Adams et al. present a Spiking Neural Network implementation of a SOM which uses
The model due to Cuppini et al. develops low-level multisensory integration (spatial principle) such that integration happens only with higher-level input.
In their model, Hebbian learning leads to sharpening of receptive fields, overlap of receptive fields, and Integration through higher-cognitive input.⇒
Deneve describes how neurons performing Bayesian inference on variables behind Poisson inputs can learn the parameters of the Poisson processes in an online variant of the expectation maximization (EM) algorithm.⇒