Where-What Network 3: Developmental top-down attention for multiple foregrounds and complex backgrounds

The Where-What Network 3 (WWN-3) is an artificial developmental network modeled after visual cortical pathways, for the purpose of attention and recognition in the presence of complex natural backgrounds. It is general-purpose and not pre-determined to detect a certain type of stimulus. It is a learning network, which develops its weights from images using a supervised paradigm and a local Hebbian learning algorithm. Attention has been thought of as bottom-up or top-down. This paper focuses on the biologically-inspired mechanisms of top-down attention in WWN-3, through top-down excitation that interacts with bottom-up activity at every layer within the network. Top-down excitation in WWN-3 can control the location of attention by imposing a certain location or disengaging from the current location. It can also control what type of object to search for. Paired layers and sparse coding deal with potential hallucination problems. Top-down attention in WWN occurs as soon as an action emerges at a motor layer, which could be imposed by a teacher or internally selected. Given two competing foregrounds in the same scene, WWN showed effective performance in all the attention modes tested.