Modeling selective attention using a neuromorphic analog VLSI device

Attentional mechanisms are required to overcome the problem of flooding a l imited processing capacity system with information. They are present in bio logical sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) c hip, using analog neuromorphic circuits. The chip exploits a spike-based re presentation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the sele ctive attention mechanism and provide experimental data for each circuit. W e demonstrate the expected behavior of the model at the system level by sti mulating the chip with both artificially generated control signals and sign als obtained from a saliency may, computed from an image containing several salient features.