Implementing position-invariant detection of feature-conjunctions in a network of spiking neurons

The design of neural networks that are able to efficiently detect conjunctions of features is an important open challenge. We develop a feedforward spiking neural network that requires a constant number of neurons for detecting a conjunction irrespective of the size of the retinal input field, and for up to four simultaneously present feature-conjunctions.