Neural mechanism for noise exclusion in spatial cueing

Spatial cueing in an orientation discrimination task with targets embedded in high or low external noise indicates noise exclusion as a primary mechanism for attentional modulation. To implement noise exclusion in a neural network, a new mechanism is proposed based on a dendritic computation of difference between self-inhibition and lateral inhibition signals. A computer simulation illustrates that the model exhibits a strong cueing effect for high noise input and no effect when the noiseless input is presented, as is consistent with behavioral signatures of noise exclusion. It is argued that the model could also exhibit object-based selection if uniform activity distribution is assumed for all cells representing the object.