Abstract

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Visual marking: prioritising selection for new objects by top-down attentional inhibition of old objects. Psychol. Rev. 104 (1997) 90–122] presented evidence that the prioritisation of new information in search tasks depends, at least in part, on the active ignoring of old items–a process they termed visual marking. In the present paper we present for the first time an explicit computational model of visual marking using a biologically plausible neural network. The model incorporates different synaptic components and a frequency adaptation mechanism, which acts to suppress the previously attended items. We show that, when coupled with a process of active inhibition to the old items, the pattern of preview search can be captured, as well as both efficient and inefficient search patterns in baseline conditions. The simulations point to the involvement of both active and passive inhibitory mechanisms in the preview effect in human search.

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