' resistive switching behaviours in electrochemical metallization (ECM) cells utilizing a dual-layer (SiOx/GeSex: SiOx on GeSex) solid electrolyte (SE). The observed switching behaviour markedly varies with the thickness of the upper SiOx layer and compliance current: (i) monostable switching, (ii) counter-eightwise bipolar switching, and (iii) combination of monostable and eightwise bipolar switching behaviours. Focusing on cases (i) and (iii), electrical and chemical analyses on these chameleonic cells were performed in an attempt to gain clues to the understanding of the observed complexity.

Leaky Integrate-and-Fire Neuron Circuit Based on Floating-Gate Integrator.

The artificial spiking neural network (SNN) is promising and has been brought to the notice of the theoretical neuroscience and neuromorphic engineering research communities. In this light, we propose a new type of artificial spiking neuron based on leaky integrate-and-fire (LIF) behavior. A distinctive feature of the proposed FG-LIF neuron is the use of a floating-gate (FG) integrator rather than a capacitor-based one.

Relaxation oscillator-realized artificial electronic neurons, their responses, and noise.

A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor).