A Habituation Sensory Nervous System with Memristors

Abstract

The sensory nervous system (SNS) builds up the association between external stimuli and the response of organisms. In this system, habituation is a fundamental characteristic that filters out irrelevantly repetitive information and makes the SNS adapt to the external environment. To emulate this critical process in electronic devices, a LixSiOy‐based memristor (TiN/LixSiOy/Pt) is developed where the temporal response under repetitive stimulation is similar to that of habituation. By connecting this synaptic device to a leaky integrate‐and‐fire neuron based on a Ag/SiO2:Ag/Au memristor, a fully memristive SNS with habituation is experimentally demonstrated. Finally, a habituation spiking neural network based on the SNS is built and its application in obstacle avoidance for robot navigation is successfully presented. The results provide that a direct emulation of the biologically inspired learning process by memristors could be a sound choice for neuromorphic hardware implementation.

A dual-functional Ta/TaOx/Ru device with both nonlinear selector and resistive switching behaviors

“…4,5 Due to the direct accomplishment of dot products through Ohm's and Kirchhoff's laws, the memristor crossbar arrays are very suitable for some specic applications, for example, neuromorphic computing systems. [6][7][8][9][10][11] However, the array size in state-of-theart memristor-based neuromorphic computing is small, limiting the practical applications of memristive computing systems. To achieve large-scale arrays, a stable and uniform resistive switching device is a basic requirement.…”

Adaptive Latent Inhibition in Associatively Responsive Optoelectronic Synapse

“…Classical conditioning involves intimate association by pairing two neural inputs (unconditioned and conditioned stimuli) and is often illustrated by the example of Pavlov's salivating dog. [18,19,39,40] Latent inhibition differs from sensitization and habituation in the type of memory acquisition; latent inhibition is a characteristic in the associative learning paradigm while sensitization and habituation [41,42] are forms of nonassociative learning. From previous experiments, optical pulses were capable of inducing persistent weight changes, and hence chosen as biologically salient unconditioned stimulus (US).…”

An artificial olfactory inference system based on memristive devices

“…Considering the memory‐driven computation in biological neural networks, an artificial olfactory system integrates gas sensors and a compute‐in‐memory system, which enhances the power efficiency 4‐6 . To emulate the functions of a biological olfactory system, artificial olfactory systems implemented by sensor arrays and inference systems, 7‐9 have been successfully applied in many areas, for example, food and beverage industry, agriculture and forestry, medicine and healthcare, indoor and outdoor air‐quality monitoring 1,10 .…”

“…As a result, the neural network rapidly learned gases online and was robust to noises 21 . Moreover, neuromorphic computing architectures based on SNN integrates sensors, computing cores and memories on one chip, processing sensing data in real‐time with high power efficiency 5,22‐24 . However, SNNs are incompatible with current computing architecture and need specific circuits 25‐27 .…”