Spiking neural network (SNN) is a new generation of artificial neural networks (ANNs),
which is more analogous with the brain. It has been widely considered with neural …

A neuroprosthesis is a type of precision medical device that is intended to manipulate the
neuronal signals of the brain in a closed-loop fashion, while simultaneously receiving stimuli …

Spiking neural networks (SNNs) are bio-inspired neural networks with asynchronous
discrete and sparse characteristics, which have increasingly manifested their superiority in …

Spiking Neural Networks (SNNs) have been attached great importance due to their
biological plausibility and high energy-efficiency on neuromorphic chips. As these chips are …

The temporal credit assignment problem, which aims to discover the predictive features
hidden in distracting background streams with delayed feedback, remains a core challenge …

Address event representation (AER) cameras have recently attracted more attention due to
the advantages of high temporal resolution and low power consumption, compared with …

This article proposes an unsupervised address event representation (AER) object
recognition approach. The proposed approach consists of a novel multiscale spatio …

In this article, we present a systematic computational model to explore brain-based
computation for object recognition. The model extracts temporal features embedded in …

Spiking neural networks (SNNs), inspired by the neuronal network in the brain, provide
biologically relevant and low-power consuming models for information processing. Existing …

Spiking Neural Networks (SNNs) are more biologically plausible and computationally
efficient. Therefore, SNNs have the natural advantage of drawing the sparse structural …