Modeling Selective Attention Using a Neuromorphic Analog VLSI Device
Neural Computation
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Selective attention is a mechanisms used to sequentially select the spatial locations of salient regions in the sensor's field of view. This mechanism overcomes the problem of flooding limited processing capacity systems with sensory information. It is found in many biological sensory systems and can be a useful engineering tool for artificial visual systems. We present a hardware model of a selective attention mechanism implemented on a VLSI chip, using analog neuromorphic circuits. The chip makes use of a spike-based representation for receiving input signals, transmitting output signals and for shifting the selection of the attended input stimulus over time. The chip can be interfaced to neuromorphic sensors and actuators, for implementing multi-chip selective attention systems. We describe the characteristics of the circuits used in the architecture and present experimental data measured from the system.