Network of integrate-and-fire neurons using Rank Order Coding B: spike timing dependant plasticity and emergence of orientation selectivity
Abstract
Rank Order Coding is an alternative to conventional rate coding schemes that uses the order in which a neuron’s inputs fire to encode information. In a visual system framework, we simulated the asynchronous waves of retinal spikes produced in response to natural scenes and used them to stimulate integrate-and-fire V1 neurons that implemented a standard learning rule based on spike timing. After propagating thousands of images, orientation like receptive fields arise in these neurons despite the …
Type
Publication
Neurocomputing
Laurent U Perrinet
Researcher in Computational Neuroscience
My research interests include Machine Learning and computational neuroscience applied to Vision.
