Elisabetta Chicca

TL;DR: In this article, a mixed-mode analog/digital VLSI device comprising an array of leaky integrate-and-fire (I&F) neurons, adaptive synapses with spike-timing dependent plasticity, and an asynchronous event based communication infrastructure is presented.

TL;DR: In this article, a set of neuromorphic engineering solutions for fast simulations of spiking neural networks is proposed, which can emulate neural and synaptic dynamics in real time and discuss the role of biophysically realistic temporal dynamics in hardware neural processing architectures.

TL;DR: In this article, a set of neuromorphic engineering solutions for fast simulations of spiking neural networks is proposed, which can emulate neural and synaptic dynamics in real time and discuss the role of biophysically realistic temporal dynamics in hardware neural processing architectures; the challenges of realizing spike-based plasticity mechanisms in real physical systems and present examples of analog electronic circuits that implement them.

TL;DR: The full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning is described.

TL;DR: Neuromorphic Engineering (NE) encompasses a diverse range of approaches to information processing that are inspired by neurobiological systems, and this feature distinguishes neuromorphic systems from conventional computing systems as discussed by the authors.