Synaptic plasticity is believed to underlie the formation of appropriate patterns of connectivity that stabilize stimulus-selective reverberations in the cortex. Here we present a ...
This paper explores the computational consequences of simultaneous intrinsic and synaptic plasticity in individual model neurons. It proposes a new intrinsic plasticity mechanism ...
Several formulations of correlation-based Hebbian learning are reviewed. On the presynaptic side, activity is described either by a firing rate or by presynaptic spike arrival. The...
Hebbian learning has been a staple of neural-network models for many years. It is well known that the most straight-forward implementations of this popular learning rule lead to u...
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...