— We propose a modeling framework based on the event-driven paradigm for populations of neurons which interchange messages. Unlike other strategies our approach is focused on the...
Inspired by the behaviour of biological receptive fields and the human visual system, a network model based on spiking neurons is proposed to detect edges in a visual image. The st...
Qingxiang Wu, T. Martin McGinnity, Liam P. Maguire...
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
The persistent modification of synaptic efficacy as a function of the relative timing of pre- and postsynaptic spikes is a phenomenon known as spiketiming-dependent plasticity (...
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...