Spatial attention in asynchronous neural networks

Rufin van Rullen, Simon J. Thorpe

Abstract: We propose a simple mechanism for spatial visual attention that involves selectively lowering the thresholds of neurons with receptive fields in the attended region. Whereas such a mechanism is of no use in classical artificial neural networks, where all activities for each position in the visual field are computed simultaneously, it can be of great interest in an asynchronous neural network, where the relative order of firing in a population of neurons constitutes the code. Since neurons in the attended region will tend to reach threshold and fire earlier, they will tend to dominate later stages of processing. We illustrate this hypothesis with simulations based on SpikeNET.