VLSI implementation of cortical visual motion detection using an analog neural computer

Two dimensional image motion detection neural networks have been implemented using a general purpose analog neural computer. The neural circuits perform spatiotemporal feature extraction based on the cortical motion detection model of Adelson and Bergen. The neural computer provides the neurons, synapses and synaptic time-constants required to realize the model in VLSI hardware. Results show that visual motion estimation can be implemented with simple sum-and-threshold neural hardware with temporal computational capabilities. The neural circuits compute general 2D visual motion in real-time.