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Analyzing spike-timing-dependent plasticity in recurrent neuronal networks »

Matthieu Gilson, Anthony Burkitt, David Grayden, Doreen Thomas, and Leo van Hemmen

A mathematical framework is being used to investigate the learning dynamics induced by a class of biologically realistic synaptic plasticity rules in recurrently connected neuronal networks.
Audio-visual sensor fusion for object localization »

Vincent Chan

Using the onset time of stimuli, a biologically-inspired system learns to identify the sources of sounds.
Spike-based synaptic plasticity and classification on VLSI »

Srinjoy Mitra and Giacomo Indiveri

A VLSI system implements a bioplausible spike-based learning algorithm and is capable of robust classification of binary patterns, even when they are highly correlated.
The iCub cometh »

Sunny Bains

I've been taking a break from writing to work on another project this spring and summer but managed to find the time to finish off a story about the iCub. This open-source robot is designed to allow academics to concentrate...
Supervised learning in spiking neural networks »

Filip Ponulak

A learning method called ReSuMe allows fast convergence and optimal solution stability.


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