A Neurodynamic Model of Feature-Based Spatial Selection - Marić, Mateja; Domijan, Dražen (Frontiers in Psychology, 2018)
Huang and Pashler [2007, Psychological Review, 114(3), 599-631] suggested that feature-based attention creates a special form of spatial representation, which is termed a Boolean map. It partitions the visual scene into two distinct and complementary regions: selected and not selected. Here, we developed a model of a recurrent competitive network that is capable of state-dependent computation. It selects multiple winning locations based on a joint top-down cue. We augmented a model of the WTA circuit that is based on linear-threshold units with two computational elements: dendritic nonlinearity that acts on the excitatory units and activity-dependent modulation of synaptic transmission between excitatory and inhibitory units. Computer simulations showed that the proposed model could create a Boolean map in response to a featured cue and elaborate it using the logical operations of intersection and union. In addition, it was shown that in the absence of top-down guidance, the model is sensitive to bottom-up cues such as saliency and abrupt visual onset.